diff --git a/.gitignore b/.gitignore
index 05b37627bd..15cac247ed 100644
--- a/.gitignore
+++ b/.gitignore
@@ -17,8 +17,10 @@ filtered_rat.txt
 dev/dist
 apache-rat-*.jar
 venv
+.venv
 dev/release/comet-rm/workdir
 spark/benchmarks
 .DS_Store
 comet-event-trace.json
 __pycache__
+output
diff --git a/dev/benchmarks/.gitignore b/benchmarks/tpc/.gitignore
similarity index 100%
rename from dev/benchmarks/.gitignore
rename to benchmarks/tpc/.gitignore
diff --git a/benchmarks/tpc/README.md b/benchmarks/tpc/README.md
new file mode 100644
index 0000000000..e8bb0c3a15
--- /dev/null
+++ b/benchmarks/tpc/README.md
@@ -0,0 +1,381 @@
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+# Comet Benchmarking Scripts
+
+This directory contains scripts used for generating benchmark results that are published in this repository and in
+the Comet documentation.
+
+For full instructions on running these benchmarks on an EC2 instance, see the [Comet Benchmarking on EC2 Guide].
+
+[Comet Benchmarking on EC2 Guide]: https://datafusion.apache.org/comet/contributor-guide/benchmarking_aws_ec2.html
+
+## Setup
+
+TPC queries are bundled in `benchmarks/tpc/queries/` (derived from TPC-H/DS under the TPC Fair Use Policy).
+
+Create a virtual environment and install dependencies:
+
+```shell
+cd benchmarks/tpc
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+```
+
+## Usage
+
+All benchmarks are run via `run.py`:
+
+```
+python3 run.py --engine <engine> --benchmark <tpch|tpcds> [options]
+```
+
+| Option         | Description                                      |
+| -------------- | ------------------------------------------------ |
+| `--engine`     | Engine name (matches a TOML file in `engines/`)  |
+| `--benchmark`  | `tpch` or `tpcds`                                |
+| `--iterations` | Number of iterations (default: 1)                |
+| `--output`     | Output directory (default: `.`)                  |
+| `--query`      | Run a single query number                        |
+| `--no-restart`        | Skip Spark master/worker restart                     |
+| `--dry-run`           | Print the spark-submit command without executing     |
+| `--profile`           | Enable executor metrics profiling via Spark REST API |
+| `--profile-interval`  | Profiling poll interval in seconds (default: 2.0)    |
+
+Available engines: `spark`, `comet`, `comet-iceberg`, `gluten`
+
+## Example usage
+
+Set Spark environment variables:
+
+```shell
+export SPARK_HOME=/opt/spark-3.5.3-bin-hadoop3/
+export SPARK_MASTER=spark://yourhostname:7077
+```
+
+Set path to data (TPC queries are bundled in `benchmarks/tpc/queries/`):
+
+```shell
+export TPCH_DATA=/mnt/bigdata/tpch/sf100/
+```
+
+Run Spark benchmark:
+
+```shell
+export JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
+sudo ./drop-caches.sh
+python3 run.py --engine spark --benchmark tpch
+```
+
+Run Comet benchmark:
+
+```shell
+export JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
+export COMET_JAR=/opt/comet/comet-spark-spark3.5_2.12-0.10.0.jar
+sudo ./drop-caches.sh
+python3 run.py --engine comet --benchmark tpch
+```
+
+Run Gluten benchmark:
+
+```shell
+export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64
+export GLUTEN_JAR=/opt/gluten/gluten-velox-bundle-spark3.5_2.12-linux_amd64-1.4.0.jar
+sudo ./drop-caches.sh
+python3 run.py --engine gluten --benchmark tpch
+```
+
+Preview a command without running it:
+
+```shell
+python3 run.py --engine comet --benchmark tpch --dry-run
+```
+
+Generating charts:
+
+```shell
+python3 generate-comparison.py --benchmark tpch --labels "Spark 3.5.3" "Comet 0.9.0" "Gluten 1.4.0" --title "TPC-H @ 100 GB (single executor, 8 cores, local Parquet files)" spark-tpch-1752338506381.json comet-tpch-1752337818039.json gluten-tpch-1752337474344.json
+```
+
+## Profiling
+
+Use `--profile` to collect executor memory metrics from the Spark REST API during the benchmark run.
+A background thread polls `/api/v1/applications/{appId}/executors` at a configurable interval and
+writes the time-series data to a CSV file alongside the benchmark results.
+
+```shell
+python3 run.py --engine comet --benchmark tpch --profile
+python3 run.py --engine comet --benchmark tpch --profile --profile-interval 1.0
+```
+
+The output CSV is written to `{output}/{name}-{benchmark}-metrics.csv` and contains per-executor
+columns including `memoryUsed`, `maxMemory`, heap/off-heap storage metrics, and peak memory metrics.
+
+## Engine Configuration
+
+Each engine is defined by a TOML file in `engines/`. The config specifies JARs, Spark conf overrides,
+required environment variables, and optional defaults/exports. See existing files for examples.
+
+## Iceberg Benchmarking
+
+Comet includes native Iceberg support via iceberg-rust integration. This enables benchmarking TPC-H queries
+against Iceberg tables with native scan acceleration.
+
+### Prerequisites
+
+Download the Iceberg Spark runtime JAR (required for running the benchmark):
+
+```shell
+wget https://repo1.maven.org/maven2/org/apache/iceberg/iceberg-spark-runtime-3.5_2.12/1.8.1/iceberg-spark-runtime-3.5_2.12-1.8.1.jar
+export ICEBERG_JAR=/path/to/iceberg-spark-runtime-3.5_2.12-1.8.1.jar
+```
+
+Note: Table creation uses `--packages` which auto-downloads the dependency.
+
+### Create Iceberg tables
+
+Convert existing Parquet data to Iceberg format using `create-iceberg-tables.py`.
+The script configures the Iceberg catalog automatically -- no `--conf` flags needed.
+
+```shell
+export ICEBERG_WAREHOUSE=/mnt/bigdata/iceberg-warehouse
+mkdir -p $ICEBERG_WAREHOUSE
+
+# TPC-H
+$SPARK_HOME/bin/spark-submit \
+    --master $SPARK_MASTER \
+    --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
+    --conf spark.driver.memory=8G \
+    --conf spark.executor.instances=2 \
+    --conf spark.executor.cores=8 \
+    --conf spark.cores.max=16 \
+    --conf spark.executor.memory=16g \
+    create-iceberg-tables.py \
+    --benchmark tpch \
+    --parquet-path $TPCH_DATA \
+    --warehouse $ICEBERG_WAREHOUSE
+
+# TPC-DS
+$SPARK_HOME/bin/spark-submit \
+    --master $SPARK_MASTER \
+    --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
+    --conf spark.driver.memory=8G \
+    --conf spark.executor.instances=2 \
+    --conf spark.executor.cores=8 \
+    --conf spark.cores.max=16 \
+    --conf spark.executor.memory=16g \
+    create-iceberg-tables.py \
+    --benchmark tpcds \
+    --parquet-path $TPCDS_DATA \
+    --warehouse $ICEBERG_WAREHOUSE
+```
+
+### Run Iceberg benchmark
+
+```shell
+export JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
+export COMET_JAR=/opt/comet/comet-spark-spark3.5_2.12-0.10.0.jar
+export ICEBERG_JAR=/path/to/iceberg-spark-runtime-3.5_2.12-1.8.1.jar
+export ICEBERG_WAREHOUSE=/mnt/bigdata/iceberg-warehouse
+sudo ./drop-caches.sh
+python3 run.py --engine comet-iceberg --benchmark tpch
+```
+
+The benchmark uses `spark.comet.scan.icebergNative.enabled=true` to enable Comet's native iceberg-rust
+integration. Verify native scanning is active by checking for `CometIcebergNativeScanExec` in the
+physical plan output.
+
+### create-iceberg-tables.py options
+
+| Option           | Required | Default        | Description                         |
+| ---------------- | -------- | -------------- | ----------------------------------- |
+| `--benchmark`    | Yes      |                | `tpch` or `tpcds`                   |
+| `--parquet-path` | Yes      |                | Path to source Parquet data         |
+| `--warehouse`    | Yes      |                | Path to Iceberg warehouse directory |
+| `--catalog`      | No       | `local`        | Iceberg catalog name                |
+| `--database`     | No       | benchmark name | Database name for the tables        |
+
+## Running with Docker
+
+A Docker Compose setup is provided in `infra/docker/` for running benchmarks in an isolated
+Spark standalone cluster. The Docker image supports both **Linux (amd64)** and **macOS (arm64)**
+via architecture-agnostic Java symlinks created at build time.
+
+### Build the image
+
+The image must be built for the correct platform to match the native libraries in the
+engine JARs (e.g. Comet bundles `libcomet.so` for a specific OS/arch).
+
+**Linux (amd64):**
+
+```shell
+docker build -t comet-bench -f benchmarks/tpc/infra/docker/Dockerfile .
+```
+
+**macOS (Apple Silicon):** Engine JARs contain platform-specific native libraries. A
+Comet JAR built on macOS includes `darwin/aarch64` libraries which won't work inside
+Linux containers. You need a JAR with Linux native libraries.
+
+Build a Comet JAR with Linux native libraries using the provided build Dockerfile:
+
+```shell
+mkdir -p output
+docker build -t comet-builder \
+    -f benchmarks/tpc/infra/docker/Dockerfile.build-comet .
+docker run --rm -v $(pwd)/output:/output comet-builder
+export COMET_JAR=$(pwd)/output/comet-spark-spark3.5_2.12-*.jar
+```
+
+Then build the benchmark image (the architecture is auto-detected):
+
+```shell
+docker build -t comet-bench -f benchmarks/tpc/infra/docker/Dockerfile .
+```
+
+### Platform notes
+
+**macOS (Apple Silicon):** Docker Desktop is required.
+
+- **Memory:** Docker Desktop defaults to a small memory allocation (often 8 GB) which
+  is not enough for Spark benchmarks. Go to **Docker Desktop > Settings > Resources >
+  Memory** and increase it to at least 48 GB (each worker requests 16 GB for its executor
+  plus overhead, and the driver needs 8 GB). Without enough memory, executors will be
+  OOM-killed (exit code 137).
+- **File Sharing:** You may need to add your data directory (e.g. `/opt`) to
+  **Docker Desktop > Settings > Resources > File Sharing** before mounting host volumes.
+
+**Linux (amd64):** No special configuration is needed. Docker uses cgroup memory limits
+directly without a VM layer.
+
+The Docker image auto-detects the container architecture (amd64/arm64) and sets up
+arch-agnostic Java symlinks. The compose file uses `BENCH_JAVA_HOME` (not `JAVA_HOME`)
+to avoid inheriting the host's Java path into the container.
+
+### Start the cluster
+
+Set environment variables pointing to your host paths, then start the Spark master and
+two workers:
+
+```shell
+export DATA_DIR=/mnt/bigdata/tpch/sf100
+export RESULTS_DIR=/tmp/bench-results
+export COMET_JAR=/opt/comet/comet-spark-spark3.5_2.12-0.10.0.jar
+
+docker compose -f benchmarks/tpc/infra/docker/docker-compose.yml up -d
+```
+
+Set `COMET_JAR`, `GLUTEN_JAR`, or `ICEBERG_JAR` to the host path of the engine JAR you
+want to use. Each JAR is mounted individually into the container, so you can easily switch
+between versions by changing the path and restarting.
+
+### Run benchmarks
+
+Use `docker compose run --rm` to execute benchmarks. The `--rm` flag removes the
+container when it exits, preventing port conflicts on subsequent runs. Pass
+`--no-restart` since the cluster is already managed by Compose, and `--output /results`
+so that output files land in the mounted results directory (alongside cgroup metrics
+CSVs):
+
+```shell
+docker compose -f benchmarks/tpc/infra/docker/docker-compose.yml \
+    run --rm -p 4040:4040 bench \
+    sh -c 'mkdir -p /tmp/spark-events && \
+    python3 /opt/benchmarks/run.py \
+    --engine comet --benchmark tpch --output /results --no-restart'
+```
+
+> **Note:** The `mkdir -p /tmp/spark-events` is needed because the common Spark
+> config enables event logging. The bench container is ephemeral so this directory
+> does not persist between runs.
+
+The `-p 4040:4040` flag exposes the Spark Application UI on the host. The following
+UIs are available during a benchmark run:
+
+| UI                   | URL                    |
+| -------------------- | ---------------------- |
+| Spark Master         | http://localhost:8080  |
+| Worker 1             | http://localhost:8081  |
+| Worker 2             | http://localhost:8082  |
+| Spark Application    | http://localhost:4040  |
+
+> **Note:** The Master UI links to the Application UI using the container's internal
+> hostname, which is not reachable from the host. Use `http://localhost:4040` directly
+> to access the Application UI.
+
+For Gluten (requires Java 8), you must restart the **entire cluster** with `JAVA_HOME`
+set so that all services (master, workers, and bench) use Java 8:
+
+```shell
+export BENCH_JAVA_HOME=/usr/lib/jvm/java-8-openjdk
+docker compose -f benchmarks/tpc/infra/docker/docker-compose.yml down
+docker compose -f benchmarks/tpc/infra/docker/docker-compose.yml up -d
+
+docker compose -f benchmarks/tpc/infra/docker/docker-compose.yml \
+    run --rm bench sh -c 'mkdir -p /tmp/spark-events && \
+    python3 /opt/benchmarks/run.py \
+    --engine gluten --benchmark tpch --output /results --no-restart'
+```
+
+> **Important:** Only passing `-e JAVA_HOME=...` to the `bench` container is not
+> sufficient -- the workers also need Java 8 or Gluten will fail at runtime with
+> `sun.misc.Unsafe` errors. Unset `BENCH_JAVA_HOME` (or switch it back to Java 17)
+> and restart the cluster before running Comet or Spark benchmarks.
+
+### Memory limits and metrics
+
+Hard memory limits are enforced on all worker and bench containers. A metrics-collector
+sidecar runs alongside each worker to collect cgroup metrics. Configure via environment
+variables: `WORKER_MEM_LIMIT` (default: 32g per worker), `BENCH_MEM_LIMIT` (default: 10g),
+`METRICS_INTERVAL` (default: 1 second).
+
+Raw cgroup metrics are continuously written to
+`$RESULTS_DIR/container-metrics-spark-worker-{1,2}.csv`. These files are overwritten each
+time the cluster restarts.
+
+When `--profile` is used, the profiler automatically snapshots the cgroup data for the
+benchmark time window, producing per-engine files:
+
+- `{name}-{benchmark}-metrics.csv` -- JVM executor metrics
+- `{name}-{benchmark}-container-metrics-spark-worker-1.csv` -- cgroup snapshot for worker 1
+- `{name}-{benchmark}-container-metrics-spark-worker-2.csv` -- cgroup snapshot for worker 2
+
+This ensures each engine run has its own paired JVM + cgroup dataset even when multiple
+engines are benchmarked on the same cluster.
+
+Use `visualize-metrics.py` to generate memory charts from these files:
+
+```shell
+python3 visualize-metrics.py \
+    --jvm-metrics /tmp/bench-results/comet-tpch-metrics.csv \
+    --cgroup-metrics /tmp/bench-results/comet-tpch-container-metrics-spark-worker-1.csv \
+                     /tmp/bench-results/comet-tpch-container-metrics-spark-worker-2.csv \
+    --output-dir /tmp/comet-charts --title "Comet TPC-H"
+```
+
+### Comparing Parquet vs Iceberg performance
+
+Run both benchmarks and compare:
+
+```shell
+python3 generate-comparison.py --benchmark tpch \
+    --labels "Comet (Parquet)" "Comet (Iceberg)" \
+    --title "TPC-H @ 100 GB: Parquet vs Iceberg" \
+    comet-tpch-*.json comet-iceberg-tpch-*.json
+```
diff --git a/benchmarks/tpc/create-iceberg-tables.py b/benchmarks/tpc/create-iceberg-tables.py
new file mode 100644
index 0000000000..219969bda7
--- /dev/null
+++ b/benchmarks/tpc/create-iceberg-tables.py
@@ -0,0 +1,171 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""
+Convert TPC-H or TPC-DS Parquet data to Iceberg tables.
+
+Usage:
+    spark-submit \
+        --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
+        create-iceberg-tables.py \
+        --benchmark tpch \
+        --parquet-path /path/to/tpch/parquet \
+        --warehouse /path/to/iceberg-warehouse
+
+    spark-submit \
+        --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
+        create-iceberg-tables.py \
+        --benchmark tpcds \
+        --parquet-path /path/to/tpcds/parquet \
+        --warehouse /path/to/iceberg-warehouse
+"""
+
+import argparse
+import os
+import sys
+from pyspark.sql import SparkSession
+import time
+
+TPCH_TABLES = [
+    "customer",
+    "lineitem",
+    "nation",
+    "orders",
+    "part",
+    "partsupp",
+    "region",
+    "supplier",
+]
+
+TPCDS_TABLES = [
+    "call_center",
+    "catalog_page",
+    "catalog_returns",
+    "catalog_sales",
+    "customer",
+    "customer_address",
+    "customer_demographics",
+    "date_dim",
+    "time_dim",
+    "household_demographics",
+    "income_band",
+    "inventory",
+    "item",
+    "promotion",
+    "reason",
+    "ship_mode",
+    "store",
+    "store_returns",
+    "store_sales",
+    "warehouse",
+    "web_page",
+    "web_returns",
+    "web_sales",
+    "web_site",
+]
+
+BENCHMARK_TABLES = {
+    "tpch": TPCH_TABLES,
+    "tpcds": TPCDS_TABLES,
+}
+
+
+def main(benchmark: str, parquet_path: str, warehouse: str, catalog: str, database: str):
+    table_names = BENCHMARK_TABLES[benchmark]
+
+    # Validate paths before starting Spark
+    errors = []
+    if not os.path.isdir(parquet_path):
+        errors.append(f"Error: --parquet-path '{parquet_path}' does not exist or is not a directory")
+    if not os.path.isdir(warehouse):
+        errors.append(f"Error: --warehouse '{warehouse}' does not exist or is not a directory. "
+                       "Create it with: mkdir -p " + warehouse)
+    if errors:
+        for e in errors:
+            print(e, file=sys.stderr)
+        sys.exit(1)
+
+    spark = SparkSession.builder \
+        .appName(f"Create Iceberg {benchmark.upper()} Tables") \
+        .config(f"spark.sql.catalog.{catalog}", "org.apache.iceberg.spark.SparkCatalog") \
+        .config(f"spark.sql.catalog.{catalog}.type", "hadoop") \
+        .config(f"spark.sql.catalog.{catalog}.warehouse", warehouse) \
+        .getOrCreate()
+
+    # Set the Iceberg catalog as the current catalog so that
+    # namespace operations are routed correctly
+    spark.sql(f"USE {catalog}")
+
+    # Create namespace if it doesn't exist
+    try:
+        spark.sql(f"CREATE NAMESPACE IF NOT EXISTS {database}")
+    except Exception:
+        # Namespace may already exist
+        pass
+
+    for table in table_names:
+        parquet_table_path = f"{parquet_path}/{table}.parquet"
+        iceberg_table = f"{catalog}.{database}.{table}"
+
+        print(f"Converting {parquet_table_path} -> {iceberg_table}")
+        start_time = time.time()
+
+        # Drop table if exists to allow re-running
+        spark.sql(f"DROP TABLE IF EXISTS {iceberg_table}")
+
+        # Read parquet and write as Iceberg
+        df = spark.read.parquet(parquet_table_path)
+        df.writeTo(iceberg_table).using("iceberg").create()
+
+        row_count = spark.table(iceberg_table).count()
+        elapsed = time.time() - start_time
+        print(f"  Created {iceberg_table} with {row_count} rows in {elapsed:.2f}s")
+
+    print(f"\nAll {benchmark.upper()} tables created successfully!")
+    print(f"Tables available at: {catalog}.{database}.*")
+
+    spark.stop()
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Convert TPC-H or TPC-DS Parquet data to Iceberg tables"
+    )
+    parser.add_argument(
+        "--benchmark", required=True, choices=["tpch", "tpcds"],
+        help="Benchmark whose tables to convert (tpch or tpcds)"
+    )
+    parser.add_argument(
+        "--parquet-path", required=True,
+        help="Path to Parquet data directory"
+    )
+    parser.add_argument(
+        "--warehouse", required=True,
+        help="Path to Iceberg warehouse directory"
+    )
+    parser.add_argument(
+        "--catalog", default="local",
+        help="Iceberg catalog name (default: 'local')"
+    )
+    parser.add_argument(
+        "--database", default=None,
+        help="Database name to create tables in (defaults to benchmark name)"
+    )
+    args = parser.parse_args()
+
+    database = args.database if args.database else args.benchmark
+    main(args.benchmark, args.parquet_path, args.warehouse, args.catalog, database)
diff --git a/dev/benchmarks/drop-caches.sh b/benchmarks/tpc/drop-caches.sh
similarity index 100%
rename from dev/benchmarks/drop-caches.sh
rename to benchmarks/tpc/drop-caches.sh
diff --git a/benchmarks/tpc/engines/comet-iceberg.toml b/benchmarks/tpc/engines/comet-iceberg.toml
new file mode 100644
index 0000000000..2e01270f13
--- /dev/null
+++ b/benchmarks/tpc/engines/comet-iceberg.toml
@@ -0,0 +1,48 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+[engine]
+name = "comet-iceberg"
+
+[env]
+required = ["COMET_JAR", "ICEBERG_JAR", "ICEBERG_WAREHOUSE"]
+
+[env.defaults]
+ICEBERG_CATALOG = "local"
+
+[spark_submit]
+jars = ["$COMET_JAR", "$ICEBERG_JAR"]
+driver_class_path = ["$COMET_JAR", "$ICEBERG_JAR"]
+
+[spark_conf]
+"spark.driver.extraClassPath" = "$COMET_JAR:$ICEBERG_JAR"
+"spark.executor.extraClassPath" = "$COMET_JAR:$ICEBERG_JAR"
+"spark.plugins" = "org.apache.spark.CometPlugin"
+"spark.shuffle.manager" = "org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager"
+"spark.comet.exec.replaceSortMergeJoin" = "true"
+"spark.comet.expression.Cast.allowIncompatible" = "true"
+"spark.comet.enabled" = "true"
+"spark.comet.exec.enabled" = "true"
+"spark.comet.scan.icebergNative.enabled" = "true"
+"spark.comet.explainFallback.enabled" = "true"
+"spark.sql.catalog.${ICEBERG_CATALOG}" = "org.apache.iceberg.spark.SparkCatalog"
+"spark.sql.catalog.${ICEBERG_CATALOG}.type" = "hadoop"
+"spark.sql.catalog.${ICEBERG_CATALOG}.warehouse" = "$ICEBERG_WAREHOUSE"
+"spark.sql.defaultCatalog" = "${ICEBERG_CATALOG}"
+
+[tpcbench_args]
+use_iceberg = true
diff --git a/benchmarks/tpc/engines/comet.toml b/benchmarks/tpc/engines/comet.toml
new file mode 100644
index 0000000000..8e19165ebf
--- /dev/null
+++ b/benchmarks/tpc/engines/comet.toml
@@ -0,0 +1,35 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+[engine]
+name = "comet"
+
+[env]
+required = ["COMET_JAR"]
+
+[spark_submit]
+jars = ["$COMET_JAR"]
+driver_class_path = ["$COMET_JAR"]
+
+[spark_conf]
+"spark.driver.extraClassPath" = "$COMET_JAR"
+"spark.executor.extraClassPath" = "$COMET_JAR"
+"spark.plugins" = "org.apache.spark.CometPlugin"
+"spark.shuffle.manager" = "org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager"
+"spark.comet.scan.impl" = "native_datafusion"
+"spark.comet.exec.replaceSortMergeJoin" = "true"
+"spark.comet.expression.Cast.allowIncompatible" = "true"
diff --git a/benchmarks/tpc/engines/gluten.toml b/benchmarks/tpc/engines/gluten.toml
new file mode 100644
index 0000000000..20165788c2
--- /dev/null
+++ b/benchmarks/tpc/engines/gluten.toml
@@ -0,0 +1,34 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+[engine]
+name = "gluten"
+
+[env]
+required = ["GLUTEN_JAR"]
+exports = { TZ = "UTC" }
+
+[spark_submit]
+jars = ["$GLUTEN_JAR"]
+
+[spark_conf]
+"spark.plugins" = "org.apache.gluten.GlutenPlugin"
+"spark.driver.extraClassPath" = "${GLUTEN_JAR}"
+"spark.executor.extraClassPath" = "${GLUTEN_JAR}"
+"spark.gluten.sql.columnar.forceShuffledHashJoin" = "true"
+"spark.shuffle.manager" = "org.apache.spark.shuffle.sort.ColumnarShuffleManager"
+"spark.sql.session.timeZone" = "UTC"
diff --git a/benchmarks/tpc/engines/spark.toml b/benchmarks/tpc/engines/spark.toml
new file mode 100644
index 0000000000..c02e7a6ad2
--- /dev/null
+++ b/benchmarks/tpc/engines/spark.toml
@@ -0,0 +1,19 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+[engine]
+name = "spark"
diff --git a/dev/benchmarks/generate-comparison.py b/benchmarks/tpc/generate-comparison.py
similarity index 100%
rename from dev/benchmarks/generate-comparison.py
rename to benchmarks/tpc/generate-comparison.py
diff --git a/benchmarks/tpc/infra/docker/Dockerfile b/benchmarks/tpc/infra/docker/Dockerfile
new file mode 100644
index 0000000000..202ec66de6
--- /dev/null
+++ b/benchmarks/tpc/infra/docker/Dockerfile
@@ -0,0 +1,64 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Benchmark image for running TPC-H and TPC-DS benchmarks across engines
+# (Spark, Comet, Gluten).
+#
+# Build (from repository root):
+#   docker build -t comet-bench -f benchmarks/tpc/infra/docker/Dockerfile .
+
+ARG SPARK_IMAGE=apache/spark:3.5.2-python3
+FROM ${SPARK_IMAGE}
+
+USER root
+
+# Install Java 8 (Gluten) and Java 17 (Comet) plus Python 3.
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends \
+       openjdk-8-jdk-headless \
+       openjdk-17-jdk-headless \
+       python3 python3-pip procps \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+# Default to Java 17 (override with JAVA_HOME at runtime for Gluten).
+# Detect architecture (amd64 or arm64) so the image works on both Linux and macOS.
+ARG TARGETARCH
+RUN ln -s /usr/lib/jvm/java-17-openjdk-${TARGETARCH} /usr/lib/jvm/java-17-openjdk && \
+    ln -s /usr/lib/jvm/java-8-openjdk-${TARGETARCH} /usr/lib/jvm/java-8-openjdk
+ENV JAVA_HOME=/usr/lib/jvm/java-17-openjdk
+
+# Copy the benchmark scripts into the image.
+COPY benchmarks/tpc/run.py              /opt/benchmarks/run.py
+COPY benchmarks/tpc/tpcbench.py         /opt/benchmarks/tpcbench.py
+COPY benchmarks/tpc/profiling.py        /opt/benchmarks/profiling.py
+COPY benchmarks/tpc/engines             /opt/benchmarks/engines
+COPY benchmarks/tpc/queries             /opt/benchmarks/queries
+COPY benchmarks/tpc/create-iceberg-tables.py /opt/benchmarks/create-iceberg-tables.py
+COPY benchmarks/tpc/generate-comparison.py   /opt/benchmarks/generate-comparison.py
+COPY benchmarks/tpc/visualize-metrics.py     /opt/benchmarks/visualize-metrics.py
+
+# Copy the metrics collector script.
+COPY benchmarks/tpc/infra/docker/collect-metrics.sh /opt/benchmarks/collect-metrics.sh
+RUN chmod +x /opt/benchmarks/collect-metrics.sh
+
+# Engine JARs are bind-mounted or copied in at runtime via --jars.
+# Data and query paths are also bind-mounted.
+
+WORKDIR /opt/benchmarks
+
+# Defined in the base apache/spark image.
+ARG spark_uid
+USER ${spark_uid}
diff --git a/benchmarks/tpc/infra/docker/Dockerfile.build-comet b/benchmarks/tpc/infra/docker/Dockerfile.build-comet
new file mode 100644
index 0000000000..7c0c5e4cd2
--- /dev/null
+++ b/benchmarks/tpc/infra/docker/Dockerfile.build-comet
@@ -0,0 +1,76 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Build a Comet JAR with native libraries for the current platform.
+#
+# This is useful on macOS (Apple Silicon) where the host-built JAR contains
+# darwin/aarch64 native libraries but Docker containers need linux/aarch64.
+#
+# Usage (from repository root):
+#   docker build -t comet-builder -f benchmarks/tpc/infra/docker/Dockerfile.build-comet .
+#   docker run --rm -v $(pwd)/output:/output comet-builder
+#
+# The JAR is copied to ./output/ on the host.
+
+# Use Ubuntu 20.04 to match the GLIBC version (2.31) in apache/spark images.
+FROM ubuntu:20.04 AS builder
+
+ARG TARGETARCH
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install build dependencies: Java 17, Maven wrapper prerequisites, GCC 11.
+# Ubuntu 20.04's default GCC 9 has a memcmp bug (GCC #95189) that breaks aws-lc-sys.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        openjdk-17-jdk-headless \
+        curl ca-certificates git pkg-config \
+        libssl-dev unzip software-properties-common \
+    && add-apt-repository -y ppa:ubuntu-toolchain-r/test \
+    && apt-get update \
+    && apt-get install -y --no-install-recommends gcc-11 g++-11 make \
+    && update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 110 \
+    && update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-11 110 \
+    && update-alternatives --install /usr/bin/cc cc /usr/bin/gcc-11 110 \
+    && apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Install protoc 25.x (Ubuntu 22.04's protoc is too old for proto3 optional fields).
+ARG PROTOC_VERSION=25.6
+RUN ARCH=$(uname -m) && \
+    if [ "$ARCH" = "aarch64" ]; then PROTOC_ARCH="linux-aarch_64"; \
+    else PROTOC_ARCH="linux-x86_64"; fi && \
+    curl -sLO "https://github.com/protocolbuffers/protobuf/releases/download/v${PROTOC_VERSION}/protoc-${PROTOC_VERSION}-${PROTOC_ARCH}.zip" && \
+    unzip -o "protoc-${PROTOC_VERSION}-${PROTOC_ARCH}.zip" -d /usr/local bin/protoc && \
+    rm "protoc-${PROTOC_VERSION}-${PROTOC_ARCH}.zip" && \
+    protoc --version
+
+# Set JAVA_HOME and LD_LIBRARY_PATH so the Rust build can find libjvm.
+RUN ln -s /usr/lib/jvm/java-17-openjdk-${TARGETARCH} /usr/lib/jvm/java-17-openjdk
+ENV JAVA_HOME=/usr/lib/jvm/java-17-openjdk
+ENV LD_LIBRARY_PATH=${JAVA_HOME}/lib/server:${LD_LIBRARY_PATH}
+
+# Install Rust.
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
+ENV PATH="/root/.cargo/bin:${PATH}"
+
+WORKDIR /build
+
+# Copy the full source tree.
+COPY . .
+
+# Build native code + package the JAR (skip tests).
+RUN make release-nogit
+
+# The entrypoint copies the built JAR to /output (bind-mounted from host).
+RUN mkdir -p /output
+CMD ["sh", "-c", "cp spark/target/comet-spark-spark3.5_2.12-*-SNAPSHOT.jar /output/ && echo 'Comet JAR copied to /output/' && ls -lh /output/*.jar"]
diff --git a/benchmarks/tpc/infra/docker/collect-metrics.sh b/benchmarks/tpc/infra/docker/collect-metrics.sh
new file mode 100755
index 0000000000..fd9c1d848f
--- /dev/null
+++ b/benchmarks/tpc/infra/docker/collect-metrics.sh
@@ -0,0 +1,103 @@
+#!/bin/sh
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Container-level memory metrics collector.
+#
+# Polls cgroup memory stats at a fixed interval and writes a CSV with
+# columns: timestamp, memory_usage_bytes, memory_limit_bytes, rss_bytes,
+# cache_bytes, swap_bytes.
+#
+# Works with both cgroup v1 and v2.
+#
+# Usage:
+#   collect-metrics.sh [INTERVAL_SECS] [OUTPUT_CSV]
+#
+# Defaults: interval=1, output=/results/container-metrics.csv
+
+set -e
+
+INTERVAL="${1:-1}"
+OUTPUT="${2:-/results/container-metrics.csv}"
+
+# Detect cgroup version
+if [ -f /sys/fs/cgroup/memory/memory.usage_in_bytes ]; then
+    CGROUP_VERSION=1
+elif [ -f /sys/fs/cgroup/memory.current ]; then
+    CGROUP_VERSION=2
+else
+    echo "Warning: cannot detect cgroup memory files; polling disabled" >&2
+    # Still write a header so downstream tools don't break on a missing file.
+    echo "timestamp_ms,memory_usage_bytes,memory_limit_bytes,rss_bytes,cache_bytes,swap_bytes" > "$OUTPUT"
+    # Sleep forever so the container stays up (compose expects it to keep running).
+    exec sleep infinity
+fi
+
+# ---- helpers ----
+
+read_file() {
+    # Return the contents of a file, or "0" if it doesn't exist.
+    if [ -f "$1" ]; then cat "$1"; else echo "0"; fi
+}
+
+read_stat() {
+    # Extract a named field from memory.stat (cgroup v1 format: "key value").
+    grep "^$1 " "$2" 2>/dev/null | awk '{print $2}' || echo "0"
+}
+
+poll_v1() {
+    local usage limit rss cache swap
+    usage=$(read_file /sys/fs/cgroup/memory/memory.usage_in_bytes)
+    limit=$(read_file /sys/fs/cgroup/memory/memory.limit_in_bytes)
+    local stat=/sys/fs/cgroup/memory/memory.stat
+    rss=$(read_stat total_rss "$stat")
+    cache=$(read_stat total_cache "$stat")
+    swap=$(read_file /sys/fs/cgroup/memory/memory.memsw.usage_in_bytes)
+    # swap file reports memory+swap; subtract memory to get swap only
+    if [ "$swap" != "0" ]; then
+        swap=$((swap - usage))
+        [ "$swap" -lt 0 ] && swap=0
+    fi
+    echo "$usage,$limit,$rss,$cache,$swap"
+}
+
+poll_v2() {
+    local usage limit rss cache swap
+    usage=$(read_file /sys/fs/cgroup/memory.current)
+    limit=$(read_file /sys/fs/cgroup/memory.max)
+    [ "$limit" = "max" ] && limit=0
+    local stat=/sys/fs/cgroup/memory.stat
+    rss=$(read_stat anon "$stat")
+    cache=$(read_stat file "$stat")
+    swap=$(read_file /sys/fs/cgroup/memory.swap.current)
+    echo "$usage,$limit,$rss,$cache,$swap"
+}
+
+# ---- main loop ----
+
+echo "timestamp_ms,memory_usage_bytes,memory_limit_bytes,rss_bytes,cache_bytes,swap_bytes" > "$OUTPUT"
+echo "Collecting container memory metrics every ${INTERVAL}s -> ${OUTPUT} (cgroup v${CGROUP_VERSION})" >&2
+
+while true; do
+    ts=$(date +%s%3N 2>/dev/null || python3 -c 'import time; print(int(time.time()*1000))')
+    if [ "$CGROUP_VERSION" = "1" ]; then
+        vals=$(poll_v1)
+    else
+        vals=$(poll_v2)
+    fi
+    echo "${ts},${vals}" >> "$OUTPUT"
+    sleep "$INTERVAL"
+done
diff --git a/benchmarks/tpc/infra/docker/docker-compose.yml b/benchmarks/tpc/infra/docker/docker-compose.yml
new file mode 100644
index 0000000000..a8a8d807c1
--- /dev/null
+++ b/benchmarks/tpc/infra/docker/docker-compose.yml
@@ -0,0 +1,122 @@
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Spark standalone cluster for TPC benchmarks.
+#
+# Two workers are used so that shuffles go through the network stack,
+# which better reflects real cluster behavior.
+#
+# Usage:
+#   export COMET_JAR=/path/to/comet-spark-0.10.0.jar
+#   docker compose -f benchmarks/tpc/infra/docker/docker-compose.yml up -d
+#
+# Environment variables (set in .env or export before running):
+#   BENCH_IMAGE        - Docker image to use (default: comet-bench)
+#   DATA_DIR           - Host path to TPC data (default: /tmp/tpc-data)
+#   RESULTS_DIR        - Host path for results output (default: /tmp/bench-results)
+#   COMET_JAR          - Host path to Comet JAR
+#   GLUTEN_JAR         - Host path to Gluten JAR
+#   ICEBERG_JAR        - Host path to Iceberg Spark runtime JAR
+#   WORKER_MEM_LIMIT   - Hard memory limit per worker container (default: 32g)
+#   BENCH_MEM_LIMIT    - Hard memory limit for the bench runner (default: 10g)
+#   METRICS_INTERVAL   - Metrics collection interval in seconds (default: 1)
+#   BENCH_JAVA_HOME    - Java home inside container (default: /usr/lib/jvm/java-17-openjdk)
+#                        Set to /usr/lib/jvm/java-8-openjdk for Gluten
+
+x-volumes: &volumes
+  - ${DATA_DIR:-/tmp/tpc-data}:/data:ro
+  - ${RESULTS_DIR:-/tmp/bench-results}:/results
+  - ${COMET_JAR:-/dev/null}:/jars/comet.jar:ro
+  - ${GLUTEN_JAR:-/dev/null}:/jars/gluten.jar:ro
+  - ${ICEBERG_JAR:-/dev/null}:/jars/iceberg.jar:ro
+  - ${RESULTS_DIR:-/tmp/bench-results}/logs:/opt/spark/logs
+  - ${RESULTS_DIR:-/tmp/bench-results}/work:/opt/spark/work
+
+x-worker: &worker
+  image: ${BENCH_IMAGE:-comet-bench}
+  depends_on:
+    - spark-master
+  # The metrics collector runs inside the worker container so that it
+  # reads the worker's own cgroup memory stats (a separate sidecar
+  # container would only see its own cgroup, not the worker's).
+  command:
+    - sh
+    - -c
+    - >-
+      /opt/benchmarks/collect-metrics.sh ${METRICS_INTERVAL:-1}
+      /results/container-metrics-$${HOSTNAME}.csv &
+      exec /opt/spark/sbin/start-worker.sh spark://spark-master:7077
+  volumes: *volumes
+  environment:
+    - JAVA_HOME=${BENCH_JAVA_HOME:-/usr/lib/jvm/java-17-openjdk}
+    - SPARK_WORKER_CORES=${WORKER_CORES:-8}
+    - SPARK_WORKER_MEMORY=${WORKER_MEMORY:-16g}
+    - SPARK_NO_DAEMONIZE=true
+  mem_limit: ${WORKER_MEM_LIMIT:-32g}
+  memswap_limit: ${WORKER_MEM_LIMIT:-32g}
+
+services:
+  spark-master:
+    image: ${BENCH_IMAGE:-comet-bench}
+    container_name: spark-master
+    hostname: spark-master
+    command: /opt/spark/sbin/start-master.sh --host spark-master
+    ports:
+      - "7077:7077"
+      - "8080:8080"
+    volumes: *volumes
+    environment:
+      - JAVA_HOME=${BENCH_JAVA_HOME:-/usr/lib/jvm/java-17-openjdk}
+      - SPARK_MASTER_HOST=spark-master
+      - SPARK_NO_DAEMONIZE=true
+
+  spark-worker-1:
+    <<: *worker
+    container_name: spark-worker-1
+    hostname: spark-worker-1
+    ports:
+      - "8081:8081"
+
+  spark-worker-2:
+    <<: *worker
+    container_name: spark-worker-2
+    hostname: spark-worker-2
+    ports:
+      - "8082:8081"
+
+  bench:
+    image: ${BENCH_IMAGE:-comet-bench}
+    container_name: bench-runner
+    depends_on:
+      - spark-master
+      - spark-worker-1
+      - spark-worker-2
+    # Override 'command' to run a specific benchmark, e.g.:
+    #   docker compose run bench python3 /opt/benchmarks/run.py \
+    #       --engine comet --benchmark tpch --no-restart
+    command: ["echo", "Use 'docker compose run bench python3 /opt/benchmarks/run.py ...' to run benchmarks"]
+    volumes: *volumes
+    environment:
+      - JAVA_HOME=${BENCH_JAVA_HOME:-/usr/lib/jvm/java-17-openjdk}
+      - SPARK_HOME=/opt/spark
+      - SPARK_MASTER=spark://spark-master:7077
+      - COMET_JAR=/jars/comet.jar
+      - GLUTEN_JAR=/jars/gluten.jar
+      - ICEBERG_JAR=/jars/iceberg.jar
+      - TPCH_DATA=/data
+      - TPCDS_DATA=/data
+    mem_limit: ${BENCH_MEM_LIMIT:-10g}
+    memswap_limit: ${BENCH_MEM_LIMIT:-10g}
+
diff --git a/benchmarks/tpc/profiling.py b/benchmarks/tpc/profiling.py
new file mode 100644
index 0000000000..23a8a7f34e
--- /dev/null
+++ b/benchmarks/tpc/profiling.py
@@ -0,0 +1,246 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""
+Level 1 profiling hooks: JVM metrics via the Spark REST API.
+
+Polls ``/api/v1/applications/{appId}/executors`` at a configurable interval
+and records executor memory metrics as a time-series CSV alongside the
+benchmark results.
+
+Usage::
+
+    profiler = SparkMetricsProfiler(spark, interval_secs=2)
+    profiler.start()
+    # ... run benchmark ...
+    profiler.stop()
+    profiler.write_csv("/path/to/output/metrics.csv")
+"""
+
+import csv
+import glob
+import os
+import threading
+import time
+from typing import Any, Dict, List, Optional
+
+from pyspark.sql import SparkSession
+
+try:
+    from urllib.request import urlopen
+    import json as _json
+
+    def _fetch_json(url: str) -> Any:
+        with urlopen(url, timeout=5) as resp:
+            return _json.loads(resp.read().decode())
+except ImportError:
+    _fetch_json = None  # type: ignore[assignment]
+
+
+# Metrics we extract per executor from the REST API response
+_EXECUTOR_METRICS = [
+    "memoryUsed",
+    "maxMemory",
+    "totalOnHeapStorageMemory",
+    "usedOnHeapStorageMemory",
+    "totalOffHeapStorageMemory",
+    "usedOffHeapStorageMemory",
+]
+
+# Metrics nested under peakMemoryMetrics (if available)
+_PEAK_MEMORY_METRICS = [
+    "JVMHeapMemory",
+    "JVMOffHeapMemory",
+    "OnHeapExecutionMemory",
+    "OffHeapExecutionMemory",
+    "OnHeapStorageMemory",
+    "OffHeapStorageMemory",
+    "OnHeapUnifiedMemory",
+    "OffHeapUnifiedMemory",
+    "ProcessTreeJVMRSSMemory",
+]
+
+
+class SparkMetricsProfiler:
+    """Periodically polls executor metrics from the Spark REST API."""
+
+    def __init__(
+        self,
+        spark: SparkSession,
+        interval_secs: float = 2.0,
+    ):
+        self._spark = spark
+        self._interval = interval_secs
+        self._samples: List[Dict[str, Any]] = []
+        self._stop_event = threading.Event()
+        self._thread: Optional[threading.Thread] = None
+        self._start_time: float = 0.0
+        self._stop_time: float = 0.0
+
+    @property
+    def samples(self) -> List[Dict[str, Any]]:
+        """Return collected samples (each is a flat dict)."""
+        return list(self._samples)
+
+    def _ui_url(self) -> Optional[str]:
+        """Return the Spark UI base URL, or None if unavailable."""
+        url = self._spark.sparkContext.uiWebUrl
+        if url:
+            return url.rstrip("/")
+        return None
+
+    def _app_id(self) -> str:
+        return self._spark.sparkContext.applicationId
+
+    def _poll_once(self) -> None:
+        """Fetch executor metrics and append a timestamped sample."""
+        base = self._ui_url()
+        if base is None or _fetch_json is None:
+            return
+
+        url = f"{base}/api/v1/applications/{self._app_id()}/executors"
+        try:
+            executors = _fetch_json(url)
+        except Exception:
+            return
+
+        now = time.time()
+        elapsed = now - self._start_time
+        timestamp_ms = int(now * 1000)
+        for exc in executors:
+            row: Dict[str, Any] = {
+                "timestamp_ms": timestamp_ms,
+                "elapsed_secs": round(elapsed, 2),
+                "executor_id": exc.get("id", ""),
+                "is_active": exc.get("isActive", True),
+            }
+            for key in _EXECUTOR_METRICS:
+                row[key] = exc.get(key, 0)
+
+            peak = exc.get("peakMemoryMetrics", {})
+            for key in _PEAK_MEMORY_METRICS:
+                row[f"peak_{key}"] = peak.get(key, 0)
+
+            self._samples.append(row)
+
+    def _run(self) -> None:
+        """Background polling loop."""
+        while not self._stop_event.is_set():
+            self._poll_once()
+            self._stop_event.wait(self._interval)
+
+    def start(self) -> None:
+        """Start background polling thread."""
+        if self._thread is not None:
+            return
+        self._start_time = time.time()
+        self._stop_event.clear()
+        self._thread = threading.Thread(
+            target=self._run, name="spark-metrics-profiler", daemon=True
+        )
+        self._thread.start()
+        print(
+            f"Profiler started (interval={self._interval}s, "
+            f"ui={self._ui_url()})"
+        )
+
+    def stop(self) -> None:
+        """Stop the polling thread and collect a final sample."""
+        if self._thread is None:
+            return
+        self._stop_event.set()
+        self._thread.join(timeout=self._interval + 2)
+        self._thread = None
+        # One last poll to capture final state
+        self._poll_once()
+        self._stop_time = time.time()
+        print(f"Profiler stopped ({len(self._samples)} samples collected)")
+
+    def write_csv(self, path: str) -> str:
+        """Write collected samples to a CSV file.  Returns the path."""
+        if not self._samples:
+            print("Profiler: no samples to write")
+            return path
+
+        fieldnames = list(self._samples[0].keys())
+        with open(path, "w", newline="") as f:
+            writer = csv.DictWriter(f, fieldnames=fieldnames)
+            writer.writeheader()
+            for row in self._samples:
+                writer.writerow(row)
+        print(f"Profiler: wrote {len(self._samples)} samples to {path}")
+        return path
+
+    def snapshot_cgroup_metrics(
+        self, output_dir: str, name: str, benchmark: str
+    ) -> List[str]:
+        """Filter cgroup CSVs to the profiling time window and write snapshots.
+
+        Looks for ``container-metrics-*.csv`` in *output_dir*, keeps only
+        rows whose ``timestamp_ms`` falls within the profiler's start/stop
+        window, and writes each filtered file as
+        ``{name}-{benchmark}-container-metrics-{label}.csv``.
+
+        Returns the list of snapshot file paths written.
+        """
+        start_ms = int(self._start_time * 1000)
+        stop_ms = int(self._stop_time * 1000) if self._stop_time else int(
+            time.time() * 1000
+        )
+
+        source_files = sorted(
+            glob.glob(os.path.join(output_dir, "container-metrics-*.csv"))
+        )
+        if not source_files:
+            print("Profiler: no container-metrics CSVs found to snapshot")
+            return []
+
+        written: List[str] = []
+        for src in source_files:
+            # Extract label, e.g. "spark-worker-1" from
+            # "container-metrics-spark-worker-1.csv"
+            basename = os.path.basename(src)
+            label = basename.replace("container-metrics-", "").replace(
+                ".csv", ""
+            )
+            dest = os.path.join(
+                output_dir,
+                f"{name}-{benchmark}-container-metrics-{label}.csv",
+            )
+
+            with open(src, "r", newline="") as fin:
+                reader = csv.DictReader(fin)
+                fieldnames = reader.fieldnames
+                if not fieldnames:
+                    continue
+                rows = [
+                    row
+                    for row in reader
+                    if start_ms <= int(row["timestamp_ms"]) <= stop_ms
+                ]
+
+            with open(dest, "w", newline="") as fout:
+                writer = csv.DictWriter(fout, fieldnames=fieldnames)
+                writer.writeheader()
+                writer.writerows(rows)
+
+            print(
+                f"Profiler: snapshot {len(rows)} cgroup rows -> {dest}"
+            )
+            written.append(dest)
+
+        return written
diff --git a/benchmarks/tpc/queries/tpcds/q1.sql b/benchmarks/tpc/queries/tpcds/q1.sql
new file mode 100644
index 0000000000..31bd9eb045
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q1.sql
@@ -0,0 +1,26 @@
+-- CometBench-DS query 1 derived from TPC-DS query 1 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with customer_total_return as
+(select sr_customer_sk as ctr_customer_sk
+,sr_store_sk as ctr_store_sk
+,sum(SR_RETURN_AMT_INC_TAX) as ctr_total_return
+from store_returns
+,date_dim
+where sr_returned_date_sk = d_date_sk
+and d_year =1999
+group by sr_customer_sk
+,sr_store_sk)
+ select  c_customer_id
+from customer_total_return ctr1
+,store
+,customer
+where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
+from customer_total_return ctr2
+where ctr1.ctr_store_sk = ctr2.ctr_store_sk)
+and s_store_sk = ctr1.ctr_store_sk
+and s_state = 'TN'
+and ctr1.ctr_customer_sk = c_customer_sk
+order by c_customer_id
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q10.sql b/benchmarks/tpc/queries/tpcds/q10.sql
new file mode 100644
index 0000000000..9ddfefb25d
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q10.sql
@@ -0,0 +1,60 @@
+-- CometBench-DS query 10 derived from TPC-DS query 10 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+  cd_gender,
+  cd_marital_status,
+  cd_education_status,
+  count(*) cnt1,
+  cd_purchase_estimate,
+  count(*) cnt2,
+  cd_credit_rating,
+  count(*) cnt3,
+  cd_dep_count,
+  count(*) cnt4,
+  cd_dep_employed_count,
+  count(*) cnt5,
+  cd_dep_college_count,
+  count(*) cnt6
+ from
+  customer c,customer_address ca,customer_demographics
+ where
+  c.c_current_addr_sk = ca.ca_address_sk and
+  ca_county in ('Clinton County','Platte County','Franklin County','Louisa County','Harmon County') and
+  cd_demo_sk = c.c_current_cdemo_sk and 
+  exists (select *
+          from store_sales,date_dim
+          where c.c_customer_sk = ss_customer_sk and
+                ss_sold_date_sk = d_date_sk and
+                d_year = 2002 and
+                d_moy between 3 and 3+3) and
+   (exists (select *
+            from web_sales,date_dim
+            where c.c_customer_sk = ws_bill_customer_sk and
+                  ws_sold_date_sk = d_date_sk and
+                  d_year = 2002 and
+                  d_moy between 3 ANd 3+3) or 
+    exists (select * 
+            from catalog_sales,date_dim
+            where c.c_customer_sk = cs_ship_customer_sk and
+                  cs_sold_date_sk = d_date_sk and
+                  d_year = 2002 and
+                  d_moy between 3 and 3+3))
+ group by cd_gender,
+          cd_marital_status,
+          cd_education_status,
+          cd_purchase_estimate,
+          cd_credit_rating,
+          cd_dep_count,
+          cd_dep_employed_count,
+          cd_dep_college_count
+ order by cd_gender,
+          cd_marital_status,
+          cd_education_status,
+          cd_purchase_estimate,
+          cd_credit_rating,
+          cd_dep_count,
+          cd_dep_employed_count,
+          cd_dep_college_count
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q11.sql b/benchmarks/tpc/queries/tpcds/q11.sql
new file mode 100644
index 0000000000..abc1e14ae4
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q11.sql
@@ -0,0 +1,82 @@
+-- CometBench-DS query 11 derived from TPC-DS query 11 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with year_total as (
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,c_preferred_cust_flag customer_preferred_cust_flag
+       ,c_birth_country customer_birth_country
+       ,c_login customer_login
+       ,c_email_address customer_email_address
+       ,d_year dyear
+       ,sum(ss_ext_list_price-ss_ext_discount_amt) year_total
+       ,'s' sale_type
+ from customer
+     ,store_sales
+     ,date_dim
+ where c_customer_sk = ss_customer_sk
+   and ss_sold_date_sk = d_date_sk
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,c_preferred_cust_flag 
+         ,c_birth_country
+         ,c_login
+         ,c_email_address
+         ,d_year 
+ union all
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,c_preferred_cust_flag customer_preferred_cust_flag
+       ,c_birth_country customer_birth_country
+       ,c_login customer_login
+       ,c_email_address customer_email_address
+       ,d_year dyear
+       ,sum(ws_ext_list_price-ws_ext_discount_amt) year_total
+       ,'w' sale_type
+ from customer
+     ,web_sales
+     ,date_dim
+ where c_customer_sk = ws_bill_customer_sk
+   and ws_sold_date_sk = d_date_sk
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,c_preferred_cust_flag 
+         ,c_birth_country
+         ,c_login
+         ,c_email_address
+         ,d_year
+         )
+  select  
+                  t_s_secyear.customer_id
+                 ,t_s_secyear.customer_first_name
+                 ,t_s_secyear.customer_last_name
+                 ,t_s_secyear.customer_email_address
+ from year_total t_s_firstyear
+     ,year_total t_s_secyear
+     ,year_total t_w_firstyear
+     ,year_total t_w_secyear
+ where t_s_secyear.customer_id = t_s_firstyear.customer_id
+         and t_s_firstyear.customer_id = t_w_secyear.customer_id
+         and t_s_firstyear.customer_id = t_w_firstyear.customer_id
+         and t_s_firstyear.sale_type = 's'
+         and t_w_firstyear.sale_type = 'w'
+         and t_s_secyear.sale_type = 's'
+         and t_w_secyear.sale_type = 'w'
+         and t_s_firstyear.dyear = 1999
+         and t_s_secyear.dyear = 1999+1
+         and t_w_firstyear.dyear = 1999
+         and t_w_secyear.dyear = 1999+1
+         and t_s_firstyear.year_total > 0
+         and t_w_firstyear.year_total > 0
+         and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else 0.0 end
+             > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else 0.0 end
+ order by t_s_secyear.customer_id
+         ,t_s_secyear.customer_first_name
+         ,t_s_secyear.customer_last_name
+         ,t_s_secyear.customer_email_address
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q12.sql b/benchmarks/tpc/queries/tpcds/q12.sql
new file mode 100644
index 0000000000..e44b5de0b6
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q12.sql
@@ -0,0 +1,35 @@
+-- CometBench-DS query 12 derived from TPC-DS query 12 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id
+      ,i_item_desc 
+      ,i_category 
+      ,i_class 
+      ,i_current_price
+      ,sum(ws_ext_sales_price) as itemrevenue 
+      ,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
+          (partition by i_class) as revenueratio
+from	
+	web_sales
+    	,item 
+    	,date_dim
+where 
+	ws_item_sk = i_item_sk 
+  	and i_category in ('Jewelry', 'Books', 'Women')
+  	and ws_sold_date_sk = d_date_sk
+	and d_date between cast('2002-03-22' as date) 
+				and (cast('2002-03-22' as date) + 30 days)
+group by 
+	i_item_id
+        ,i_item_desc 
+        ,i_category
+        ,i_class
+        ,i_current_price
+order by 
+	i_category
+        ,i_class
+        ,i_item_id
+        ,i_item_desc
+        ,revenueratio
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q13.sql b/benchmarks/tpc/queries/tpcds/q13.sql
new file mode 100644
index 0000000000..9cf55cc15d
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q13.sql
@@ -0,0 +1,53 @@
+-- CometBench-DS query 13 derived from TPC-DS query 13 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select avg(ss_quantity)
+       ,avg(ss_ext_sales_price)
+       ,avg(ss_ext_wholesale_cost)
+       ,sum(ss_ext_wholesale_cost)
+ from store_sales
+     ,store
+     ,customer_demographics
+     ,household_demographics
+     ,customer_address
+     ,date_dim
+ where s_store_sk = ss_store_sk
+ and  ss_sold_date_sk = d_date_sk and d_year = 2001
+ and((ss_hdemo_sk=hd_demo_sk
+  and cd_demo_sk = ss_cdemo_sk
+  and cd_marital_status = 'U'
+  and cd_education_status = '4 yr Degree'
+  and ss_sales_price between 100.00 and 150.00
+  and hd_dep_count = 3   
+     )or
+     (ss_hdemo_sk=hd_demo_sk
+  and cd_demo_sk = ss_cdemo_sk
+  and cd_marital_status = 'S'
+  and cd_education_status = 'Unknown'
+  and ss_sales_price between 50.00 and 100.00   
+  and hd_dep_count = 1
+     ) or 
+     (ss_hdemo_sk=hd_demo_sk
+  and cd_demo_sk = ss_cdemo_sk
+  and cd_marital_status = 'D'
+  and cd_education_status = '2 yr Degree'
+  and ss_sales_price between 150.00 and 200.00 
+  and hd_dep_count = 1  
+     ))
+ and((ss_addr_sk = ca_address_sk
+  and ca_country = 'United States'
+  and ca_state in ('CO', 'MI', 'MN')
+  and ss_net_profit between 100 and 200  
+     ) or
+     (ss_addr_sk = ca_address_sk
+  and ca_country = 'United States'
+  and ca_state in ('NC', 'NY', 'TX')
+  and ss_net_profit between 150 and 300  
+     ) or
+     (ss_addr_sk = ca_address_sk
+  and ca_country = 'United States'
+  and ca_state in ('CA', 'NE', 'TN')
+  and ss_net_profit between 50 and 250  
+     ))
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q14.sql b/benchmarks/tpc/queries/tpcds/q14.sql
new file mode 100644
index 0000000000..f242c1eaa6
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q14.sql
@@ -0,0 +1,211 @@
+-- CometBench-DS query 14 derived from TPC-DS query 14 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with  cross_items as
+ (select i_item_sk ss_item_sk
+ from item,
+ (select iss.i_brand_id brand_id
+     ,iss.i_class_id class_id
+     ,iss.i_category_id category_id
+ from store_sales
+     ,item iss
+     ,date_dim d1
+ where ss_item_sk = iss.i_item_sk
+   and ss_sold_date_sk = d1.d_date_sk
+   and d1.d_year between 1999 AND 1999 + 2
+ intersect 
+ select ics.i_brand_id
+     ,ics.i_class_id
+     ,ics.i_category_id
+ from catalog_sales
+     ,item ics
+     ,date_dim d2
+ where cs_item_sk = ics.i_item_sk
+   and cs_sold_date_sk = d2.d_date_sk
+   and d2.d_year between 1999 AND 1999 + 2
+ intersect
+ select iws.i_brand_id
+     ,iws.i_class_id
+     ,iws.i_category_id
+ from web_sales
+     ,item iws
+     ,date_dim d3
+ where ws_item_sk = iws.i_item_sk
+   and ws_sold_date_sk = d3.d_date_sk
+   and d3.d_year between 1999 AND 1999 + 2)
+ where i_brand_id = brand_id
+      and i_class_id = class_id
+      and i_category_id = category_id
+),
+ avg_sales as
+ (select avg(quantity*list_price) average_sales
+  from (select ss_quantity quantity
+             ,ss_list_price list_price
+       from store_sales
+           ,date_dim
+       where ss_sold_date_sk = d_date_sk
+         and d_year between 1999 and 1999 + 2
+       union all 
+       select cs_quantity quantity 
+             ,cs_list_price list_price
+       from catalog_sales
+           ,date_dim
+       where cs_sold_date_sk = d_date_sk
+         and d_year between 1999 and 1999 + 2 
+       union all
+       select ws_quantity quantity
+             ,ws_list_price list_price
+       from web_sales
+           ,date_dim
+       where ws_sold_date_sk = d_date_sk
+         and d_year between 1999 and 1999 + 2) x)
+  select  channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales)
+ from(
+       select 'store' channel, i_brand_id,i_class_id
+             ,i_category_id,sum(ss_quantity*ss_list_price) sales
+             , count(*) number_sales
+       from store_sales
+           ,item
+           ,date_dim
+       where ss_item_sk in (select ss_item_sk from cross_items)
+         and ss_item_sk = i_item_sk
+         and ss_sold_date_sk = d_date_sk
+         and d_year = 1999+2 
+         and d_moy = 11
+       group by i_brand_id,i_class_id,i_category_id
+       having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)
+       union all
+       select 'catalog' channel, i_brand_id,i_class_id,i_category_id, sum(cs_quantity*cs_list_price) sales, count(*) number_sales
+       from catalog_sales
+           ,item
+           ,date_dim
+       where cs_item_sk in (select ss_item_sk from cross_items)
+         and cs_item_sk = i_item_sk
+         and cs_sold_date_sk = d_date_sk
+         and d_year = 1999+2 
+         and d_moy = 11
+       group by i_brand_id,i_class_id,i_category_id
+       having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales)
+       union all
+       select 'web' channel, i_brand_id,i_class_id,i_category_id, sum(ws_quantity*ws_list_price) sales , count(*) number_sales
+       from web_sales
+           ,item
+           ,date_dim
+       where ws_item_sk in (select ss_item_sk from cross_items)
+         and ws_item_sk = i_item_sk
+         and ws_sold_date_sk = d_date_sk
+         and d_year = 1999+2
+         and d_moy = 11
+       group by i_brand_id,i_class_id,i_category_id
+       having sum(ws_quantity*ws_list_price) > (select average_sales from avg_sales)
+ ) y
+ group by rollup (channel, i_brand_id,i_class_id,i_category_id)
+ order by channel,i_brand_id,i_class_id,i_category_id
+  LIMIT 100;
+with  cross_items as
+ (select i_item_sk ss_item_sk
+ from item,
+ (select iss.i_brand_id brand_id
+     ,iss.i_class_id class_id
+     ,iss.i_category_id category_id
+ from store_sales
+     ,item iss
+     ,date_dim d1
+ where ss_item_sk = iss.i_item_sk
+   and ss_sold_date_sk = d1.d_date_sk
+   and d1.d_year between 1999 AND 1999 + 2
+ intersect
+ select ics.i_brand_id
+     ,ics.i_class_id
+     ,ics.i_category_id
+ from catalog_sales
+     ,item ics
+     ,date_dim d2
+ where cs_item_sk = ics.i_item_sk
+   and cs_sold_date_sk = d2.d_date_sk
+   and d2.d_year between 1999 AND 1999 + 2
+ intersect
+ select iws.i_brand_id
+     ,iws.i_class_id
+     ,iws.i_category_id
+ from web_sales
+     ,item iws
+     ,date_dim d3
+ where ws_item_sk = iws.i_item_sk
+   and ws_sold_date_sk = d3.d_date_sk
+   and d3.d_year between 1999 AND 1999 + 2) x
+ where i_brand_id = brand_id
+      and i_class_id = class_id
+      and i_category_id = category_id
+),
+ avg_sales as
+(select avg(quantity*list_price) average_sales
+  from (select ss_quantity quantity
+             ,ss_list_price list_price
+       from store_sales
+           ,date_dim
+       where ss_sold_date_sk = d_date_sk
+         and d_year between 1999 and 1999 + 2
+       union all
+       select cs_quantity quantity
+             ,cs_list_price list_price
+       from catalog_sales
+           ,date_dim
+       where cs_sold_date_sk = d_date_sk
+         and d_year between 1999 and 1999 + 2
+       union all
+       select ws_quantity quantity
+             ,ws_list_price list_price
+       from web_sales
+           ,date_dim
+       where ws_sold_date_sk = d_date_sk
+         and d_year between 1999 and 1999 + 2) x)
+  select  this_year.channel ty_channel
+                           ,this_year.i_brand_id ty_brand
+                           ,this_year.i_class_id ty_class
+                           ,this_year.i_category_id ty_category
+                           ,this_year.sales ty_sales
+                           ,this_year.number_sales ty_number_sales
+                           ,last_year.channel ly_channel
+                           ,last_year.i_brand_id ly_brand
+                           ,last_year.i_class_id ly_class
+                           ,last_year.i_category_id ly_category
+                           ,last_year.sales ly_sales
+                           ,last_year.number_sales ly_number_sales 
+ from
+ (select 'store' channel, i_brand_id,i_class_id,i_category_id
+        ,sum(ss_quantity*ss_list_price) sales, count(*) number_sales
+ from store_sales 
+     ,item
+     ,date_dim
+ where ss_item_sk in (select ss_item_sk from cross_items)
+   and ss_item_sk = i_item_sk
+   and ss_sold_date_sk = d_date_sk
+   and d_week_seq = (select d_week_seq
+                     from date_dim
+                     where d_year = 1999 + 1
+                       and d_moy = 12
+                       and d_dom = 14)
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)) this_year,
+ (select 'store' channel, i_brand_id,i_class_id
+        ,i_category_id, sum(ss_quantity*ss_list_price) sales, count(*) number_sales
+ from store_sales
+     ,item
+     ,date_dim
+ where ss_item_sk in (select ss_item_sk from cross_items)
+   and ss_item_sk = i_item_sk
+   and ss_sold_date_sk = d_date_sk
+   and d_week_seq = (select d_week_seq
+                     from date_dim
+                     where d_year = 1999
+                       and d_moy = 12
+                       and d_dom = 14)
+ group by i_brand_id,i_class_id,i_category_id
+ having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)) last_year
+ where this_year.i_brand_id= last_year.i_brand_id
+   and this_year.i_class_id = last_year.i_class_id
+   and this_year.i_category_id = last_year.i_category_id
+ order by this_year.channel, this_year.i_brand_id, this_year.i_class_id, this_year.i_category_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q15.sql b/benchmarks/tpc/queries/tpcds/q15.sql
new file mode 100644
index 0000000000..37f0d2791f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q15.sql
@@ -0,0 +1,21 @@
+-- CometBench-DS query 15 derived from TPC-DS query 15 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  ca_zip
+       ,sum(cs_sales_price)
+ from catalog_sales
+     ,customer
+     ,customer_address
+     ,date_dim
+ where cs_bill_customer_sk = c_customer_sk
+ 	and c_current_addr_sk = ca_address_sk 
+ 	and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475',
+                                   '85392', '85460', '80348', '81792')
+ 	      or ca_state in ('CA','WA','GA')
+ 	      or cs_sales_price > 500)
+ 	and cs_sold_date_sk = d_date_sk
+ 	and d_qoy = 2 and d_year = 2002
+ group by ca_zip
+ order by ca_zip
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q16.sql b/benchmarks/tpc/queries/tpcds/q16.sql
new file mode 100644
index 0000000000..2f5db58ff3
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q16.sql
@@ -0,0 +1,32 @@
+-- CometBench-DS query 16 derived from TPC-DS query 16 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   count(distinct cs_order_number) as "order count"
+  ,sum(cs_ext_ship_cost) as "total shipping cost"
+  ,sum(cs_net_profit) as "total net profit"
+from
+   catalog_sales cs1
+  ,date_dim
+  ,customer_address
+  ,call_center
+where
+    d_date between '1999-5-01' and 
+           (cast('1999-5-01' as date) + 60 days)
+and cs1.cs_ship_date_sk = d_date_sk
+and cs1.cs_ship_addr_sk = ca_address_sk
+and ca_state = 'ID'
+and cs1.cs_call_center_sk = cc_call_center_sk
+and cc_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
+                  'Williamson County'
+)
+and exists (select *
+            from catalog_sales cs2
+            where cs1.cs_order_number = cs2.cs_order_number
+              and cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk)
+and not exists(select *
+               from catalog_returns cr1
+               where cs1.cs_order_number = cr1.cr_order_number)
+order by count(distinct cs_order_number)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q17.sql b/benchmarks/tpc/queries/tpcds/q17.sql
new file mode 100644
index 0000000000..37602e2a8a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q17.sql
@@ -0,0 +1,46 @@
+-- CometBench-DS query 17 derived from TPC-DS query 17 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id
+       ,i_item_desc
+       ,s_state
+       ,count(ss_quantity) as store_sales_quantitycount
+       ,avg(ss_quantity) as store_sales_quantityave
+       ,stddev_samp(ss_quantity) as store_sales_quantitystdev
+       ,stddev_samp(ss_quantity)/avg(ss_quantity) as store_sales_quantitycov
+       ,count(sr_return_quantity) as store_returns_quantitycount
+       ,avg(sr_return_quantity) as store_returns_quantityave
+       ,stddev_samp(sr_return_quantity) as store_returns_quantitystdev
+       ,stddev_samp(sr_return_quantity)/avg(sr_return_quantity) as store_returns_quantitycov
+       ,count(cs_quantity) as catalog_sales_quantitycount ,avg(cs_quantity) as catalog_sales_quantityave
+       ,stddev_samp(cs_quantity) as catalog_sales_quantitystdev
+       ,stddev_samp(cs_quantity)/avg(cs_quantity) as catalog_sales_quantitycov
+ from store_sales
+     ,store_returns
+     ,catalog_sales
+     ,date_dim d1
+     ,date_dim d2
+     ,date_dim d3
+     ,store
+     ,item
+ where d1.d_quarter_name = '1999Q1'
+   and d1.d_date_sk = ss_sold_date_sk
+   and i_item_sk = ss_item_sk
+   and s_store_sk = ss_store_sk
+   and ss_customer_sk = sr_customer_sk
+   and ss_item_sk = sr_item_sk
+   and ss_ticket_number = sr_ticket_number
+   and sr_returned_date_sk = d2.d_date_sk
+   and d2.d_quarter_name in ('1999Q1','1999Q2','1999Q3')
+   and sr_customer_sk = cs_bill_customer_sk
+   and sr_item_sk = cs_item_sk
+   and cs_sold_date_sk = d3.d_date_sk
+   and d3.d_quarter_name in ('1999Q1','1999Q2','1999Q3')
+ group by i_item_id
+         ,i_item_desc
+         ,s_state
+ order by i_item_id
+         ,i_item_desc
+         ,s_state
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q18.sql b/benchmarks/tpc/queries/tpcds/q18.sql
new file mode 100644
index 0000000000..fa89d2db86
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q18.sql
@@ -0,0 +1,35 @@
+-- CometBench-DS query 18 derived from TPC-DS query 18 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id,
+        ca_country,
+        ca_state, 
+        ca_county,
+        avg( cast(cs_quantity as decimal(12,2))) agg1,
+        avg( cast(cs_list_price as decimal(12,2))) agg2,
+        avg( cast(cs_coupon_amt as decimal(12,2))) agg3,
+        avg( cast(cs_sales_price as decimal(12,2))) agg4,
+        avg( cast(cs_net_profit as decimal(12,2))) agg5,
+        avg( cast(c_birth_year as decimal(12,2))) agg6,
+        avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7
+ from catalog_sales, customer_demographics cd1, 
+      customer_demographics cd2, customer, customer_address, date_dim, item
+ where cs_sold_date_sk = d_date_sk and
+       cs_item_sk = i_item_sk and
+       cs_bill_cdemo_sk = cd1.cd_demo_sk and
+       cs_bill_customer_sk = c_customer_sk and
+       cd1.cd_gender = 'M' and 
+       cd1.cd_education_status = 'Primary' and
+       c_current_cdemo_sk = cd2.cd_demo_sk and
+       c_current_addr_sk = ca_address_sk and
+       c_birth_month in (1,2,9,5,11,3) and
+       d_year = 1998 and
+       ca_state in ('MS','NE','IA'
+                   ,'MI','GA','NY','CO')
+ group by rollup (i_item_id, ca_country, ca_state, ca_county)
+ order by ca_country,
+        ca_state, 
+        ca_county,
+	i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q19.sql b/benchmarks/tpc/queries/tpcds/q19.sql
new file mode 100644
index 0000000000..54cc69519f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q19.sql
@@ -0,0 +1,26 @@
+-- CometBench-DS query 19 derived from TPC-DS query 19 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact,
+ 	sum(ss_ext_sales_price) ext_price
+ from date_dim, store_sales, item,customer,customer_address,store
+ where d_date_sk = ss_sold_date_sk
+   and ss_item_sk = i_item_sk
+   and i_manager_id=8
+   and d_moy=11
+   and d_year=1999
+   and ss_customer_sk = c_customer_sk 
+   and c_current_addr_sk = ca_address_sk
+   and substr(ca_zip,1,5) <> substr(s_zip,1,5) 
+   and ss_store_sk = s_store_sk 
+ group by i_brand
+      ,i_brand_id
+      ,i_manufact_id
+      ,i_manufact
+ order by ext_price desc
+         ,i_brand
+         ,i_brand_id
+         ,i_manufact_id
+         ,i_manufact
+ LIMIT 100 ;
+
diff --git a/benchmarks/tpc/queries/tpcds/q2.sql b/benchmarks/tpc/queries/tpcds/q2.sql
new file mode 100644
index 0000000000..77b0dccf8c
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q2.sql
@@ -0,0 +1,61 @@
+-- CometBench-DS query 2 derived from TPC-DS query 2 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with wscs as
+ (select sold_date_sk
+        ,sales_price
+  from (select ws_sold_date_sk sold_date_sk
+              ,ws_ext_sales_price sales_price
+        from web_sales 
+        union all
+        select cs_sold_date_sk sold_date_sk
+              ,cs_ext_sales_price sales_price
+        from catalog_sales)),
+ wswscs as 
+ (select d_week_seq,
+        sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales,
+        sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales,
+        sum(case when (d_day_name='Tuesday') then sales_price else  null end) tue_sales,
+        sum(case when (d_day_name='Wednesday') then sales_price else null end) wed_sales,
+        sum(case when (d_day_name='Thursday') then sales_price else null end) thu_sales,
+        sum(case when (d_day_name='Friday') then sales_price else null end) fri_sales,
+        sum(case when (d_day_name='Saturday') then sales_price else null end) sat_sales
+ from wscs
+     ,date_dim
+ where d_date_sk = sold_date_sk
+ group by d_week_seq)
+ select d_week_seq1
+       ,round(sun_sales1/sun_sales2,2)
+       ,round(mon_sales1/mon_sales2,2)
+       ,round(tue_sales1/tue_sales2,2)
+       ,round(wed_sales1/wed_sales2,2)
+       ,round(thu_sales1/thu_sales2,2)
+       ,round(fri_sales1/fri_sales2,2)
+       ,round(sat_sales1/sat_sales2,2)
+ from
+ (select wswscs.d_week_seq d_week_seq1
+        ,sun_sales sun_sales1
+        ,mon_sales mon_sales1
+        ,tue_sales tue_sales1
+        ,wed_sales wed_sales1
+        ,thu_sales thu_sales1
+        ,fri_sales fri_sales1
+        ,sat_sales sat_sales1
+  from wswscs,date_dim 
+  where date_dim.d_week_seq = wswscs.d_week_seq and
+        d_year = 2000) y,
+ (select wswscs.d_week_seq d_week_seq2
+        ,sun_sales sun_sales2
+        ,mon_sales mon_sales2
+        ,tue_sales tue_sales2
+        ,wed_sales wed_sales2
+        ,thu_sales thu_sales2
+        ,fri_sales fri_sales2
+        ,sat_sales sat_sales2
+  from wswscs
+      ,date_dim 
+  where date_dim.d_week_seq = wswscs.d_week_seq and
+        d_year = 2000+1) z
+ where d_week_seq1=d_week_seq2-53
+ order by d_week_seq1;
+
diff --git a/benchmarks/tpc/queries/tpcds/q20.sql b/benchmarks/tpc/queries/tpcds/q20.sql
new file mode 100644
index 0000000000..12e61a06fa
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q20.sql
@@ -0,0 +1,31 @@
+-- CometBench-DS query 20 derived from TPC-DS query 20 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id
+       ,i_item_desc 
+       ,i_category 
+       ,i_class 
+       ,i_current_price
+       ,sum(cs_ext_sales_price) as itemrevenue 
+       ,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over
+           (partition by i_class) as revenueratio
+ from	catalog_sales
+     ,item 
+     ,date_dim
+ where cs_item_sk = i_item_sk 
+   and i_category in ('Children', 'Sports', 'Music')
+   and cs_sold_date_sk = d_date_sk
+ and d_date between cast('2002-04-01' as date) 
+ 				and (cast('2002-04-01' as date) + 30 days)
+ group by i_item_id
+         ,i_item_desc 
+         ,i_category
+         ,i_class
+         ,i_current_price
+ order by i_category
+         ,i_class
+         ,i_item_id
+         ,i_item_desc
+         ,revenueratio
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q21.sql b/benchmarks/tpc/queries/tpcds/q21.sql
new file mode 100644
index 0000000000..b7c2a5eb2f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q21.sql
@@ -0,0 +1,31 @@
+-- CometBench-DS query 21 derived from TPC-DS query 21 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  *
+ from(select w_warehouse_name
+            ,i_item_id
+            ,sum(case when (cast(d_date as date) < cast ('2000-05-19' as date))
+	                then inv_quantity_on_hand 
+                      else 0 end) as inv_before
+            ,sum(case when (cast(d_date as date) >= cast ('2000-05-19' as date))
+                      then inv_quantity_on_hand 
+                      else 0 end) as inv_after
+   from inventory
+       ,warehouse
+       ,item
+       ,date_dim
+   where i_current_price between 0.99 and 1.49
+     and i_item_sk          = inv_item_sk
+     and inv_warehouse_sk   = w_warehouse_sk
+     and inv_date_sk    = d_date_sk
+     and d_date between (cast ('2000-05-19' as date) - 30 days)
+                    and (cast ('2000-05-19' as date) + 30 days)
+   group by w_warehouse_name, i_item_id) x
+ where (case when inv_before > 0 
+             then inv_after / inv_before 
+             else null
+             end) between 2.0/3.0 and 3.0/2.0
+ order by w_warehouse_name
+         ,i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q22.sql b/benchmarks/tpc/queries/tpcds/q22.sql
new file mode 100644
index 0000000000..416c4879c5
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q22.sql
@@ -0,0 +1,21 @@
+-- CometBench-DS query 22 derived from TPC-DS query 22 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_product_name
+             ,i_brand
+             ,i_class
+             ,i_category
+             ,avg(inv_quantity_on_hand) qoh
+       from inventory
+           ,date_dim
+           ,item
+       where inv_date_sk=d_date_sk
+              and inv_item_sk=i_item_sk
+              and d_month_seq between 1201 and 1201 + 11
+       group by rollup(i_product_name
+                       ,i_brand
+                       ,i_class
+                       ,i_category)
+order by qoh, i_product_name, i_brand, i_class, i_category
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q23.sql b/benchmarks/tpc/queries/tpcds/q23.sql
new file mode 100644
index 0000000000..220bf5bf72
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q23.sql
@@ -0,0 +1,108 @@
+-- CometBench-DS query 23 derived from TPC-DS query 23 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with frequent_ss_items as 
+ (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
+  from store_sales
+      ,date_dim 
+      ,item
+  where ss_sold_date_sk = d_date_sk
+    and ss_item_sk = i_item_sk 
+    and d_year in (2000,2000+1,2000+2,2000+3)
+  group by substr(i_item_desc,1,30),i_item_sk,d_date
+  having count(*) >4),
+ max_store_sales as
+ (select max(csales) tpcds_cmax 
+  from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
+        from store_sales
+            ,customer
+            ,date_dim 
+        where ss_customer_sk = c_customer_sk
+         and ss_sold_date_sk = d_date_sk
+         and d_year in (2000,2000+1,2000+2,2000+3) 
+        group by c_customer_sk)),
+ best_ss_customer as
+ (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
+  from store_sales
+      ,customer
+  where ss_customer_sk = c_customer_sk
+  group by c_customer_sk
+  having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select
+  *
+from
+ max_store_sales))
+  select  sum(sales)
+ from (select cs_quantity*cs_list_price sales
+       from catalog_sales
+           ,date_dim 
+       where d_year = 2000 
+         and d_moy = 3 
+         and cs_sold_date_sk = d_date_sk 
+         and cs_item_sk in (select item_sk from frequent_ss_items)
+         and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
+      union all
+      select ws_quantity*ws_list_price sales
+       from web_sales 
+           ,date_dim 
+       where d_year = 2000 
+         and d_moy = 3 
+         and ws_sold_date_sk = d_date_sk 
+         and ws_item_sk in (select item_sk from frequent_ss_items)
+         and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)) 
+  LIMIT 100;
+with frequent_ss_items as
+ (select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
+  from store_sales
+      ,date_dim
+      ,item
+  where ss_sold_date_sk = d_date_sk
+    and ss_item_sk = i_item_sk
+    and d_year in (2000,2000 + 1,2000 + 2,2000 + 3)
+  group by substr(i_item_desc,1,30),i_item_sk,d_date
+  having count(*) >4),
+ max_store_sales as
+ (select max(csales) tpcds_cmax
+  from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
+        from store_sales
+            ,customer
+            ,date_dim 
+        where ss_customer_sk = c_customer_sk
+         and ss_sold_date_sk = d_date_sk
+         and d_year in (2000,2000+1,2000+2,2000+3)
+        group by c_customer_sk)),
+ best_ss_customer as
+ (select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
+  from store_sales
+      ,customer
+  where ss_customer_sk = c_customer_sk
+  group by c_customer_sk
+  having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select
+  *
+ from max_store_sales))
+  select  c_last_name,c_first_name,sales
+ from (select c_last_name,c_first_name,sum(cs_quantity*cs_list_price) sales
+        from catalog_sales
+            ,customer
+            ,date_dim 
+        where d_year = 2000 
+         and d_moy = 3 
+         and cs_sold_date_sk = d_date_sk 
+         and cs_item_sk in (select item_sk from frequent_ss_items)
+         and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
+         and cs_bill_customer_sk = c_customer_sk 
+       group by c_last_name,c_first_name
+      union all
+      select c_last_name,c_first_name,sum(ws_quantity*ws_list_price) sales
+       from web_sales
+           ,customer
+           ,date_dim 
+       where d_year = 2000 
+         and d_moy = 3 
+         and ws_sold_date_sk = d_date_sk 
+         and ws_item_sk in (select item_sk from frequent_ss_items)
+         and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer)
+         and ws_bill_customer_sk = c_customer_sk
+       group by c_last_name,c_first_name) 
+     order by c_last_name,c_first_name,sales
+   LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q24.sql b/benchmarks/tpc/queries/tpcds/q24.sql
new file mode 100644
index 0000000000..119f86267b
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q24.sql
@@ -0,0 +1,108 @@
+-- CometBench-DS query 24 derived from TPC-DS query 24 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ssales as
+(select c_last_name
+      ,c_first_name
+      ,s_store_name
+      ,ca_state
+      ,s_state
+      ,i_color
+      ,i_current_price
+      ,i_manager_id
+      ,i_units
+      ,i_size
+      ,sum(ss_net_profit) netpaid
+from store_sales
+    ,store_returns
+    ,store
+    ,item
+    ,customer
+    ,customer_address
+where ss_ticket_number = sr_ticket_number
+  and ss_item_sk = sr_item_sk
+  and ss_customer_sk = c_customer_sk
+  and ss_item_sk = i_item_sk
+  and ss_store_sk = s_store_sk
+  and c_current_addr_sk = ca_address_sk
+  and c_birth_country <> upper(ca_country)
+  and s_zip = ca_zip
+and s_market_id=10
+group by c_last_name
+        ,c_first_name
+        ,s_store_name
+        ,ca_state
+        ,s_state
+        ,i_color
+        ,i_current_price
+        ,i_manager_id
+        ,i_units
+        ,i_size)
+select c_last_name
+      ,c_first_name
+      ,s_store_name
+      ,sum(netpaid) paid
+from ssales
+where i_color = 'orchid'
+group by c_last_name
+        ,c_first_name
+        ,s_store_name
+having sum(netpaid) > (select 0.05*avg(netpaid)
+                                 from ssales)
+order by c_last_name
+        ,c_first_name
+        ,s_store_name
+;
+with ssales as
+(select c_last_name
+      ,c_first_name
+      ,s_store_name
+      ,ca_state
+      ,s_state
+      ,i_color
+      ,i_current_price
+      ,i_manager_id
+      ,i_units
+      ,i_size
+      ,sum(ss_net_profit) netpaid
+from store_sales
+    ,store_returns
+    ,store
+    ,item
+    ,customer
+    ,customer_address
+where ss_ticket_number = sr_ticket_number
+  and ss_item_sk = sr_item_sk
+  and ss_customer_sk = c_customer_sk
+  and ss_item_sk = i_item_sk
+  and ss_store_sk = s_store_sk
+  and c_current_addr_sk = ca_address_sk
+  and c_birth_country <> upper(ca_country)
+  and s_zip = ca_zip
+  and s_market_id = 10
+group by c_last_name
+        ,c_first_name
+        ,s_store_name
+        ,ca_state
+        ,s_state
+        ,i_color
+        ,i_current_price
+        ,i_manager_id
+        ,i_units
+        ,i_size)
+select c_last_name
+      ,c_first_name
+      ,s_store_name
+      ,sum(netpaid) paid
+from ssales
+where i_color = 'green'
+group by c_last_name
+        ,c_first_name
+        ,s_store_name
+having sum(netpaid) > (select 0.05*avg(netpaid)
+                           from ssales)
+order by c_last_name
+        ,c_first_name
+        ,s_store_name
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q25.sql b/benchmarks/tpc/queries/tpcds/q25.sql
new file mode 100644
index 0000000000..eda5d6f724
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q25.sql
@@ -0,0 +1,49 @@
+-- CometBench-DS query 25 derived from TPC-DS query 25 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ ,min(ss_net_profit) as store_sales_profit
+ ,min(sr_net_loss) as store_returns_loss
+ ,min(cs_net_profit) as catalog_sales_profit
+ from
+ store_sales
+ ,store_returns
+ ,catalog_sales
+ ,date_dim d1
+ ,date_dim d2
+ ,date_dim d3
+ ,store
+ ,item
+ where
+ d1.d_moy = 4
+ and d1.d_year = 2002
+ and d1.d_date_sk = ss_sold_date_sk
+ and i_item_sk = ss_item_sk
+ and s_store_sk = ss_store_sk
+ and ss_customer_sk = sr_customer_sk
+ and ss_item_sk = sr_item_sk
+ and ss_ticket_number = sr_ticket_number
+ and sr_returned_date_sk = d2.d_date_sk
+ and d2.d_moy               between 4 and  10
+ and d2.d_year              = 2002
+ and sr_customer_sk = cs_bill_customer_sk
+ and sr_item_sk = cs_item_sk
+ and cs_sold_date_sk = d3.d_date_sk
+ and d3.d_moy               between 4 and  10 
+ and d3.d_year              = 2002
+ group by
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+ order by
+ i_item_id
+ ,i_item_desc
+ ,s_store_id
+ ,s_store_name
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q26.sql b/benchmarks/tpc/queries/tpcds/q26.sql
new file mode 100644
index 0000000000..44cc067b3a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q26.sql
@@ -0,0 +1,22 @@
+-- CometBench-DS query 26 derived from TPC-DS query 26 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id, 
+        avg(cs_quantity) agg1,
+        avg(cs_list_price) agg2,
+        avg(cs_coupon_amt) agg3,
+        avg(cs_sales_price) agg4 
+ from catalog_sales, customer_demographics, date_dim, item, promotion
+ where cs_sold_date_sk = d_date_sk and
+       cs_item_sk = i_item_sk and
+       cs_bill_cdemo_sk = cd_demo_sk and
+       cs_promo_sk = p_promo_sk and
+       cd_gender = 'F' and 
+       cd_marital_status = 'M' and
+       cd_education_status = '4 yr Degree' and
+       (p_channel_email = 'N' or p_channel_event = 'N') and
+       d_year = 2000 
+ group by i_item_id
+ order by i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q27.sql b/benchmarks/tpc/queries/tpcds/q27.sql
new file mode 100644
index 0000000000..d141d56a8a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q27.sql
@@ -0,0 +1,24 @@
+-- CometBench-DS query 27 derived from TPC-DS query 27 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id,
+        s_state, grouping(s_state) g_state,
+        avg(ss_quantity) agg1,
+        avg(ss_list_price) agg2,
+        avg(ss_coupon_amt) agg3,
+        avg(ss_sales_price) agg4
+ from store_sales, customer_demographics, date_dim, store, item
+ where ss_sold_date_sk = d_date_sk and
+       ss_item_sk = i_item_sk and
+       ss_store_sk = s_store_sk and
+       ss_cdemo_sk = cd_demo_sk and
+       cd_gender = 'M' and
+       cd_marital_status = 'U' and
+       cd_education_status = 'Secondary' and
+       d_year = 2000 and
+       s_state in ('TN','TN', 'TN', 'TN', 'TN', 'TN')
+ group by rollup (i_item_id, s_state)
+ order by i_item_id
+         ,s_state
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q28.sql b/benchmarks/tpc/queries/tpcds/q28.sql
new file mode 100644
index 0000000000..a34b079dea
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q28.sql
@@ -0,0 +1,54 @@
+-- CometBench-DS query 28 derived from TPC-DS query 28 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  *
+from (select avg(ss_list_price) B1_LP
+            ,count(ss_list_price) B1_CNT
+            ,count(distinct ss_list_price) B1_CNTD
+      from store_sales
+      where ss_quantity between 0 and 5
+        and (ss_list_price between 28 and 28+10 
+             or ss_coupon_amt between 12573 and 12573+1000
+             or ss_wholesale_cost between 33 and 33+20)) B1,
+     (select avg(ss_list_price) B2_LP
+            ,count(ss_list_price) B2_CNT
+            ,count(distinct ss_list_price) B2_CNTD
+      from store_sales
+      where ss_quantity between 6 and 10
+        and (ss_list_price between 143 and 143+10
+          or ss_coupon_amt between 5562 and 5562+1000
+          or ss_wholesale_cost between 45 and 45+20)) B2,
+     (select avg(ss_list_price) B3_LP
+            ,count(ss_list_price) B3_CNT
+            ,count(distinct ss_list_price) B3_CNTD
+      from store_sales
+      where ss_quantity between 11 and 15
+        and (ss_list_price between 159 and 159+10
+          or ss_coupon_amt between 2807 and 2807+1000
+          or ss_wholesale_cost between 24 and 24+20)) B3,
+     (select avg(ss_list_price) B4_LP
+            ,count(ss_list_price) B4_CNT
+            ,count(distinct ss_list_price) B4_CNTD
+      from store_sales
+      where ss_quantity between 16 and 20
+        and (ss_list_price between 24 and 24+10
+          or ss_coupon_amt between 3706 and 3706+1000
+          or ss_wholesale_cost between 46 and 46+20)) B4,
+     (select avg(ss_list_price) B5_LP
+            ,count(ss_list_price) B5_CNT
+            ,count(distinct ss_list_price) B5_CNTD
+      from store_sales
+      where ss_quantity between 21 and 25
+        and (ss_list_price between 76 and 76+10
+          or ss_coupon_amt between 2096 and 2096+1000
+          or ss_wholesale_cost between 50 and 50+20)) B5,
+     (select avg(ss_list_price) B6_LP
+            ,count(ss_list_price) B6_CNT
+            ,count(distinct ss_list_price) B6_CNTD
+      from store_sales
+      where ss_quantity between 26 and 30
+        and (ss_list_price between 169 and 169+10
+          or ss_coupon_amt between 10672 and 10672+1000
+          or ss_wholesale_cost between 58 and 58+20)) B6
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q29.sql b/benchmarks/tpc/queries/tpcds/q29.sql
new file mode 100644
index 0000000000..3d6a7f8d0b
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q29.sql
@@ -0,0 +1,48 @@
+-- CometBench-DS query 29 derived from TPC-DS query 29 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select   
+     i_item_id
+    ,i_item_desc
+    ,s_store_id
+    ,s_store_name
+    ,stddev_samp(ss_quantity)        as store_sales_quantity
+    ,stddev_samp(sr_return_quantity) as store_returns_quantity
+    ,stddev_samp(cs_quantity)        as catalog_sales_quantity
+ from
+    store_sales
+   ,store_returns
+   ,catalog_sales
+   ,date_dim             d1
+   ,date_dim             d2
+   ,date_dim             d3
+   ,store
+   ,item
+ where
+     d1.d_moy               = 4 
+ and d1.d_year              = 1999
+ and d1.d_date_sk           = ss_sold_date_sk
+ and i_item_sk              = ss_item_sk
+ and s_store_sk             = ss_store_sk
+ and ss_customer_sk         = sr_customer_sk
+ and ss_item_sk             = sr_item_sk
+ and ss_ticket_number       = sr_ticket_number
+ and sr_returned_date_sk    = d2.d_date_sk
+ and d2.d_moy               between 4 and  4 + 3 
+ and d2.d_year              = 1999
+ and sr_customer_sk         = cs_bill_customer_sk
+ and sr_item_sk             = cs_item_sk
+ and cs_sold_date_sk        = d3.d_date_sk     
+ and d3.d_year              in (1999,1999+1,1999+2)
+ group by
+    i_item_id
+   ,i_item_desc
+   ,s_store_id
+   ,s_store_name
+ order by
+    i_item_id 
+   ,i_item_desc
+   ,s_store_id
+   ,s_store_name
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q3.sql b/benchmarks/tpc/queries/tpcds/q3.sql
new file mode 100644
index 0000000000..2890c02e85
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q3.sql
@@ -0,0 +1,22 @@
+-- CometBench-DS query 3 derived from TPC-DS query 3 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  dt.d_year 
+       ,item.i_brand_id brand_id 
+       ,item.i_brand brand
+       ,sum(ss_net_profit) sum_agg
+ from  date_dim dt 
+      ,store_sales
+      ,item
+ where dt.d_date_sk = store_sales.ss_sold_date_sk
+   and store_sales.ss_item_sk = item.i_item_sk
+   and item.i_manufact_id = 445
+   and dt.d_moy=12
+ group by dt.d_year
+      ,item.i_brand
+      ,item.i_brand_id
+ order by dt.d_year
+         ,sum_agg desc
+         ,brand_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q30.sql b/benchmarks/tpc/queries/tpcds/q30.sql
new file mode 100644
index 0000000000..658653381f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q30.sql
@@ -0,0 +1,32 @@
+-- CometBench-DS query 30 derived from TPC-DS query 30 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with customer_total_return as
+ (select wr_returning_customer_sk as ctr_customer_sk
+        ,ca_state as ctr_state, 
+ 	sum(wr_return_amt) as ctr_total_return
+ from web_returns
+     ,date_dim
+     ,customer_address
+ where wr_returned_date_sk = d_date_sk 
+   and d_year =2000
+   and wr_returning_addr_sk = ca_address_sk 
+ group by wr_returning_customer_sk
+         ,ca_state)
+  select  c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
+       ,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
+       ,c_last_review_date_sk,ctr_total_return
+ from customer_total_return ctr1
+     ,customer_address
+     ,customer
+ where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
+ 			  from customer_total_return ctr2 
+                  	  where ctr1.ctr_state = ctr2.ctr_state)
+       and ca_address_sk = c_current_addr_sk
+       and ca_state = 'KS'
+       and ctr1.ctr_customer_sk = c_customer_sk
+ order by c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
+                  ,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
+                  ,c_last_review_date_sk,ctr_total_return
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q31.sql b/benchmarks/tpc/queries/tpcds/q31.sql
new file mode 100644
index 0000000000..509a86fa43
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q31.sql
@@ -0,0 +1,53 @@
+-- CometBench-DS query 31 derived from TPC-DS query 31 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ss as
+ (select ca_county,d_qoy, d_year,sum(ss_ext_sales_price) as store_sales
+ from store_sales,date_dim,customer_address
+ where ss_sold_date_sk = d_date_sk
+  and ss_addr_sk=ca_address_sk
+ group by ca_county,d_qoy, d_year),
+ ws as
+ (select ca_county,d_qoy, d_year,sum(ws_ext_sales_price) as web_sales
+ from web_sales,date_dim,customer_address
+ where ws_sold_date_sk = d_date_sk
+  and ws_bill_addr_sk=ca_address_sk
+ group by ca_county,d_qoy, d_year)
+ select 
+        ss1.ca_county
+       ,ss1.d_year
+       ,ws2.web_sales/ws1.web_sales web_q1_q2_increase
+       ,ss2.store_sales/ss1.store_sales store_q1_q2_increase
+       ,ws3.web_sales/ws2.web_sales web_q2_q3_increase
+       ,ss3.store_sales/ss2.store_sales store_q2_q3_increase
+ from
+        ss ss1
+       ,ss ss2
+       ,ss ss3
+       ,ws ws1
+       ,ws ws2
+       ,ws ws3
+ where
+    ss1.d_qoy = 1
+    and ss1.d_year = 1999
+    and ss1.ca_county = ss2.ca_county
+    and ss2.d_qoy = 2
+    and ss2.d_year = 1999
+ and ss2.ca_county = ss3.ca_county
+    and ss3.d_qoy = 3
+    and ss3.d_year = 1999
+    and ss1.ca_county = ws1.ca_county
+    and ws1.d_qoy = 1
+    and ws1.d_year = 1999
+    and ws1.ca_county = ws2.ca_county
+    and ws2.d_qoy = 2
+    and ws2.d_year = 1999
+    and ws1.ca_county = ws3.ca_county
+    and ws3.d_qoy = 3
+    and ws3.d_year =1999
+    and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end 
+       > case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end
+    and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end
+       > case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end
+ order by ss1.ca_county;
+
diff --git a/benchmarks/tpc/queries/tpcds/q32.sql b/benchmarks/tpc/queries/tpcds/q32.sql
new file mode 100644
index 0000000000..058756465c
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q32.sql
@@ -0,0 +1,29 @@
+-- CometBench-DS query 32 derived from TPC-DS query 32 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  sum(cs_ext_discount_amt)  as "excess discount amount" 
+from 
+   catalog_sales 
+   ,item 
+   ,date_dim
+where
+i_manufact_id = 283
+and i_item_sk = cs_item_sk 
+and d_date between '1999-02-22' and 
+        (cast('1999-02-22' as date) + 90 days)
+and d_date_sk = cs_sold_date_sk 
+and cs_ext_discount_amt  
+     > ( 
+         select 
+            1.3 * avg(cs_ext_discount_amt) 
+         from 
+            catalog_sales 
+           ,date_dim
+         where 
+              cs_item_sk = i_item_sk 
+          and d_date between '1999-02-22' and
+                             (cast('1999-02-22' as date) + 90 days)
+          and d_date_sk = cs_sold_date_sk 
+      ) 
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q33.sql b/benchmarks/tpc/queries/tpcds/q33.sql
new file mode 100644
index 0000000000..97f1f0fbf8
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q33.sql
@@ -0,0 +1,76 @@
+-- CometBench-DS query 33 derived from TPC-DS query 33 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ss as (
+ select
+          i_manufact_id,sum(ss_ext_sales_price) total_sales
+ from
+ 	store_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_manufact_id in (select
+  i_manufact_id
+from
+ item
+where i_category in ('Books'))
+ and     ss_item_sk              = i_item_sk
+ and     ss_sold_date_sk         = d_date_sk
+ and     d_year                  = 1999
+ and     d_moy                   = 4
+ and     ss_addr_sk              = ca_address_sk
+ and     ca_gmt_offset           = -5 
+ group by i_manufact_id),
+ cs as (
+ select
+          i_manufact_id,sum(cs_ext_sales_price) total_sales
+ from
+ 	catalog_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_manufact_id               in (select
+  i_manufact_id
+from
+ item
+where i_category in ('Books'))
+ and     cs_item_sk              = i_item_sk
+ and     cs_sold_date_sk         = d_date_sk
+ and     d_year                  = 1999
+ and     d_moy                   = 4
+ and     cs_bill_addr_sk         = ca_address_sk
+ and     ca_gmt_offset           = -5 
+ group by i_manufact_id),
+ ws as (
+ select
+          i_manufact_id,sum(ws_ext_sales_price) total_sales
+ from
+ 	web_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_manufact_id               in (select
+  i_manufact_id
+from
+ item
+where i_category in ('Books'))
+ and     ws_item_sk              = i_item_sk
+ and     ws_sold_date_sk         = d_date_sk
+ and     d_year                  = 1999
+ and     d_moy                   = 4
+ and     ws_bill_addr_sk         = ca_address_sk
+ and     ca_gmt_offset           = -5
+ group by i_manufact_id)
+  select  i_manufact_id ,sum(total_sales) total_sales
+ from  (select * from ss 
+        union all
+        select * from cs 
+        union all
+        select * from ws) tmp1
+ group by i_manufact_id
+ order by total_sales
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q34.sql b/benchmarks/tpc/queries/tpcds/q34.sql
new file mode 100644
index 0000000000..2c772481ef
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q34.sql
@@ -0,0 +1,32 @@
+-- CometBench-DS query 34 derived from TPC-DS query 34 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select c_last_name
+       ,c_first_name
+       ,c_salutation
+       ,c_preferred_cust_flag
+       ,ss_ticket_number
+       ,cnt from
+   (select ss_ticket_number
+          ,ss_customer_sk
+          ,count(*) cnt
+    from store_sales,date_dim,store,household_demographics
+    where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+    and store_sales.ss_store_sk = store.s_store_sk  
+    and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+    and (date_dim.d_dom between 1 and 3 or date_dim.d_dom between 25 and 28)
+    and (household_demographics.hd_buy_potential = '501-1000' or
+         household_demographics.hd_buy_potential = 'Unknown')
+    and household_demographics.hd_vehicle_count > 0
+    and (case when household_demographics.hd_vehicle_count > 0 
+	then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count 
+	else null 
+	end)  > 1.2
+    and date_dim.d_year in (2000,2000+1,2000+2)
+    and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
+                           'Williamson County','Williamson County','Williamson County','Williamson County')
+    group by ss_ticket_number,ss_customer_sk) dn,customer
+    where ss_customer_sk = c_customer_sk
+      and cnt between 15 and 20
+    order by c_last_name,c_first_name,c_salutation,c_preferred_cust_flag desc, ss_ticket_number;
+
diff --git a/benchmarks/tpc/queries/tpcds/q35.sql b/benchmarks/tpc/queries/tpcds/q35.sql
new file mode 100644
index 0000000000..5876bb94ad
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q35.sql
@@ -0,0 +1,59 @@
+-- CometBench-DS query 35 derived from TPC-DS query 35 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select   
+  ca_state,
+  cd_gender,
+  cd_marital_status,
+  cd_dep_count,
+  count(*) cnt1,
+  min(cd_dep_count),
+  max(cd_dep_count),
+  avg(cd_dep_count),
+  cd_dep_employed_count,
+  count(*) cnt2,
+  min(cd_dep_employed_count),
+  max(cd_dep_employed_count),
+  avg(cd_dep_employed_count),
+  cd_dep_college_count,
+  count(*) cnt3,
+  min(cd_dep_college_count),
+  max(cd_dep_college_count),
+  avg(cd_dep_college_count)
+ from
+  customer c,customer_address ca,customer_demographics
+ where
+  c.c_current_addr_sk = ca.ca_address_sk and
+  cd_demo_sk = c.c_current_cdemo_sk and 
+  exists (select *
+          from store_sales,date_dim
+          where c.c_customer_sk = ss_customer_sk and
+                ss_sold_date_sk = d_date_sk and
+                d_year = 2000 and
+                d_qoy < 4) and
+   (exists (select *
+            from web_sales,date_dim
+            where c.c_customer_sk = ws_bill_customer_sk and
+                  ws_sold_date_sk = d_date_sk and
+                  d_year = 2000 and
+                  d_qoy < 4) or 
+    exists (select * 
+            from catalog_sales,date_dim
+            where c.c_customer_sk = cs_ship_customer_sk and
+                  cs_sold_date_sk = d_date_sk and
+                  d_year = 2000 and
+                  d_qoy < 4))
+ group by ca_state,
+          cd_gender,
+          cd_marital_status,
+          cd_dep_count,
+          cd_dep_employed_count,
+          cd_dep_college_count
+ order by ca_state,
+          cd_gender,
+          cd_marital_status,
+          cd_dep_count,
+          cd_dep_employed_count,
+          cd_dep_college_count
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q36.sql b/benchmarks/tpc/queries/tpcds/q36.sql
new file mode 100644
index 0000000000..0b5d84adcf
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q36.sql
@@ -0,0 +1,31 @@
+-- CometBench-DS query 36 derived from TPC-DS query 36 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+    sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin
+   ,i_category
+   ,i_class
+   ,grouping(i_category)+grouping(i_class) as lochierarchy
+   ,rank() over (
+ 	partition by grouping(i_category)+grouping(i_class),
+ 	case when grouping(i_class) = 0 then i_category end 
+ 	order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent
+ from
+    store_sales
+   ,date_dim       d1
+   ,item
+   ,store
+ where
+    d1.d_year = 2001 
+ and d1.d_date_sk = ss_sold_date_sk
+ and i_item_sk  = ss_item_sk 
+ and s_store_sk  = ss_store_sk
+ and s_state in ('TN','TN','TN','TN',
+                 'TN','TN','TN','TN')
+ group by rollup(i_category,i_class)
+ order by
+   lochierarchy desc
+  ,case when lochierarchy = 0 then i_category end
+  ,rank_within_parent
+   LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q37.sql b/benchmarks/tpc/queries/tpcds/q37.sql
new file mode 100644
index 0000000000..4cc1d66d29
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q37.sql
@@ -0,0 +1,18 @@
+-- CometBench-DS query 37 derived from TPC-DS query 37 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id
+       ,i_item_desc
+       ,i_current_price
+ from item, inventory, date_dim, catalog_sales
+ where i_current_price between 26 and 26 + 30
+ and inv_item_sk = i_item_sk
+ and d_date_sk=inv_date_sk
+ and d_date between cast('2001-06-09' as date) and (cast('2001-06-09' as date) +  60 days)
+ and i_manufact_id in (744,884,722,693)
+ and inv_quantity_on_hand between 100 and 500
+ and cs_item_sk = i_item_sk
+ group by i_item_id,i_item_desc,i_current_price
+ order by i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q38.sql b/benchmarks/tpc/queries/tpcds/q38.sql
new file mode 100644
index 0000000000..563be4e807
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q38.sql
@@ -0,0 +1,24 @@
+-- CometBench-DS query 38 derived from TPC-DS query 38 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  count(*) from (
+    select distinct c_last_name, c_first_name, d_date
+    from store_sales, date_dim, customer
+          where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+      and store_sales.ss_customer_sk = customer.c_customer_sk
+      and d_month_seq between 1190 and 1190 + 11
+  intersect
+    select distinct c_last_name, c_first_name, d_date
+    from catalog_sales, date_dim, customer
+          where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
+      and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
+      and d_month_seq between 1190 and 1190 + 11
+  intersect
+    select distinct c_last_name, c_first_name, d_date
+    from web_sales, date_dim, customer
+          where web_sales.ws_sold_date_sk = date_dim.d_date_sk
+      and web_sales.ws_bill_customer_sk = customer.c_customer_sk
+      and d_month_seq between 1190 and 1190 + 11
+) hot_cust
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q39.sql b/benchmarks/tpc/queries/tpcds/q39.sql
new file mode 100644
index 0000000000..41d981501c
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q39.sql
@@ -0,0 +1,55 @@
+-- CometBench-DS query 39 derived from TPC-DS query 39 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with inv as
+(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+       ,stdev,mean, case mean when 0 then null else stdev/mean end cov
+ from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+            ,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean
+      from inventory
+          ,item
+          ,warehouse
+          ,date_dim
+      where inv_item_sk = i_item_sk
+        and inv_warehouse_sk = w_warehouse_sk
+        and inv_date_sk = d_date_sk
+        and d_year =2001
+      group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo
+ where case mean when 0 then 0 else stdev/mean end > 1)
+select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov
+        ,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov
+from inv inv1,inv inv2
+where inv1.i_item_sk = inv2.i_item_sk
+  and inv1.w_warehouse_sk =  inv2.w_warehouse_sk
+  and inv1.d_moy=1
+  and inv2.d_moy=1+1
+order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
+        ,inv2.d_moy,inv2.mean, inv2.cov
+;
+with inv as
+(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+       ,stdev,mean, case mean when 0 then null else stdev/mean end cov
+ from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
+            ,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean
+      from inventory
+          ,item
+          ,warehouse
+          ,date_dim
+      where inv_item_sk = i_item_sk
+        and inv_warehouse_sk = w_warehouse_sk
+        and inv_date_sk = d_date_sk
+        and d_year =2001
+      group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo
+ where case mean when 0 then 0 else stdev/mean end > 1)
+select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov
+        ,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov
+from inv inv1,inv inv2
+where inv1.i_item_sk = inv2.i_item_sk
+  and inv1.w_warehouse_sk =  inv2.w_warehouse_sk
+  and inv1.d_moy=1
+  and inv2.d_moy=1+1
+  and inv1.cov > 1.5
+order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
+        ,inv2.d_moy,inv2.mean, inv2.cov
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q4.sql b/benchmarks/tpc/queries/tpcds/q4.sql
new file mode 100644
index 0000000000..8edacf2f9d
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q4.sql
@@ -0,0 +1,117 @@
+-- CometBench-DS query 4 derived from TPC-DS query 4 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with year_total as (
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,c_preferred_cust_flag customer_preferred_cust_flag
+       ,c_birth_country customer_birth_country
+       ,c_login customer_login
+       ,c_email_address customer_email_address
+       ,d_year dyear
+       ,sum(((ss_ext_list_price-ss_ext_wholesale_cost-ss_ext_discount_amt)+ss_ext_sales_price)/2) year_total
+       ,'s' sale_type
+ from customer
+     ,store_sales
+     ,date_dim
+ where c_customer_sk = ss_customer_sk
+   and ss_sold_date_sk = d_date_sk
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,c_preferred_cust_flag
+         ,c_birth_country
+         ,c_login
+         ,c_email_address
+         ,d_year
+ union all
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,c_preferred_cust_flag customer_preferred_cust_flag
+       ,c_birth_country customer_birth_country
+       ,c_login customer_login
+       ,c_email_address customer_email_address
+       ,d_year dyear
+       ,sum((((cs_ext_list_price-cs_ext_wholesale_cost-cs_ext_discount_amt)+cs_ext_sales_price)/2) ) year_total
+       ,'c' sale_type
+ from customer
+     ,catalog_sales
+     ,date_dim
+ where c_customer_sk = cs_bill_customer_sk
+   and cs_sold_date_sk = d_date_sk
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,c_preferred_cust_flag
+         ,c_birth_country
+         ,c_login
+         ,c_email_address
+         ,d_year
+union all
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,c_preferred_cust_flag customer_preferred_cust_flag
+       ,c_birth_country customer_birth_country
+       ,c_login customer_login
+       ,c_email_address customer_email_address
+       ,d_year dyear
+       ,sum((((ws_ext_list_price-ws_ext_wholesale_cost-ws_ext_discount_amt)+ws_ext_sales_price)/2) ) year_total
+       ,'w' sale_type
+ from customer
+     ,web_sales
+     ,date_dim
+ where c_customer_sk = ws_bill_customer_sk
+   and ws_sold_date_sk = d_date_sk
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,c_preferred_cust_flag
+         ,c_birth_country
+         ,c_login
+         ,c_email_address
+         ,d_year
+         )
+  select  
+                  t_s_secyear.customer_id
+                 ,t_s_secyear.customer_first_name
+                 ,t_s_secyear.customer_last_name
+                 ,t_s_secyear.customer_email_address
+ from year_total t_s_firstyear
+     ,year_total t_s_secyear
+     ,year_total t_c_firstyear
+     ,year_total t_c_secyear
+     ,year_total t_w_firstyear
+     ,year_total t_w_secyear
+ where t_s_secyear.customer_id = t_s_firstyear.customer_id
+   and t_s_firstyear.customer_id = t_c_secyear.customer_id
+   and t_s_firstyear.customer_id = t_c_firstyear.customer_id
+   and t_s_firstyear.customer_id = t_w_firstyear.customer_id
+   and t_s_firstyear.customer_id = t_w_secyear.customer_id
+   and t_s_firstyear.sale_type = 's'
+   and t_c_firstyear.sale_type = 'c'
+   and t_w_firstyear.sale_type = 'w'
+   and t_s_secyear.sale_type = 's'
+   and t_c_secyear.sale_type = 'c'
+   and t_w_secyear.sale_type = 'w'
+   and t_s_firstyear.dyear =  2001
+   and t_s_secyear.dyear = 2001+1
+   and t_c_firstyear.dyear =  2001
+   and t_c_secyear.dyear =  2001+1
+   and t_w_firstyear.dyear = 2001
+   and t_w_secyear.dyear = 2001+1
+   and t_s_firstyear.year_total > 0
+   and t_c_firstyear.year_total > 0
+   and t_w_firstyear.year_total > 0
+   and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
+           > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
+   and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
+           > case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
+ order by t_s_secyear.customer_id
+         ,t_s_secyear.customer_first_name
+         ,t_s_secyear.customer_last_name
+         ,t_s_secyear.customer_email_address
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q40.sql b/benchmarks/tpc/queries/tpcds/q40.sql
new file mode 100644
index 0000000000..f1bd48aa7a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q40.sql
@@ -0,0 +1,29 @@
+-- CometBench-DS query 40 derived from TPC-DS query 40 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   w_state
+  ,i_item_id
+  ,sum(case when (cast(d_date as date) < cast ('2002-05-18' as date)) 
+ 		then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before
+  ,sum(case when (cast(d_date as date) >= cast ('2002-05-18' as date)) 
+ 		then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after
+ from
+   catalog_sales left outer join catalog_returns on
+       (cs_order_number = cr_order_number 
+        and cs_item_sk = cr_item_sk)
+  ,warehouse 
+  ,item
+  ,date_dim
+ where
+     i_current_price between 0.99 and 1.49
+ and i_item_sk          = cs_item_sk
+ and cs_warehouse_sk    = w_warehouse_sk 
+ and cs_sold_date_sk    = d_date_sk
+ and d_date between (cast ('2002-05-18' as date) - 30 days)
+                and (cast ('2002-05-18' as date) + 30 days) 
+ group by
+    w_state,i_item_id
+ order by w_state,i_item_id
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q41.sql b/benchmarks/tpc/queries/tpcds/q41.sql
new file mode 100644
index 0000000000..df2db88833
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q41.sql
@@ -0,0 +1,53 @@
+-- CometBench-DS query 41 derived from TPC-DS query 41 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  distinct(i_product_name)
+ from item i1
+ where i_manufact_id between 668 and 668+40 
+   and (select count(*) as item_cnt
+        from item
+        where (i_manufact = i1.i_manufact and
+        ((i_category = 'Women' and 
+        (i_color = 'cream' or i_color = 'ghost') and 
+        (i_units = 'Ton' or i_units = 'Gross') and
+        (i_size = 'economy' or i_size = 'small')
+        ) or
+        (i_category = 'Women' and
+        (i_color = 'midnight' or i_color = 'burlywood') and
+        (i_units = 'Tsp' or i_units = 'Bundle') and
+        (i_size = 'medium' or i_size = 'extra large')
+        ) or
+        (i_category = 'Men' and
+        (i_color = 'lavender' or i_color = 'azure') and
+        (i_units = 'Each' or i_units = 'Lb') and
+        (i_size = 'large' or i_size = 'N/A')
+        ) or
+        (i_category = 'Men' and
+        (i_color = 'chocolate' or i_color = 'steel') and
+        (i_units = 'N/A' or i_units = 'Dozen') and
+        (i_size = 'economy' or i_size = 'small')
+        ))) or
+       (i_manufact = i1.i_manufact and
+        ((i_category = 'Women' and 
+        (i_color = 'floral' or i_color = 'royal') and 
+        (i_units = 'Unknown' or i_units = 'Tbl') and
+        (i_size = 'economy' or i_size = 'small')
+        ) or
+        (i_category = 'Women' and
+        (i_color = 'navy' or i_color = 'forest') and
+        (i_units = 'Bunch' or i_units = 'Dram') and
+        (i_size = 'medium' or i_size = 'extra large')
+        ) or
+        (i_category = 'Men' and
+        (i_color = 'cyan' or i_color = 'indian') and
+        (i_units = 'Carton' or i_units = 'Cup') and
+        (i_size = 'large' or i_size = 'N/A')
+        ) or
+        (i_category = 'Men' and
+        (i_color = 'coral' or i_color = 'pale') and
+        (i_units = 'Pallet' or i_units = 'Gram') and
+        (i_size = 'economy' or i_size = 'small')
+        )))) > 0
+ order by i_product_name
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q42.sql b/benchmarks/tpc/queries/tpcds/q42.sql
new file mode 100644
index 0000000000..3c565534a9
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q42.sql
@@ -0,0 +1,23 @@
+-- CometBench-DS query 42 derived from TPC-DS query 42 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  dt.d_year
+ 	,item.i_category_id
+ 	,item.i_category
+ 	,sum(ss_ext_sales_price)
+ from 	date_dim dt
+ 	,store_sales
+ 	,item
+ where dt.d_date_sk = store_sales.ss_sold_date_sk
+ 	and store_sales.ss_item_sk = item.i_item_sk
+ 	and item.i_manager_id = 1  	
+ 	and dt.d_moy=11
+ 	and dt.d_year=1998
+ group by 	dt.d_year
+ 		,item.i_category_id
+ 		,item.i_category
+ order by       sum(ss_ext_sales_price) desc,dt.d_year
+ 		,item.i_category_id
+ 		,item.i_category
+ LIMIT 100 ;
+
diff --git a/benchmarks/tpc/queries/tpcds/q43.sql b/benchmarks/tpc/queries/tpcds/q43.sql
new file mode 100644
index 0000000000..1aaf123c9a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q43.sql
@@ -0,0 +1,20 @@
+-- CometBench-DS query 43 derived from TPC-DS query 43 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  s_store_name, s_store_id,
+        sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
+        sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
+        sum(case when (d_day_name='Tuesday') then ss_sales_price else  null end) tue_sales,
+        sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
+        sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
+        sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
+        sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
+ from date_dim, store_sales, store
+ where d_date_sk = ss_sold_date_sk and
+       s_store_sk = ss_store_sk and
+       s_gmt_offset = -5 and
+       d_year = 2000 
+ group by s_store_name, s_store_id
+ order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q44.sql b/benchmarks/tpc/queries/tpcds/q44.sql
new file mode 100644
index 0000000000..f7e474249f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q44.sql
@@ -0,0 +1,36 @@
+-- CometBench-DS query 44 derived from TPC-DS query 44 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing
+from(select *
+     from (select item_sk,rank() over (order by rank_col asc) rnk
+           from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col 
+                 from store_sales ss1
+                 where ss_store_sk = 6
+                 group by ss_item_sk
+                 having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
+                                                  from store_sales
+                                                  where ss_store_sk = 6
+                                                    and ss_hdemo_sk is null
+                                                  group by ss_store_sk))V1)V11
+     where rnk  < 11) asceding,
+    (select *
+     from (select item_sk,rank() over (order by rank_col desc) rnk
+           from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
+                 from store_sales ss1
+                 where ss_store_sk = 6
+                 group by ss_item_sk
+                 having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
+                                                  from store_sales
+                                                  where ss_store_sk = 6
+                                                    and ss_hdemo_sk is null
+                                                  group by ss_store_sk))V2)V21
+     where rnk  < 11) descending,
+item i1,
+item i2
+where asceding.rnk = descending.rnk 
+  and i1.i_item_sk=asceding.item_sk
+  and i2.i_item_sk=descending.item_sk
+order by asceding.rnk
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q45.sql b/benchmarks/tpc/queries/tpcds/q45.sql
new file mode 100644
index 0000000000..dd77ce6cb3
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q45.sql
@@ -0,0 +1,21 @@
+-- CometBench-DS query 45 derived from TPC-DS query 45 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  ca_zip, ca_city, sum(ws_sales_price)
+ from web_sales, customer, customer_address, date_dim, item
+ where ws_bill_customer_sk = c_customer_sk
+ 	and c_current_addr_sk = ca_address_sk 
+ 	and ws_item_sk = i_item_sk 
+ 	and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792')
+ 	      or 
+ 	      i_item_id in (select i_item_id
+                             from item
+                             where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)
+                             )
+ 	    )
+ 	and ws_sold_date_sk = d_date_sk
+ 	and d_qoy = 2 and d_year = 2000
+ group by ca_zip, ca_city
+ order by ca_zip, ca_city
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q46.sql b/benchmarks/tpc/queries/tpcds/q46.sql
new file mode 100644
index 0000000000..1321f134ef
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q46.sql
@@ -0,0 +1,36 @@
+-- CometBench-DS query 46 derived from TPC-DS query 46 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  c_last_name
+       ,c_first_name
+       ,ca_city
+       ,bought_city
+       ,ss_ticket_number
+       ,amt,profit 
+ from
+   (select ss_ticket_number
+          ,ss_customer_sk
+          ,ca_city bought_city
+          ,sum(ss_coupon_amt) amt
+          ,sum(ss_net_profit) profit
+    from store_sales,date_dim,store,household_demographics,customer_address 
+    where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+    and store_sales.ss_store_sk = store.s_store_sk  
+    and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+    and store_sales.ss_addr_sk = customer_address.ca_address_sk
+    and (household_demographics.hd_dep_count = 3 or
+         household_demographics.hd_vehicle_count= 1)
+    and date_dim.d_dow in (6,0)
+    and date_dim.d_year in (1999,1999+1,1999+2) 
+    and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview') 
+    group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr
+    where ss_customer_sk = c_customer_sk
+      and customer.c_current_addr_sk = current_addr.ca_address_sk
+      and current_addr.ca_city <> bought_city
+  order by c_last_name
+          ,c_first_name
+          ,ca_city
+          ,bought_city
+          ,ss_ticket_number
+   LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q47.sql b/benchmarks/tpc/queries/tpcds/q47.sql
new file mode 100644
index 0000000000..5b29007c03
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q47.sql
@@ -0,0 +1,52 @@
+-- CometBench-DS query 47 derived from TPC-DS query 47 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with v1 as(
+ select i_category, i_brand,
+        s_store_name, s_company_name,
+        d_year, d_moy,
+        sum(ss_sales_price) sum_sales,
+        avg(sum(ss_sales_price)) over
+          (partition by i_category, i_brand,
+                     s_store_name, s_company_name, d_year)
+          avg_monthly_sales,
+        rank() over
+          (partition by i_category, i_brand,
+                     s_store_name, s_company_name
+           order by d_year, d_moy) rn
+ from item, store_sales, date_dim, store
+ where ss_item_sk = i_item_sk and
+       ss_sold_date_sk = d_date_sk and
+       ss_store_sk = s_store_sk and
+       (
+         d_year = 2001 or
+         ( d_year = 2001-1 and d_moy =12) or
+         ( d_year = 2001+1 and d_moy =1)
+       )
+ group by i_category, i_brand,
+          s_store_name, s_company_name,
+          d_year, d_moy),
+ v2 as(
+ select v1.i_category, v1.i_brand, v1.s_store_name, v1.s_company_name
+        ,v1.d_year
+        ,v1.avg_monthly_sales
+        ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
+ from v1, v1 v1_lag, v1 v1_lead
+ where v1.i_category = v1_lag.i_category and
+       v1.i_category = v1_lead.i_category and
+       v1.i_brand = v1_lag.i_brand and
+       v1.i_brand = v1_lead.i_brand and
+       v1.s_store_name = v1_lag.s_store_name and
+       v1.s_store_name = v1_lead.s_store_name and
+       v1.s_company_name = v1_lag.s_company_name and
+       v1.s_company_name = v1_lead.s_company_name and
+       v1.rn = v1_lag.rn + 1 and
+       v1.rn = v1_lead.rn - 1)
+  select  *
+ from v2
+ where  d_year = 2001 and    
+        avg_monthly_sales > 0 and
+        case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+ order by sum_sales - avg_monthly_sales, nsum
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q48.sql b/benchmarks/tpc/queries/tpcds/q48.sql
new file mode 100644
index 0000000000..cf08721423
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q48.sql
@@ -0,0 +1,68 @@
+-- CometBench-DS query 48 derived from TPC-DS query 48 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select sum (ss_quantity)
+ from store_sales, store, customer_demographics, customer_address, date_dim
+ where s_store_sk = ss_store_sk
+ and  ss_sold_date_sk = d_date_sk and d_year = 2001
+ and  
+ (
+  (
+   cd_demo_sk = ss_cdemo_sk
+   and 
+   cd_marital_status = 'W'
+   and 
+   cd_education_status = '2 yr Degree'
+   and 
+   ss_sales_price between 100.00 and 150.00  
+   )
+ or
+  (
+  cd_demo_sk = ss_cdemo_sk
+   and 
+   cd_marital_status = 'S'
+   and 
+   cd_education_status = 'Advanced Degree'
+   and 
+   ss_sales_price between 50.00 and 100.00   
+  )
+ or 
+ (
+  cd_demo_sk = ss_cdemo_sk
+  and 
+   cd_marital_status = 'D'
+   and 
+   cd_education_status = 'Primary'
+   and 
+   ss_sales_price between 150.00 and 200.00  
+ )
+ )
+ and
+ (
+  (
+  ss_addr_sk = ca_address_sk
+  and
+  ca_country = 'United States'
+  and
+  ca_state in ('IL', 'KY', 'OR')
+  and ss_net_profit between 0 and 2000  
+  )
+ or
+  (ss_addr_sk = ca_address_sk
+  and
+  ca_country = 'United States'
+  and
+  ca_state in ('VA', 'FL', 'AL')
+  and ss_net_profit between 150 and 3000 
+  )
+ or
+  (ss_addr_sk = ca_address_sk
+  and
+  ca_country = 'United States'
+  and
+  ca_state in ('OK', 'IA', 'TX')
+  and ss_net_profit between 50 and 25000 
+  )
+ )
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q49.sql b/benchmarks/tpc/queries/tpcds/q49.sql
new file mode 100644
index 0000000000..3e37517bc4
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q49.sql
@@ -0,0 +1,130 @@
+-- CometBench-DS query 49 derived from TPC-DS query 49 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  channel, item, return_ratio, return_rank, currency_rank from
+ (select
+ 'web' as channel
+ ,web.item
+ ,web.return_ratio
+ ,web.return_rank
+ ,web.currency_rank
+ from (
+ 	select 
+ 	 item
+ 	,return_ratio
+ 	,currency_ratio
+ 	,rank() over (order by return_ratio) as return_rank
+ 	,rank() over (order by currency_ratio) as currency_rank
+ 	from
+ 	(	select ws.ws_item_sk as item
+ 		,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/
+ 		cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio
+ 		,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/
+ 		cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio
+ 		from 
+ 		 web_sales ws left outer join web_returns wr 
+ 			on (ws.ws_order_number = wr.wr_order_number and 
+ 			ws.ws_item_sk = wr.wr_item_sk)
+                 ,date_dim
+ 		where 
+ 			wr.wr_return_amt > 10000 
+ 			and ws.ws_net_profit > 1
+                         and ws.ws_net_paid > 0
+                         and ws.ws_quantity > 0
+                         and ws_sold_date_sk = d_date_sk
+                         and d_year = 2000
+                         and d_moy = 12
+ 		group by ws.ws_item_sk
+ 	) in_web
+ ) web
+ where 
+ (
+ web.return_rank <= 10
+ or
+ web.currency_rank <= 10
+ )
+ union
+ select 
+ 'catalog' as channel
+ ,catalog.item
+ ,catalog.return_ratio
+ ,catalog.return_rank
+ ,catalog.currency_rank
+ from (
+ 	select 
+ 	 item
+ 	,return_ratio
+ 	,currency_ratio
+ 	,rank() over (order by return_ratio) as return_rank
+ 	,rank() over (order by currency_ratio) as currency_rank
+ 	from
+ 	(	select 
+ 		cs.cs_item_sk as item
+ 		,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/
+ 		cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio
+ 		,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/
+ 		cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio
+ 		from 
+ 		catalog_sales cs left outer join catalog_returns cr
+ 			on (cs.cs_order_number = cr.cr_order_number and 
+ 			cs.cs_item_sk = cr.cr_item_sk)
+                ,date_dim
+ 		where 
+ 			cr.cr_return_amount > 10000 
+ 			and cs.cs_net_profit > 1
+                         and cs.cs_net_paid > 0
+                         and cs.cs_quantity > 0
+                         and cs_sold_date_sk = d_date_sk
+                         and d_year = 2000
+                         and d_moy = 12
+                 group by cs.cs_item_sk
+ 	) in_cat
+ ) catalog
+ where 
+ (
+ catalog.return_rank <= 10
+ or
+ catalog.currency_rank <=10
+ )
+ union
+ select 
+ 'store' as channel
+ ,store.item
+ ,store.return_ratio
+ ,store.return_rank
+ ,store.currency_rank
+ from (
+ 	select 
+ 	 item
+ 	,return_ratio
+ 	,currency_ratio
+ 	,rank() over (order by return_ratio) as return_rank
+ 	,rank() over (order by currency_ratio) as currency_rank
+ 	from
+ 	(	select sts.ss_item_sk as item
+ 		,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio
+ 		,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio
+ 		from 
+ 		store_sales sts left outer join store_returns sr
+ 			on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk)
+                ,date_dim
+ 		where 
+ 			sr.sr_return_amt > 10000 
+ 			and sts.ss_net_profit > 1
+                         and sts.ss_net_paid > 0 
+                         and sts.ss_quantity > 0
+                         and ss_sold_date_sk = d_date_sk
+                         and d_year = 2000
+                         and d_moy = 12
+ 		group by sts.ss_item_sk
+ 	) in_store
+ ) store
+ where  (
+ store.return_rank <= 10
+ or 
+ store.currency_rank <= 10
+ )
+ )
+ order by 1,4,5,2
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q5.sql b/benchmarks/tpc/queries/tpcds/q5.sql
new file mode 100644
index 0000000000..6b750b4c76
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q5.sql
@@ -0,0 +1,129 @@
+-- CometBench-DS query 5 derived from TPC-DS query 5 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ssr as
+ (select s_store_id,
+        sum(sales_price) as sales,
+        sum(profit) as profit,
+        sum(return_amt) as returns,
+        sum(net_loss) as profit_loss
+ from
+  ( select  ss_store_sk as store_sk,
+            ss_sold_date_sk  as date_sk,
+            ss_ext_sales_price as sales_price,
+            ss_net_profit as profit,
+            cast(0 as decimal(7,2)) as return_amt,
+            cast(0 as decimal(7,2)) as net_loss
+    from store_sales
+    union all
+    select sr_store_sk as store_sk,
+           sr_returned_date_sk as date_sk,
+           cast(0 as decimal(7,2)) as sales_price,
+           cast(0 as decimal(7,2)) as profit,
+           sr_return_amt as return_amt,
+           sr_net_loss as net_loss
+    from store_returns
+   ) salesreturns,
+     date_dim,
+     store
+ where date_sk = d_date_sk
+       and d_date between cast('2001-08-04' as date) 
+                  and (cast('2001-08-04' as date) +  14 days)
+       and store_sk = s_store_sk
+ group by s_store_id)
+ ,
+ csr as
+ (select cp_catalog_page_id,
+        sum(sales_price) as sales,
+        sum(profit) as profit,
+        sum(return_amt) as returns,
+        sum(net_loss) as profit_loss
+ from
+  ( select  cs_catalog_page_sk as page_sk,
+            cs_sold_date_sk  as date_sk,
+            cs_ext_sales_price as sales_price,
+            cs_net_profit as profit,
+            cast(0 as decimal(7,2)) as return_amt,
+            cast(0 as decimal(7,2)) as net_loss
+    from catalog_sales
+    union all
+    select cr_catalog_page_sk as page_sk,
+           cr_returned_date_sk as date_sk,
+           cast(0 as decimal(7,2)) as sales_price,
+           cast(0 as decimal(7,2)) as profit,
+           cr_return_amount as return_amt,
+           cr_net_loss as net_loss
+    from catalog_returns
+   ) salesreturns,
+     date_dim,
+     catalog_page
+ where date_sk = d_date_sk
+       and d_date between cast('2001-08-04' as date)
+                  and (cast('2001-08-04' as date) +  14 days)
+       and page_sk = cp_catalog_page_sk
+ group by cp_catalog_page_id)
+ ,
+ wsr as
+ (select web_site_id,
+        sum(sales_price) as sales,
+        sum(profit) as profit,
+        sum(return_amt) as returns,
+        sum(net_loss) as profit_loss
+ from
+  ( select  ws_web_site_sk as wsr_web_site_sk,
+            ws_sold_date_sk  as date_sk,
+            ws_ext_sales_price as sales_price,
+            ws_net_profit as profit,
+            cast(0 as decimal(7,2)) as return_amt,
+            cast(0 as decimal(7,2)) as net_loss
+    from web_sales
+    union all
+    select ws_web_site_sk as wsr_web_site_sk,
+           wr_returned_date_sk as date_sk,
+           cast(0 as decimal(7,2)) as sales_price,
+           cast(0 as decimal(7,2)) as profit,
+           wr_return_amt as return_amt,
+           wr_net_loss as net_loss
+    from web_returns left outer join web_sales on
+         ( wr_item_sk = ws_item_sk
+           and wr_order_number = ws_order_number)
+   ) salesreturns,
+     date_dim,
+     web_site
+ where date_sk = d_date_sk
+       and d_date between cast('2001-08-04' as date)
+                  and (cast('2001-08-04' as date) +  14 days)
+       and wsr_web_site_sk = web_site_sk
+ group by web_site_id)
+  select  channel
+        , id
+        , sum(sales) as sales
+        , sum(returns) as returns
+        , sum(profit) as profit
+ from 
+ (select 'store channel' as channel
+        , 'store' || s_store_id as id
+        , sales
+        , returns
+        , (profit - profit_loss) as profit
+ from   ssr
+ union all
+ select 'catalog channel' as channel
+        , 'catalog_page' || cp_catalog_page_id as id
+        , sales
+        , returns
+        , (profit - profit_loss) as profit
+ from  csr
+ union all
+ select 'web channel' as channel
+        , 'web_site' || web_site_id as id
+        , sales
+        , returns
+        , (profit - profit_loss) as profit
+ from   wsr
+ ) x
+ group by rollup (channel, id)
+ order by channel
+         ,id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q50.sql b/benchmarks/tpc/queries/tpcds/q50.sql
new file mode 100644
index 0000000000..0fd43d1130
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q50.sql
@@ -0,0 +1,60 @@
+-- CometBench-DS query 50 derived from TPC-DS query 50 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   s_store_name
+  ,s_company_id
+  ,s_street_number
+  ,s_street_name
+  ,s_street_type
+  ,s_suite_number
+  ,s_city
+  ,s_county
+  ,s_state
+  ,s_zip
+  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end)  as "30 days" 
+  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and 
+                 (sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end )  as "31-60 days" 
+  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and 
+                 (sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end)  as "61-90 days" 
+  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and
+                 (sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end)  as "91-120 days" 
+  ,sum(case when (sr_returned_date_sk - ss_sold_date_sk  > 120) then 1 else 0 end)  as ">120 days" 
+from
+   store_sales
+  ,store_returns
+  ,store
+  ,date_dim d1
+  ,date_dim d2
+where
+    d2.d_year = 2002
+and d2.d_moy  = 8
+and ss_ticket_number = sr_ticket_number
+and ss_item_sk = sr_item_sk
+and ss_sold_date_sk   = d1.d_date_sk
+and sr_returned_date_sk   = d2.d_date_sk
+and ss_customer_sk = sr_customer_sk
+and ss_store_sk = s_store_sk
+group by
+   s_store_name
+  ,s_company_id
+  ,s_street_number
+  ,s_street_name
+  ,s_street_type
+  ,s_suite_number
+  ,s_city
+  ,s_county
+  ,s_state
+  ,s_zip
+order by s_store_name
+        ,s_company_id
+        ,s_street_number
+        ,s_street_name
+        ,s_street_type
+        ,s_suite_number
+        ,s_city
+        ,s_county
+        ,s_state
+        ,s_zip
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q51.sql b/benchmarks/tpc/queries/tpcds/q51.sql
new file mode 100644
index 0000000000..55ed6c462f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q51.sql
@@ -0,0 +1,46 @@
+-- CometBench-DS query 51 derived from TPC-DS query 51 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+WITH web_v1 as (
+select
+  ws_item_sk item_sk, d_date,
+  sum(sum(ws_sales_price))
+      over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
+from web_sales
+    ,date_dim
+where ws_sold_date_sk=d_date_sk
+  and d_month_seq between 1215 and 1215+11
+  and ws_item_sk is not NULL
+group by ws_item_sk, d_date),
+store_v1 as (
+select
+  ss_item_sk item_sk, d_date,
+  sum(sum(ss_sales_price))
+      over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
+from store_sales
+    ,date_dim
+where ss_sold_date_sk=d_date_sk
+  and d_month_seq between 1215 and 1215+11
+  and ss_item_sk is not NULL
+group by ss_item_sk, d_date)
+ select  *
+from (select item_sk
+     ,d_date
+     ,web_sales
+     ,store_sales
+     ,max(web_sales)
+         over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
+     ,max(store_sales)
+         over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
+     from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
+                 ,case when web.d_date is not null then web.d_date else store.d_date end d_date
+                 ,web.cume_sales web_sales
+                 ,store.cume_sales store_sales
+           from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
+                                                          and web.d_date = store.d_date)
+          )x )y
+where web_cumulative > store_cumulative
+order by item_sk
+        ,d_date
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q52.sql b/benchmarks/tpc/queries/tpcds/q52.sql
new file mode 100644
index 0000000000..fc133fa7a5
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q52.sql
@@ -0,0 +1,23 @@
+-- CometBench-DS query 52 derived from TPC-DS query 52 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  dt.d_year
+ 	,item.i_brand_id brand_id
+ 	,item.i_brand brand
+ 	,sum(ss_ext_sales_price) ext_price
+ from date_dim dt
+     ,store_sales
+     ,item
+ where dt.d_date_sk = store_sales.ss_sold_date_sk
+    and store_sales.ss_item_sk = item.i_item_sk
+    and item.i_manager_id = 1
+    and dt.d_moy=11
+    and dt.d_year=2000
+ group by dt.d_year
+ 	,item.i_brand
+ 	,item.i_brand_id
+ order by dt.d_year
+ 	,ext_price desc
+ 	,brand_id
+ LIMIT 100 ;
+
diff --git a/benchmarks/tpc/queries/tpcds/q53.sql b/benchmarks/tpc/queries/tpcds/q53.sql
new file mode 100644
index 0000000000..cff50f65e8
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q53.sql
@@ -0,0 +1,29 @@
+-- CometBench-DS query 53 derived from TPC-DS query 53 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  * from 
+(select i_manufact_id,
+sum(ss_sales_price) sum_sales,
+avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales
+from item, store_sales, date_dim, store
+where ss_item_sk = i_item_sk and
+ss_sold_date_sk = d_date_sk and
+ss_store_sk = s_store_sk and
+d_month_seq in (1197,1197+1,1197+2,1197+3,1197+4,1197+5,1197+6,1197+7,1197+8,1197+9,1197+10,1197+11) and
+((i_category in ('Books','Children','Electronics') and
+i_class in ('personal','portable','reference','self-help') and
+i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
+		'exportiunivamalg #9','scholaramalgamalg #9'))
+or(i_category in ('Women','Music','Men') and
+i_class in ('accessories','classical','fragrances','pants') and
+i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
+		'importoamalg #1')))
+group by i_manufact_id, d_qoy ) tmp1
+where case when avg_quarterly_sales > 0 
+	then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales 
+	else null end > 0.1
+order by avg_quarterly_sales,
+	 sum_sales,
+	 i_manufact_id
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q54.sql b/benchmarks/tpc/queries/tpcds/q54.sql
new file mode 100644
index 0000000000..1316ba2399
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q54.sql
@@ -0,0 +1,57 @@
+-- CometBench-DS query 54 derived from TPC-DS query 54 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with my_customers as (
+ select distinct c_customer_sk
+        , c_current_addr_sk
+ from   
+        ( select cs_sold_date_sk sold_date_sk,
+                 cs_bill_customer_sk customer_sk,
+                 cs_item_sk item_sk
+          from   catalog_sales
+          union all
+          select ws_sold_date_sk sold_date_sk,
+                 ws_bill_customer_sk customer_sk,
+                 ws_item_sk item_sk
+          from   web_sales
+         ) cs_or_ws_sales,
+         item,
+         date_dim,
+         customer
+ where   sold_date_sk = d_date_sk
+         and item_sk = i_item_sk
+         and i_category = 'Men'
+         and i_class = 'shirts'
+         and c_customer_sk = cs_or_ws_sales.customer_sk
+         and d_moy = 4
+         and d_year = 1998
+ )
+ , my_revenue as (
+ select c_customer_sk,
+        sum(ss_ext_sales_price) as revenue
+ from   my_customers,
+        store_sales,
+        customer_address,
+        store,
+        date_dim
+ where  c_current_addr_sk = ca_address_sk
+        and ca_county = s_county
+        and ca_state = s_state
+        and ss_sold_date_sk = d_date_sk
+        and c_customer_sk = ss_customer_sk
+        and d_month_seq between (select distinct d_month_seq+1
+                                 from   date_dim where d_year = 1998 and d_moy = 4)
+                           and  (select distinct d_month_seq+3
+                                 from   date_dim where d_year = 1998 and d_moy = 4)
+ group by c_customer_sk
+ )
+ , segments as
+ (select cast((revenue/50) as int) as segment
+  from   my_revenue
+ )
+  select  segment, count(*) as num_customers, segment*50 as segment_base
+ from segments
+ group by segment
+ order by segment, num_customers
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q55.sql b/benchmarks/tpc/queries/tpcds/q55.sql
new file mode 100644
index 0000000000..b448279ded
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q55.sql
@@ -0,0 +1,15 @@
+-- CometBench-DS query 55 derived from TPC-DS query 55 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_brand_id brand_id, i_brand brand,
+ 	sum(ss_ext_sales_price) ext_price
+ from date_dim, store_sales, item
+ where d_date_sk = ss_sold_date_sk
+ 	and ss_item_sk = i_item_sk
+ 	and i_manager_id=20
+ 	and d_moy=12
+ 	and d_year=1998
+ group by i_brand, i_brand_id
+ order by ext_price desc, i_brand_id
+ LIMIT 100 ;
+
diff --git a/benchmarks/tpc/queries/tpcds/q56.sql b/benchmarks/tpc/queries/tpcds/q56.sql
new file mode 100644
index 0000000000..4fb34dd3e4
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q56.sql
@@ -0,0 +1,70 @@
+-- CometBench-DS query 56 derived from TPC-DS query 56 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ss as (
+ select i_item_id,sum(ss_ext_sales_price) total_sales
+ from
+ 	store_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where i_item_id in (select
+     i_item_id
+from item
+where i_color in ('powder','goldenrod','bisque'))
+ and     ss_item_sk              = i_item_sk
+ and     ss_sold_date_sk         = d_date_sk
+ and     d_year                  = 1998
+ and     d_moy                   = 5
+ and     ss_addr_sk              = ca_address_sk
+ and     ca_gmt_offset           = -5 
+ group by i_item_id),
+ cs as (
+ select i_item_id,sum(cs_ext_sales_price) total_sales
+ from
+ 	catalog_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_item_id               in (select
+  i_item_id
+from item
+where i_color in ('powder','goldenrod','bisque'))
+ and     cs_item_sk              = i_item_sk
+ and     cs_sold_date_sk         = d_date_sk
+ and     d_year                  = 1998
+ and     d_moy                   = 5
+ and     cs_bill_addr_sk         = ca_address_sk
+ and     ca_gmt_offset           = -5 
+ group by i_item_id),
+ ws as (
+ select i_item_id,sum(ws_ext_sales_price) total_sales
+ from
+ 	web_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_item_id               in (select
+  i_item_id
+from item
+where i_color in ('powder','goldenrod','bisque'))
+ and     ws_item_sk              = i_item_sk
+ and     ws_sold_date_sk         = d_date_sk
+ and     d_year                  = 1998
+ and     d_moy                   = 5
+ and     ws_bill_addr_sk         = ca_address_sk
+ and     ca_gmt_offset           = -5
+ group by i_item_id)
+  select  i_item_id ,sum(total_sales) total_sales
+ from  (select * from ss 
+        union all
+        select * from cs 
+        union all
+        select * from ws) tmp1
+ group by i_item_id
+ order by total_sales,
+          i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q57.sql b/benchmarks/tpc/queries/tpcds/q57.sql
new file mode 100644
index 0000000000..3dc568848a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q57.sql
@@ -0,0 +1,49 @@
+-- CometBench-DS query 57 derived from TPC-DS query 57 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with v1 as(
+ select i_category, i_brand,
+        cc_name,
+        d_year, d_moy,
+        sum(cs_sales_price) sum_sales,
+        avg(sum(cs_sales_price)) over
+          (partition by i_category, i_brand,
+                     cc_name, d_year)
+          avg_monthly_sales,
+        rank() over
+          (partition by i_category, i_brand,
+                     cc_name
+           order by d_year, d_moy) rn
+ from item, catalog_sales, date_dim, call_center
+ where cs_item_sk = i_item_sk and
+       cs_sold_date_sk = d_date_sk and
+       cc_call_center_sk= cs_call_center_sk and
+       (
+         d_year = 2000 or
+         ( d_year = 2000-1 and d_moy =12) or
+         ( d_year = 2000+1 and d_moy =1)
+       )
+ group by i_category, i_brand,
+          cc_name , d_year, d_moy),
+ v2 as(
+ select v1.cc_name
+        ,v1.d_year, v1.d_moy
+        ,v1.avg_monthly_sales
+        ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
+ from v1, v1 v1_lag, v1 v1_lead
+ where v1.i_category = v1_lag.i_category and
+       v1.i_category = v1_lead.i_category and
+       v1.i_brand = v1_lag.i_brand and
+       v1.i_brand = v1_lead.i_brand and
+       v1. cc_name = v1_lag. cc_name and
+       v1. cc_name = v1_lead. cc_name and
+       v1.rn = v1_lag.rn + 1 and
+       v1.rn = v1_lead.rn - 1)
+  select  *
+ from v2
+ where  d_year = 2000 and
+        avg_monthly_sales > 0 and
+        case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+ order by sum_sales - avg_monthly_sales, psum
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q58.sql b/benchmarks/tpc/queries/tpcds/q58.sql
new file mode 100644
index 0000000000..3243c0ac8a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q58.sql
@@ -0,0 +1,66 @@
+-- CometBench-DS query 58 derived from TPC-DS query 58 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ss_items as
+ (select i_item_id item_id
+        ,sum(ss_ext_sales_price) ss_item_rev 
+ from store_sales
+     ,item
+     ,date_dim
+ where ss_item_sk = i_item_sk
+   and d_date in (select d_date
+                  from date_dim
+                  where d_week_seq = (select d_week_seq 
+                                      from date_dim
+                                      where d_date = '2000-02-12'))
+   and ss_sold_date_sk   = d_date_sk
+ group by i_item_id),
+ cs_items as
+ (select i_item_id item_id
+        ,sum(cs_ext_sales_price) cs_item_rev
+  from catalog_sales
+      ,item
+      ,date_dim
+ where cs_item_sk = i_item_sk
+  and  d_date in (select d_date
+                  from date_dim
+                  where d_week_seq = (select d_week_seq 
+                                      from date_dim
+                                      where d_date = '2000-02-12'))
+  and  cs_sold_date_sk = d_date_sk
+ group by i_item_id),
+ ws_items as
+ (select i_item_id item_id
+        ,sum(ws_ext_sales_price) ws_item_rev
+  from web_sales
+      ,item
+      ,date_dim
+ where ws_item_sk = i_item_sk
+  and  d_date in (select d_date
+                  from date_dim
+                  where d_week_seq =(select d_week_seq 
+                                     from date_dim
+                                     where d_date = '2000-02-12'))
+  and ws_sold_date_sk   = d_date_sk
+ group by i_item_id)
+  select  ss_items.item_id
+       ,ss_item_rev
+       ,ss_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ss_dev
+       ,cs_item_rev
+       ,cs_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 cs_dev
+       ,ws_item_rev
+       ,ws_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ws_dev
+       ,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
+ from ss_items,cs_items,ws_items
+ where ss_items.item_id=cs_items.item_id
+   and ss_items.item_id=ws_items.item_id 
+   and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+   and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+   and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+   and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
+   and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
+   and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
+ order by item_id
+         ,ss_item_rev
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q59.sql b/benchmarks/tpc/queries/tpcds/q59.sql
new file mode 100644
index 0000000000..cd92847be6
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q59.sql
@@ -0,0 +1,45 @@
+-- CometBench-DS query 59 derived from TPC-DS query 59 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with wss as 
+ (select d_week_seq,
+        ss_store_sk,
+        sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
+        sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
+        sum(case when (d_day_name='Tuesday') then ss_sales_price else  null end) tue_sales,
+        sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
+        sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
+        sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
+        sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
+ from store_sales,date_dim
+ where d_date_sk = ss_sold_date_sk
+ group by d_week_seq,ss_store_sk
+ )
+  select  s_store_name1,s_store_id1,d_week_seq1
+       ,sun_sales1/sun_sales2,mon_sales1/mon_sales2
+       ,tue_sales1/tue_sales2,wed_sales1/wed_sales2,thu_sales1/thu_sales2
+       ,fri_sales1/fri_sales2,sat_sales1/sat_sales2
+ from
+ (select s_store_name s_store_name1,wss.d_week_seq d_week_seq1
+        ,s_store_id s_store_id1,sun_sales sun_sales1
+        ,mon_sales mon_sales1,tue_sales tue_sales1
+        ,wed_sales wed_sales1,thu_sales thu_sales1
+        ,fri_sales fri_sales1,sat_sales sat_sales1
+  from wss,store,date_dim d
+  where d.d_week_seq = wss.d_week_seq and
+        ss_store_sk = s_store_sk and 
+        d_month_seq between 1206 and 1206 + 11) y,
+ (select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
+        ,s_store_id s_store_id2,sun_sales sun_sales2
+        ,mon_sales mon_sales2,tue_sales tue_sales2
+        ,wed_sales wed_sales2,thu_sales thu_sales2
+        ,fri_sales fri_sales2,sat_sales sat_sales2
+  from wss,store,date_dim d
+  where d.d_week_seq = wss.d_week_seq and
+        ss_store_sk = s_store_sk and 
+        d_month_seq between 1206+ 12 and 1206 + 23) x
+ where s_store_id1=s_store_id2
+   and d_week_seq1=d_week_seq2-52
+ order by s_store_name1,s_store_id1,d_week_seq1
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q6.sql b/benchmarks/tpc/queries/tpcds/q6.sql
new file mode 100644
index 0000000000..9e5a5ba8e3
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q6.sql
@@ -0,0 +1,27 @@
+-- CometBench-DS query 6 derived from TPC-DS query 6 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  a.ca_state state, count(*) cnt
+ from customer_address a
+     ,customer c
+     ,store_sales s
+     ,date_dim d
+     ,item i
+ where       a.ca_address_sk = c.c_current_addr_sk
+ 	and c.c_customer_sk = s.ss_customer_sk
+ 	and s.ss_sold_date_sk = d.d_date_sk
+ 	and s.ss_item_sk = i.i_item_sk
+ 	and d.d_month_seq = 
+ 	     (select distinct (d_month_seq)
+ 	      from date_dim
+               where d_year = 1998
+ 	        and d_moy = 3 )
+ 	and i.i_current_price > 1.2 * 
+             (select avg(j.i_current_price) 
+ 	     from item j 
+ 	     where j.i_category = i.i_category)
+ group by a.ca_state
+ having count(*) >= 10
+ order by cnt, a.ca_state 
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q60.sql b/benchmarks/tpc/queries/tpcds/q60.sql
new file mode 100644
index 0000000000..cf1f885524
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q60.sql
@@ -0,0 +1,79 @@
+-- CometBench-DS query 60 derived from TPC-DS query 60 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ss as (
+ select
+          i_item_id,sum(ss_ext_sales_price) total_sales
+ from
+ 	store_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_item_id in (select
+  i_item_id
+from
+ item
+where i_category in ('Shoes'))
+ and     ss_item_sk              = i_item_sk
+ and     ss_sold_date_sk         = d_date_sk
+ and     d_year                  = 2001
+ and     d_moy                   = 10
+ and     ss_addr_sk              = ca_address_sk
+ and     ca_gmt_offset           = -6 
+ group by i_item_id),
+ cs as (
+ select
+          i_item_id,sum(cs_ext_sales_price) total_sales
+ from
+ 	catalog_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_item_id               in (select
+  i_item_id
+from
+ item
+where i_category in ('Shoes'))
+ and     cs_item_sk              = i_item_sk
+ and     cs_sold_date_sk         = d_date_sk
+ and     d_year                  = 2001
+ and     d_moy                   = 10
+ and     cs_bill_addr_sk         = ca_address_sk
+ and     ca_gmt_offset           = -6 
+ group by i_item_id),
+ ws as (
+ select
+          i_item_id,sum(ws_ext_sales_price) total_sales
+ from
+ 	web_sales,
+ 	date_dim,
+         customer_address,
+         item
+ where
+         i_item_id               in (select
+  i_item_id
+from
+ item
+where i_category in ('Shoes'))
+ and     ws_item_sk              = i_item_sk
+ and     ws_sold_date_sk         = d_date_sk
+ and     d_year                  = 2001
+ and     d_moy                   = 10
+ and     ws_bill_addr_sk         = ca_address_sk
+ and     ca_gmt_offset           = -6
+ group by i_item_id)
+  select   
+  i_item_id
+,sum(total_sales) total_sales
+ from  (select * from ss 
+        union all
+        select * from cs 
+        union all
+        select * from ws) tmp1
+ group by i_item_id
+ order by i_item_id
+      ,total_sales
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q61.sql b/benchmarks/tpc/queries/tpcds/q61.sql
new file mode 100644
index 0000000000..ef2e89b971
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q61.sql
@@ -0,0 +1,45 @@
+-- CometBench-DS query 61 derived from TPC-DS query 61 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  promotions,total,cast(promotions as decimal(15,4))/cast(total as decimal(15,4))*100
+from
+  (select sum(ss_ext_sales_price) promotions
+   from  store_sales
+        ,store
+        ,promotion
+        ,date_dim
+        ,customer
+        ,customer_address 
+        ,item
+   where ss_sold_date_sk = d_date_sk
+   and   ss_store_sk = s_store_sk
+   and   ss_promo_sk = p_promo_sk
+   and   ss_customer_sk= c_customer_sk
+   and   ca_address_sk = c_current_addr_sk
+   and   ss_item_sk = i_item_sk 
+   and   ca_gmt_offset = -6
+   and   i_category = 'Sports'
+   and   (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y')
+   and   s_gmt_offset = -6
+   and   d_year = 2002
+   and   d_moy  = 11) promotional_sales,
+  (select sum(ss_ext_sales_price) total
+   from  store_sales
+        ,store
+        ,date_dim
+        ,customer
+        ,customer_address
+        ,item
+   where ss_sold_date_sk = d_date_sk
+   and   ss_store_sk = s_store_sk
+   and   ss_customer_sk= c_customer_sk
+   and   ca_address_sk = c_current_addr_sk
+   and   ss_item_sk = i_item_sk
+   and   ca_gmt_offset = -6
+   and   i_category = 'Sports'
+   and   s_gmt_offset = -6
+   and   d_year = 2002
+   and   d_moy  = 11) all_sales
+order by promotions, total
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q62.sql b/benchmarks/tpc/queries/tpcds/q62.sql
new file mode 100644
index 0000000000..15a0815270
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q62.sql
@@ -0,0 +1,36 @@
+-- CometBench-DS query 62 derived from TPC-DS query 62 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   substr(w_warehouse_name,1,20)
+  ,sm_type
+  ,web_name
+  ,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end)  as "30 days" 
+  ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and 
+                 (ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end )  as "31-60 days" 
+  ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and 
+                 (ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end)  as "61-90 days" 
+  ,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and
+                 (ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end)  as "91-120 days" 
+  ,sum(case when (ws_ship_date_sk - ws_sold_date_sk  > 120) then 1 else 0 end)  as ">120 days" 
+from
+   web_sales
+  ,warehouse
+  ,ship_mode
+  ,web_site
+  ,date_dim
+where
+    d_month_seq between 1217 and 1217 + 11
+and ws_ship_date_sk   = d_date_sk
+and ws_warehouse_sk   = w_warehouse_sk
+and ws_ship_mode_sk   = sm_ship_mode_sk
+and ws_web_site_sk    = web_site_sk
+group by
+   substr(w_warehouse_name,1,20)
+  ,sm_type
+  ,web_name
+order by substr(w_warehouse_name,1,20)
+        ,sm_type
+       ,web_name
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q63.sql b/benchmarks/tpc/queries/tpcds/q63.sql
new file mode 100644
index 0000000000..e903fca6a0
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q63.sql
@@ -0,0 +1,30 @@
+-- CometBench-DS query 63 derived from TPC-DS query 63 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  * 
+from (select i_manager_id
+             ,sum(ss_sales_price) sum_sales
+             ,avg(sum(ss_sales_price)) over (partition by i_manager_id) avg_monthly_sales
+      from item
+          ,store_sales
+          ,date_dim
+          ,store
+      where ss_item_sk = i_item_sk
+        and ss_sold_date_sk = d_date_sk
+        and ss_store_sk = s_store_sk
+        and d_month_seq in (1181,1181+1,1181+2,1181+3,1181+4,1181+5,1181+6,1181+7,1181+8,1181+9,1181+10,1181+11)
+        and ((    i_category in ('Books','Children','Electronics')
+              and i_class in ('personal','portable','reference','self-help')
+              and i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
+		                  'exportiunivamalg #9','scholaramalgamalg #9'))
+           or(    i_category in ('Women','Music','Men')
+              and i_class in ('accessories','classical','fragrances','pants')
+              and i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
+		                 'importoamalg #1')))
+group by i_manager_id, d_moy) tmp1
+where case when avg_monthly_sales > 0 then abs (sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
+order by i_manager_id
+        ,avg_monthly_sales
+        ,sum_sales
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q64.sql b/benchmarks/tpc/queries/tpcds/q64.sql
new file mode 100644
index 0000000000..bc8f1676fc
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q64.sql
@@ -0,0 +1,122 @@
+-- CometBench-DS query 64 derived from TPC-DS query 64 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with cs_ui as
+ (select cs_item_sk
+        ,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund
+  from catalog_sales
+      ,catalog_returns
+  where cs_item_sk = cr_item_sk
+    and cs_order_number = cr_order_number
+  group by cs_item_sk
+  having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)),
+cross_sales as
+ (select i_product_name product_name
+     ,i_item_sk item_sk
+     ,s_store_name store_name
+     ,s_zip store_zip
+     ,ad1.ca_street_number b_street_number
+     ,ad1.ca_street_name b_street_name
+     ,ad1.ca_city b_city
+     ,ad1.ca_zip b_zip
+     ,ad2.ca_street_number c_street_number
+     ,ad2.ca_street_name c_street_name
+     ,ad2.ca_city c_city
+     ,ad2.ca_zip c_zip
+     ,d1.d_year as syear
+     ,d2.d_year as fsyear
+     ,d3.d_year s2year
+     ,count(*) cnt
+     ,sum(ss_wholesale_cost) s1
+     ,sum(ss_list_price) s2
+     ,sum(ss_coupon_amt) s3
+  FROM   store_sales
+        ,store_returns
+        ,cs_ui
+        ,date_dim d1
+        ,date_dim d2
+        ,date_dim d3
+        ,store
+        ,customer
+        ,customer_demographics cd1
+        ,customer_demographics cd2
+        ,promotion
+        ,household_demographics hd1
+        ,household_demographics hd2
+        ,customer_address ad1
+        ,customer_address ad2
+        ,income_band ib1
+        ,income_band ib2
+        ,item
+  WHERE  ss_store_sk = s_store_sk AND
+         ss_sold_date_sk = d1.d_date_sk AND
+         ss_customer_sk = c_customer_sk AND
+         ss_cdemo_sk= cd1.cd_demo_sk AND
+         ss_hdemo_sk = hd1.hd_demo_sk AND
+         ss_addr_sk = ad1.ca_address_sk and
+         ss_item_sk = i_item_sk and
+         ss_item_sk = sr_item_sk and
+         ss_ticket_number = sr_ticket_number and
+         ss_item_sk = cs_ui.cs_item_sk and
+         c_current_cdemo_sk = cd2.cd_demo_sk AND
+         c_current_hdemo_sk = hd2.hd_demo_sk AND
+         c_current_addr_sk = ad2.ca_address_sk and
+         c_first_sales_date_sk = d2.d_date_sk and
+         c_first_shipto_date_sk = d3.d_date_sk and
+         ss_promo_sk = p_promo_sk and
+         hd1.hd_income_band_sk = ib1.ib_income_band_sk and
+         hd2.hd_income_band_sk = ib2.ib_income_band_sk and
+         cd1.cd_marital_status <> cd2.cd_marital_status and
+         i_color in ('light','cyan','burnished','green','almond','smoke') and
+         i_current_price between 22 and 22 + 10 and
+         i_current_price between 22 + 1 and 22 + 15
+group by i_product_name
+       ,i_item_sk
+       ,s_store_name
+       ,s_zip
+       ,ad1.ca_street_number
+       ,ad1.ca_street_name
+       ,ad1.ca_city
+       ,ad1.ca_zip
+       ,ad2.ca_street_number
+       ,ad2.ca_street_name
+       ,ad2.ca_city
+       ,ad2.ca_zip
+       ,d1.d_year
+       ,d2.d_year
+       ,d3.d_year
+)
+select cs1.product_name
+     ,cs1.store_name
+     ,cs1.store_zip
+     ,cs1.b_street_number
+     ,cs1.b_street_name
+     ,cs1.b_city
+     ,cs1.b_zip
+     ,cs1.c_street_number
+     ,cs1.c_street_name
+     ,cs1.c_city
+     ,cs1.c_zip
+     ,cs1.syear
+     ,cs1.cnt
+     ,cs1.s1 as s11
+     ,cs1.s2 as s21
+     ,cs1.s3 as s31
+     ,cs2.s1 as s12
+     ,cs2.s2 as s22
+     ,cs2.s3 as s32
+     ,cs2.syear
+     ,cs2.cnt
+from cross_sales cs1,cross_sales cs2
+where cs1.item_sk=cs2.item_sk and
+     cs1.syear = 2001 and
+     cs2.syear = 2001 + 1 and
+     cs2.cnt <= cs1.cnt and
+     cs1.store_name = cs2.store_name and
+     cs1.store_zip = cs2.store_zip
+order by cs1.product_name
+       ,cs1.store_name
+       ,cs2.cnt
+       ,cs1.s1
+       ,cs2.s1;
+
diff --git a/benchmarks/tpc/queries/tpcds/q65.sql b/benchmarks/tpc/queries/tpcds/q65.sql
new file mode 100644
index 0000000000..d00f247199
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q65.sql
@@ -0,0 +1,30 @@
+-- CometBench-DS query 65 derived from TPC-DS query 65 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select 
+	s_store_name,
+	i_item_desc,
+	sc.revenue,
+	i_current_price,
+	i_wholesale_cost,
+	i_brand
+ from store, item,
+     (select ss_store_sk, avg(revenue) as ave
+ 	from
+ 	    (select  ss_store_sk, ss_item_sk, 
+ 		     sum(ss_sales_price) as revenue
+ 		from store_sales, date_dim
+ 		where ss_sold_date_sk = d_date_sk and d_month_seq between 1186 and 1186+11
+ 		group by ss_store_sk, ss_item_sk) sa
+ 	group by ss_store_sk) sb,
+     (select  ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue
+ 	from store_sales, date_dim
+ 	where ss_sold_date_sk = d_date_sk and d_month_seq between 1186 and 1186+11
+ 	group by ss_store_sk, ss_item_sk) sc
+ where sb.ss_store_sk = sc.ss_store_sk and 
+       sc.revenue <= 0.1 * sb.ave and
+       s_store_sk = sc.ss_store_sk and
+       i_item_sk = sc.ss_item_sk
+ order by s_store_name, i_item_desc
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q66.sql b/benchmarks/tpc/queries/tpcds/q66.sql
new file mode 100644
index 0000000000..9fb527c2d5
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q66.sql
@@ -0,0 +1,221 @@
+-- CometBench-DS query 66 derived from TPC-DS query 66 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select   
+         w_warehouse_name
+ 	,w_warehouse_sq_ft
+ 	,w_city
+ 	,w_county
+ 	,w_state
+ 	,w_country
+        ,ship_carriers
+        ,year
+ 	,sum(jan_sales) as jan_sales
+ 	,sum(feb_sales) as feb_sales
+ 	,sum(mar_sales) as mar_sales
+ 	,sum(apr_sales) as apr_sales
+ 	,sum(may_sales) as may_sales
+ 	,sum(jun_sales) as jun_sales
+ 	,sum(jul_sales) as jul_sales
+ 	,sum(aug_sales) as aug_sales
+ 	,sum(sep_sales) as sep_sales
+ 	,sum(oct_sales) as oct_sales
+ 	,sum(nov_sales) as nov_sales
+ 	,sum(dec_sales) as dec_sales
+ 	,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
+ 	,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
+ 	,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
+ 	,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
+ 	,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
+ 	,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
+ 	,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
+ 	,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
+ 	,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
+ 	,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
+ 	,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
+ 	,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
+ 	,sum(jan_net) as jan_net
+ 	,sum(feb_net) as feb_net
+ 	,sum(mar_net) as mar_net
+ 	,sum(apr_net) as apr_net
+ 	,sum(may_net) as may_net
+ 	,sum(jun_net) as jun_net
+ 	,sum(jul_net) as jul_net
+ 	,sum(aug_net) as aug_net
+ 	,sum(sep_net) as sep_net
+ 	,sum(oct_net) as oct_net
+ 	,sum(nov_net) as nov_net
+ 	,sum(dec_net) as dec_net
+ from (
+     select 
+ 	w_warehouse_name
+ 	,w_warehouse_sq_ft
+ 	,w_city
+ 	,w_county
+ 	,w_state
+ 	,w_country
+ 	,'FEDEX' || ',' || 'GERMA' as ship_carriers
+       ,d_year as year
+ 	,sum(case when d_moy = 1 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as jan_sales
+ 	,sum(case when d_moy = 2 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as feb_sales
+ 	,sum(case when d_moy = 3 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as mar_sales
+ 	,sum(case when d_moy = 4 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as apr_sales
+ 	,sum(case when d_moy = 5 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as may_sales
+ 	,sum(case when d_moy = 6 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as jun_sales
+ 	,sum(case when d_moy = 7 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as jul_sales
+ 	,sum(case when d_moy = 8 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as aug_sales
+ 	,sum(case when d_moy = 9 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as sep_sales
+ 	,sum(case when d_moy = 10 
+ 		then ws_ext_list_price* ws_quantity else 0 end) as oct_sales
+ 	,sum(case when d_moy = 11
+ 		then ws_ext_list_price* ws_quantity else 0 end) as nov_sales
+ 	,sum(case when d_moy = 12
+ 		then ws_ext_list_price* ws_quantity else 0 end) as dec_sales
+ 	,sum(case when d_moy = 1 
+ 		then ws_net_profit * ws_quantity else 0 end) as jan_net
+ 	,sum(case when d_moy = 2
+ 		then ws_net_profit * ws_quantity else 0 end) as feb_net
+ 	,sum(case when d_moy = 3 
+ 		then ws_net_profit * ws_quantity else 0 end) as mar_net
+ 	,sum(case when d_moy = 4 
+ 		then ws_net_profit * ws_quantity else 0 end) as apr_net
+ 	,sum(case when d_moy = 5 
+ 		then ws_net_profit * ws_quantity else 0 end) as may_net
+ 	,sum(case when d_moy = 6 
+ 		then ws_net_profit * ws_quantity else 0 end) as jun_net
+ 	,sum(case when d_moy = 7 
+ 		then ws_net_profit * ws_quantity else 0 end) as jul_net
+ 	,sum(case when d_moy = 8 
+ 		then ws_net_profit * ws_quantity else 0 end) as aug_net
+ 	,sum(case when d_moy = 9 
+ 		then ws_net_profit * ws_quantity else 0 end) as sep_net
+ 	,sum(case when d_moy = 10 
+ 		then ws_net_profit * ws_quantity else 0 end) as oct_net
+ 	,sum(case when d_moy = 11
+ 		then ws_net_profit * ws_quantity else 0 end) as nov_net
+ 	,sum(case when d_moy = 12
+ 		then ws_net_profit * ws_quantity else 0 end) as dec_net
+     from
+          web_sales
+         ,warehouse
+         ,date_dim
+         ,time_dim
+ 	  ,ship_mode
+     where
+            ws_warehouse_sk =  w_warehouse_sk
+        and ws_sold_date_sk = d_date_sk
+        and ws_sold_time_sk = t_time_sk
+ 	and ws_ship_mode_sk = sm_ship_mode_sk
+        and d_year = 2001
+ 	and t_time between 19072 and 19072+28800 
+ 	and sm_carrier in ('FEDEX','GERMA')
+     group by 
+        w_warehouse_name
+ 	,w_warehouse_sq_ft
+ 	,w_city
+ 	,w_county
+ 	,w_state
+ 	,w_country
+       ,d_year
+ union all
+     select 
+ 	w_warehouse_name
+ 	,w_warehouse_sq_ft
+ 	,w_city
+ 	,w_county
+ 	,w_state
+ 	,w_country
+ 	,'FEDEX' || ',' || 'GERMA' as ship_carriers
+       ,d_year as year
+ 	,sum(case when d_moy = 1 
+ 		then cs_sales_price* cs_quantity else 0 end) as jan_sales
+ 	,sum(case when d_moy = 2 
+ 		then cs_sales_price* cs_quantity else 0 end) as feb_sales
+ 	,sum(case when d_moy = 3 
+ 		then cs_sales_price* cs_quantity else 0 end) as mar_sales
+ 	,sum(case when d_moy = 4 
+ 		then cs_sales_price* cs_quantity else 0 end) as apr_sales
+ 	,sum(case when d_moy = 5 
+ 		then cs_sales_price* cs_quantity else 0 end) as may_sales
+ 	,sum(case when d_moy = 6 
+ 		then cs_sales_price* cs_quantity else 0 end) as jun_sales
+ 	,sum(case when d_moy = 7 
+ 		then cs_sales_price* cs_quantity else 0 end) as jul_sales
+ 	,sum(case when d_moy = 8 
+ 		then cs_sales_price* cs_quantity else 0 end) as aug_sales
+ 	,sum(case when d_moy = 9 
+ 		then cs_sales_price* cs_quantity else 0 end) as sep_sales
+ 	,sum(case when d_moy = 10 
+ 		then cs_sales_price* cs_quantity else 0 end) as oct_sales
+ 	,sum(case when d_moy = 11
+ 		then cs_sales_price* cs_quantity else 0 end) as nov_sales
+ 	,sum(case when d_moy = 12
+ 		then cs_sales_price* cs_quantity else 0 end) as dec_sales
+ 	,sum(case when d_moy = 1 
+ 		then cs_net_paid * cs_quantity else 0 end) as jan_net
+ 	,sum(case when d_moy = 2 
+ 		then cs_net_paid * cs_quantity else 0 end) as feb_net
+ 	,sum(case when d_moy = 3 
+ 		then cs_net_paid * cs_quantity else 0 end) as mar_net
+ 	,sum(case when d_moy = 4 
+ 		then cs_net_paid * cs_quantity else 0 end) as apr_net
+ 	,sum(case when d_moy = 5 
+ 		then cs_net_paid * cs_quantity else 0 end) as may_net
+ 	,sum(case when d_moy = 6 
+ 		then cs_net_paid * cs_quantity else 0 end) as jun_net
+ 	,sum(case when d_moy = 7 
+ 		then cs_net_paid * cs_quantity else 0 end) as jul_net
+ 	,sum(case when d_moy = 8 
+ 		then cs_net_paid * cs_quantity else 0 end) as aug_net
+ 	,sum(case when d_moy = 9 
+ 		then cs_net_paid * cs_quantity else 0 end) as sep_net
+ 	,sum(case when d_moy = 10 
+ 		then cs_net_paid * cs_quantity else 0 end) as oct_net
+ 	,sum(case when d_moy = 11
+ 		then cs_net_paid * cs_quantity else 0 end) as nov_net
+ 	,sum(case when d_moy = 12
+ 		then cs_net_paid * cs_quantity else 0 end) as dec_net
+     from
+          catalog_sales
+         ,warehouse
+         ,date_dim
+         ,time_dim
+ 	 ,ship_mode
+     where
+            cs_warehouse_sk =  w_warehouse_sk
+        and cs_sold_date_sk = d_date_sk
+        and cs_sold_time_sk = t_time_sk
+ 	and cs_ship_mode_sk = sm_ship_mode_sk
+        and d_year = 2001
+ 	and t_time between 19072 AND 19072+28800 
+ 	and sm_carrier in ('FEDEX','GERMA')
+     group by 
+        w_warehouse_name
+ 	,w_warehouse_sq_ft
+ 	,w_city
+ 	,w_county
+ 	,w_state
+ 	,w_country
+       ,d_year
+ ) x
+ group by 
+        w_warehouse_name
+ 	,w_warehouse_sq_ft
+ 	,w_city
+ 	,w_county
+ 	,w_state
+ 	,w_country
+ 	,ship_carriers
+       ,year
+ order by w_warehouse_name
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q67.sql b/benchmarks/tpc/queries/tpcds/q67.sql
new file mode 100644
index 0000000000..50b7e125bd
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q67.sql
@@ -0,0 +1,45 @@
+-- CometBench-DS query 67 derived from TPC-DS query 67 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  *
+from (select i_category
+            ,i_class
+            ,i_brand
+            ,i_product_name
+            ,d_year
+            ,d_qoy
+            ,d_moy
+            ,s_store_id
+            ,sumsales
+            ,rank() over (partition by i_category order by sumsales desc) rk
+      from (select i_category
+                  ,i_class
+                  ,i_brand
+                  ,i_product_name
+                  ,d_year
+                  ,d_qoy
+                  ,d_moy
+                  ,s_store_id
+                  ,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
+            from store_sales
+                ,date_dim
+                ,store
+                ,item
+       where  ss_sold_date_sk=d_date_sk
+          and ss_item_sk=i_item_sk
+          and ss_store_sk = s_store_sk
+          and d_month_seq between 1194 and 1194+11
+       group by  rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
+where rk <= 100
+order by i_category
+        ,i_class
+        ,i_brand
+        ,i_product_name
+        ,d_year
+        ,d_qoy
+        ,d_moy
+        ,s_store_id
+        ,sumsales
+        ,rk
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q68.sql b/benchmarks/tpc/queries/tpcds/q68.sql
new file mode 100644
index 0000000000..fb69c8d045
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q68.sql
@@ -0,0 +1,43 @@
+-- CometBench-DS query 68 derived from TPC-DS query 68 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  c_last_name
+       ,c_first_name
+       ,ca_city
+       ,bought_city
+       ,ss_ticket_number
+       ,extended_price
+       ,extended_tax
+       ,list_price
+ from (select ss_ticket_number
+             ,ss_customer_sk
+             ,ca_city bought_city
+             ,sum(ss_ext_sales_price) extended_price 
+             ,sum(ss_ext_list_price) list_price
+             ,sum(ss_ext_tax) extended_tax 
+       from store_sales
+           ,date_dim
+           ,store
+           ,household_demographics
+           ,customer_address 
+       where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+         and store_sales.ss_store_sk = store.s_store_sk  
+        and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+        and store_sales.ss_addr_sk = customer_address.ca_address_sk
+        and date_dim.d_dom between 1 and 2 
+        and (household_demographics.hd_dep_count = 8 or
+             household_demographics.hd_vehicle_count= 3)
+        and date_dim.d_year in (2000,2000+1,2000+2)
+        and store.s_city in ('Midway','Fairview')
+       group by ss_ticket_number
+               ,ss_customer_sk
+               ,ss_addr_sk,ca_city) dn
+      ,customer
+      ,customer_address current_addr
+ where ss_customer_sk = c_customer_sk
+   and customer.c_current_addr_sk = current_addr.ca_address_sk
+   and current_addr.ca_city <> bought_city
+ order by c_last_name
+         ,ss_ticket_number
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q69.sql b/benchmarks/tpc/queries/tpcds/q69.sql
new file mode 100644
index 0000000000..d9bb0ff013
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q69.sql
@@ -0,0 +1,48 @@
+-- CometBench-DS query 69 derived from TPC-DS query 69 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+  cd_gender,
+  cd_marital_status,
+  cd_education_status,
+  count(*) cnt1,
+  cd_purchase_estimate,
+  count(*) cnt2,
+  cd_credit_rating,
+  count(*) cnt3
+ from
+  customer c,customer_address ca,customer_demographics
+ where
+  c.c_current_addr_sk = ca.ca_address_sk and
+  ca_state in ('IN','VA','MS') and
+  cd_demo_sk = c.c_current_cdemo_sk and 
+  exists (select *
+          from store_sales,date_dim
+          where c.c_customer_sk = ss_customer_sk and
+                ss_sold_date_sk = d_date_sk and
+                d_year = 2002 and
+                d_moy between 2 and 2+2) and
+   (not exists (select *
+            from web_sales,date_dim
+            where c.c_customer_sk = ws_bill_customer_sk and
+                  ws_sold_date_sk = d_date_sk and
+                  d_year = 2002 and
+                  d_moy between 2 and 2+2) and
+    not exists (select * 
+            from catalog_sales,date_dim
+            where c.c_customer_sk = cs_ship_customer_sk and
+                  cs_sold_date_sk = d_date_sk and
+                  d_year = 2002 and
+                  d_moy between 2 and 2+2))
+ group by cd_gender,
+          cd_marital_status,
+          cd_education_status,
+          cd_purchase_estimate,
+          cd_credit_rating
+ order by cd_gender,
+          cd_marital_status,
+          cd_education_status,
+          cd_purchase_estimate,
+          cd_credit_rating
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q7.sql b/benchmarks/tpc/queries/tpcds/q7.sql
new file mode 100644
index 0000000000..02e55dddf7
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q7.sql
@@ -0,0 +1,22 @@
+-- CometBench-DS query 7 derived from TPC-DS query 7 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id, 
+        avg(ss_quantity) agg1,
+        avg(ss_list_price) agg2,
+        avg(ss_coupon_amt) agg3,
+        avg(ss_sales_price) agg4 
+ from store_sales, customer_demographics, date_dim, item, promotion
+ where ss_sold_date_sk = d_date_sk and
+       ss_item_sk = i_item_sk and
+       ss_cdemo_sk = cd_demo_sk and
+       ss_promo_sk = p_promo_sk and
+       cd_gender = 'M' and 
+       cd_marital_status = 'M' and
+       cd_education_status = '4 yr Degree' and
+       (p_channel_email = 'N' or p_channel_event = 'N') and
+       d_year = 2001 
+ group by i_item_id
+ order by i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q70.sql b/benchmarks/tpc/queries/tpcds/q70.sql
new file mode 100644
index 0000000000..a5b67fae2a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q70.sql
@@ -0,0 +1,39 @@
+-- CometBench-DS query 70 derived from TPC-DS query 70 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+    sum(ss_net_profit) as total_sum
+   ,s_state
+   ,s_county
+   ,grouping(s_state)+grouping(s_county) as lochierarchy
+   ,rank() over (
+ 	partition by grouping(s_state)+grouping(s_county),
+ 	case when grouping(s_county) = 0 then s_state end 
+ 	order by sum(ss_net_profit) desc) as rank_within_parent
+ from
+    store_sales
+   ,date_dim       d1
+   ,store
+ where
+    d1.d_month_seq between 1180 and 1180+11
+ and d1.d_date_sk = ss_sold_date_sk
+ and s_store_sk  = ss_store_sk
+ and s_state in
+             ( select s_state
+               from  (select s_state as s_state,
+ 			    rank() over ( partition by s_state order by sum(ss_net_profit) desc) as ranking
+                      from   store_sales, store, date_dim
+                      where  d_month_seq between 1180 and 1180+11
+ 			    and d_date_sk = ss_sold_date_sk
+ 			    and s_store_sk  = ss_store_sk
+                      group by s_state
+                     ) tmp1 
+               where ranking <= 5
+             )
+ group by rollup(s_state,s_county)
+ order by
+   lochierarchy desc
+  ,case when lochierarchy = 0 then s_state end
+  ,rank_within_parent
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q71.sql b/benchmarks/tpc/queries/tpcds/q71.sql
new file mode 100644
index 0000000000..04ce711a31
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q71.sql
@@ -0,0 +1,41 @@
+-- CometBench-DS query 71 derived from TPC-DS query 71 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select i_brand_id brand_id, i_brand brand,t_hour,t_minute,
+ 	sum(ext_price) ext_price
+ from item, (select ws_ext_sales_price as ext_price, 
+                        ws_sold_date_sk as sold_date_sk,
+                        ws_item_sk as sold_item_sk,
+                        ws_sold_time_sk as time_sk  
+                 from web_sales,date_dim
+                 where d_date_sk = ws_sold_date_sk
+                   and d_moy=11
+                   and d_year=2001
+                 union all
+                 select cs_ext_sales_price as ext_price,
+                        cs_sold_date_sk as sold_date_sk,
+                        cs_item_sk as sold_item_sk,
+                        cs_sold_time_sk as time_sk
+                 from catalog_sales,date_dim
+                 where d_date_sk = cs_sold_date_sk
+                   and d_moy=11
+                   and d_year=2001
+                 union all
+                 select ss_ext_sales_price as ext_price,
+                        ss_sold_date_sk as sold_date_sk,
+                        ss_item_sk as sold_item_sk,
+                        ss_sold_time_sk as time_sk
+                 from store_sales,date_dim
+                 where d_date_sk = ss_sold_date_sk
+                   and d_moy=11
+                   and d_year=2001
+                 ) tmp,time_dim
+ where
+   sold_item_sk = i_item_sk
+   and i_manager_id=1
+   and time_sk = t_time_sk
+   and (t_meal_time = 'breakfast' or t_meal_time = 'dinner')
+ group by i_brand, i_brand_id,t_hour,t_minute
+ order by ext_price desc, i_brand_id
+ ;
+
diff --git a/benchmarks/tpc/queries/tpcds/q72.sql b/benchmarks/tpc/queries/tpcds/q72.sql
new file mode 100644
index 0000000000..d89d62ce9e
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q72.sql
@@ -0,0 +1,30 @@
+-- CometBench-DS query 72 derived from TPC-DS query 72 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_desc
+      ,w_warehouse_name
+      ,d1.d_week_seq
+      ,sum(case when p_promo_sk is null then 1 else 0 end) no_promo
+      ,sum(case when p_promo_sk is not null then 1 else 0 end) promo
+      ,count(*) total_cnt
+from catalog_sales
+join inventory on (cs_item_sk = inv_item_sk)
+join warehouse on (w_warehouse_sk=inv_warehouse_sk)
+join item on (i_item_sk = cs_item_sk)
+join customer_demographics on (cs_bill_cdemo_sk = cd_demo_sk)
+join household_demographics on (cs_bill_hdemo_sk = hd_demo_sk)
+join date_dim d1 on (cs_sold_date_sk = d1.d_date_sk)
+join date_dim d2 on (inv_date_sk = d2.d_date_sk)
+join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk)
+left outer join promotion on (cs_promo_sk=p_promo_sk)
+left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number)
+where d1.d_week_seq = d2.d_week_seq
+  and inv_quantity_on_hand < cs_quantity 
+  and d3.d_date > d1.d_date + 5
+  and hd_buy_potential = '501-1000'
+  and d1.d_year = 1999
+  and cd_marital_status = 'S'
+group by i_item_desc,w_warehouse_name,d1.d_week_seq
+order by total_cnt desc, i_item_desc, w_warehouse_name, d_week_seq
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q73.sql b/benchmarks/tpc/queries/tpcds/q73.sql
new file mode 100644
index 0000000000..b21caa6e8a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q73.sql
@@ -0,0 +1,29 @@
+-- CometBench-DS query 73 derived from TPC-DS query 73 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select c_last_name
+       ,c_first_name
+       ,c_salutation
+       ,c_preferred_cust_flag 
+       ,ss_ticket_number
+       ,cnt from
+   (select ss_ticket_number
+          ,ss_customer_sk
+          ,count(*) cnt
+    from store_sales,date_dim,store,household_demographics
+    where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+    and store_sales.ss_store_sk = store.s_store_sk  
+    and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+    and date_dim.d_dom between 1 and 2 
+    and (household_demographics.hd_buy_potential = '1001-5000' or
+         household_demographics.hd_buy_potential = '5001-10000')
+    and household_demographics.hd_vehicle_count > 0
+    and case when household_demographics.hd_vehicle_count > 0 then 
+             household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1
+    and date_dim.d_year in (1999,1999+1,1999+2)
+    and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County')
+    group by ss_ticket_number,ss_customer_sk) dj,customer
+    where ss_customer_sk = c_customer_sk
+      and cnt between 1 and 5
+    order by cnt desc, c_last_name asc;
+
diff --git a/benchmarks/tpc/queries/tpcds/q74.sql b/benchmarks/tpc/queries/tpcds/q74.sql
new file mode 100644
index 0000000000..04af4b3fd0
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q74.sql
@@ -0,0 +1,62 @@
+-- CometBench-DS query 74 derived from TPC-DS query 74 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with year_total as (
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,d_year as year
+       ,stddev_samp(ss_net_paid) year_total
+       ,'s' sale_type
+ from customer
+     ,store_sales
+     ,date_dim
+ where c_customer_sk = ss_customer_sk
+   and ss_sold_date_sk = d_date_sk
+   and d_year in (2001,2001+1)
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,d_year
+ union all
+ select c_customer_id customer_id
+       ,c_first_name customer_first_name
+       ,c_last_name customer_last_name
+       ,d_year as year
+       ,stddev_samp(ws_net_paid) year_total
+       ,'w' sale_type
+ from customer
+     ,web_sales
+     ,date_dim
+ where c_customer_sk = ws_bill_customer_sk
+   and ws_sold_date_sk = d_date_sk
+   and d_year in (2001,2001+1)
+ group by c_customer_id
+         ,c_first_name
+         ,c_last_name
+         ,d_year
+         )
+  select 
+        t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name
+ from year_total t_s_firstyear
+     ,year_total t_s_secyear
+     ,year_total t_w_firstyear
+     ,year_total t_w_secyear
+ where t_s_secyear.customer_id = t_s_firstyear.customer_id
+         and t_s_firstyear.customer_id = t_w_secyear.customer_id
+         and t_s_firstyear.customer_id = t_w_firstyear.customer_id
+         and t_s_firstyear.sale_type = 's'
+         and t_w_firstyear.sale_type = 'w'
+         and t_s_secyear.sale_type = 's'
+         and t_w_secyear.sale_type = 'w'
+         and t_s_firstyear.year = 2001
+         and t_s_secyear.year = 2001+1
+         and t_w_firstyear.year = 2001
+         and t_w_secyear.year = 2001+1
+         and t_s_firstyear.year_total > 0
+         and t_w_firstyear.year_total > 0
+         and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
+           > case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
+ order by 3,2,1
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q75.sql b/benchmarks/tpc/queries/tpcds/q75.sql
new file mode 100644
index 0000000000..8e739147d0
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q75.sql
@@ -0,0 +1,71 @@
+-- CometBench-DS query 75 derived from TPC-DS query 75 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+WITH all_sales AS (
+ SELECT d_year
+       ,i_brand_id
+       ,i_class_id
+       ,i_category_id
+       ,i_manufact_id
+       ,SUM(sales_cnt) AS sales_cnt
+       ,SUM(sales_amt) AS sales_amt
+ FROM (SELECT d_year
+             ,i_brand_id
+             ,i_class_id
+             ,i_category_id
+             ,i_manufact_id
+             ,cs_quantity - COALESCE(cr_return_quantity,0) AS sales_cnt
+             ,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt
+       FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk
+                          JOIN date_dim ON d_date_sk=cs_sold_date_sk
+                          LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number 
+                                                    AND cs_item_sk=cr_item_sk)
+       WHERE i_category='Shoes'
+       UNION
+       SELECT d_year
+             ,i_brand_id
+             ,i_class_id
+             ,i_category_id
+             ,i_manufact_id
+             ,ss_quantity - COALESCE(sr_return_quantity,0) AS sales_cnt
+             ,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt
+       FROM store_sales JOIN item ON i_item_sk=ss_item_sk
+                        JOIN date_dim ON d_date_sk=ss_sold_date_sk
+                        LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number 
+                                                AND ss_item_sk=sr_item_sk)
+       WHERE i_category='Shoes'
+       UNION
+       SELECT d_year
+             ,i_brand_id
+             ,i_class_id
+             ,i_category_id
+             ,i_manufact_id
+             ,ws_quantity - COALESCE(wr_return_quantity,0) AS sales_cnt
+             ,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt
+       FROM web_sales JOIN item ON i_item_sk=ws_item_sk
+                      JOIN date_dim ON d_date_sk=ws_sold_date_sk
+                      LEFT JOIN web_returns ON (ws_order_number=wr_order_number 
+                                            AND ws_item_sk=wr_item_sk)
+       WHERE i_category='Shoes') sales_detail
+ GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id)
+ SELECT  prev_yr.d_year AS prev_year
+                          ,curr_yr.d_year AS year
+                          ,curr_yr.i_brand_id
+                          ,curr_yr.i_class_id
+                          ,curr_yr.i_category_id
+                          ,curr_yr.i_manufact_id
+                          ,prev_yr.sales_cnt AS prev_yr_cnt
+                          ,curr_yr.sales_cnt AS curr_yr_cnt
+                          ,curr_yr.sales_cnt-prev_yr.sales_cnt AS sales_cnt_diff
+                          ,curr_yr.sales_amt-prev_yr.sales_amt AS sales_amt_diff
+ FROM all_sales curr_yr, all_sales prev_yr
+ WHERE curr_yr.i_brand_id=prev_yr.i_brand_id
+   AND curr_yr.i_class_id=prev_yr.i_class_id
+   AND curr_yr.i_category_id=prev_yr.i_category_id
+   AND curr_yr.i_manufact_id=prev_yr.i_manufact_id
+   AND curr_yr.d_year=2000
+   AND prev_yr.d_year=2000-1
+   AND CAST(curr_yr.sales_cnt AS DECIMAL(17,2))/CAST(prev_yr.sales_cnt AS DECIMAL(17,2))<0.9
+ ORDER BY sales_cnt_diff,sales_amt_diff
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q76.sql b/benchmarks/tpc/queries/tpcds/q76.sql
new file mode 100644
index 0000000000..98fc8ddb2a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q76.sql
@@ -0,0 +1,25 @@
+-- CometBench-DS query 76 derived from TPC-DS query 76 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  channel, col_name, d_year, d_qoy, i_category, COUNT(*) sales_cnt, SUM(ext_sales_price) sales_amt FROM (
+        SELECT 'store' as channel, 'ss_customer_sk' col_name, d_year, d_qoy, i_category, ss_ext_sales_price ext_sales_price
+         FROM store_sales, item, date_dim
+         WHERE ss_customer_sk IS NULL
+           AND ss_sold_date_sk=d_date_sk
+           AND ss_item_sk=i_item_sk
+        UNION ALL
+        SELECT 'web' as channel, 'ws_ship_hdemo_sk' col_name, d_year, d_qoy, i_category, ws_ext_sales_price ext_sales_price
+         FROM web_sales, item, date_dim
+         WHERE ws_ship_hdemo_sk IS NULL
+           AND ws_sold_date_sk=d_date_sk
+           AND ws_item_sk=i_item_sk
+        UNION ALL
+        SELECT 'catalog' as channel, 'cs_bill_customer_sk' col_name, d_year, d_qoy, i_category, cs_ext_sales_price ext_sales_price
+         FROM catalog_sales, item, date_dim
+         WHERE cs_bill_customer_sk IS NULL
+           AND cs_sold_date_sk=d_date_sk
+           AND cs_item_sk=i_item_sk) foo
+GROUP BY channel, col_name, d_year, d_qoy, i_category
+ORDER BY channel, col_name, d_year, d_qoy, i_category
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q77.sql b/benchmarks/tpc/queries/tpcds/q77.sql
new file mode 100644
index 0000000000..fac28a26a6
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q77.sql
@@ -0,0 +1,109 @@
+-- CometBench-DS query 77 derived from TPC-DS query 77 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ss as
+ (select s_store_sk,
+         sum(ss_ext_sales_price) as sales,
+         sum(ss_net_profit) as profit
+ from store_sales,
+      date_dim,
+      store
+ where ss_sold_date_sk = d_date_sk
+       and d_date between cast('2001-08-11' as date) 
+                  and (cast('2001-08-11' as date) +  30 days) 
+       and ss_store_sk = s_store_sk
+ group by s_store_sk)
+ ,
+ sr as
+ (select s_store_sk,
+         sum(sr_return_amt) as returns,
+         sum(sr_net_loss) as profit_loss
+ from store_returns,
+      date_dim,
+      store
+ where sr_returned_date_sk = d_date_sk
+       and d_date between cast('2001-08-11' as date)
+                  and (cast('2001-08-11' as date) +  30 days)
+       and sr_store_sk = s_store_sk
+ group by s_store_sk), 
+ cs as
+ (select cs_call_center_sk,
+        sum(cs_ext_sales_price) as sales,
+        sum(cs_net_profit) as profit
+ from catalog_sales,
+      date_dim
+ where cs_sold_date_sk = d_date_sk
+       and d_date between cast('2001-08-11' as date)
+                  and (cast('2001-08-11' as date) +  30 days)
+ group by cs_call_center_sk 
+ ), 
+ cr as
+ (select cr_call_center_sk,
+         sum(cr_return_amount) as returns,
+         sum(cr_net_loss) as profit_loss
+ from catalog_returns,
+      date_dim
+ where cr_returned_date_sk = d_date_sk
+       and d_date between cast('2001-08-11' as date)
+                  and (cast('2001-08-11' as date) +  30 days)
+ group by cr_call_center_sk
+ ), 
+ ws as
+ ( select wp_web_page_sk,
+        sum(ws_ext_sales_price) as sales,
+        sum(ws_net_profit) as profit
+ from web_sales,
+      date_dim,
+      web_page
+ where ws_sold_date_sk = d_date_sk
+       and d_date between cast('2001-08-11' as date)
+                  and (cast('2001-08-11' as date) +  30 days)
+       and ws_web_page_sk = wp_web_page_sk
+ group by wp_web_page_sk), 
+ wr as
+ (select wp_web_page_sk,
+        sum(wr_return_amt) as returns,
+        sum(wr_net_loss) as profit_loss
+ from web_returns,
+      date_dim,
+      web_page
+ where wr_returned_date_sk = d_date_sk
+       and d_date between cast('2001-08-11' as date)
+                  and (cast('2001-08-11' as date) +  30 days)
+       and wr_web_page_sk = wp_web_page_sk
+ group by wp_web_page_sk)
+  select  channel
+        , id
+        , sum(sales) as sales
+        , sum(returns) as returns
+        , sum(profit) as profit
+ from 
+ (select 'store channel' as channel
+        , ss.s_store_sk as id
+        , sales
+        , coalesce(returns, 0) as returns
+        , (profit - coalesce(profit_loss,0)) as profit
+ from   ss left join sr
+        on  ss.s_store_sk = sr.s_store_sk
+ union all
+ select 'catalog channel' as channel
+        , cs_call_center_sk as id
+        , sales
+        , returns
+        , (profit - profit_loss) as profit
+ from  cs
+       , cr
+ union all
+ select 'web channel' as channel
+        , ws.wp_web_page_sk as id
+        , sales
+        , coalesce(returns, 0) returns
+        , (profit - coalesce(profit_loss,0)) as profit
+ from   ws left join wr
+        on  ws.wp_web_page_sk = wr.wp_web_page_sk
+ ) x
+ group by rollup (channel, id)
+ order by channel
+         ,id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q78.sql b/benchmarks/tpc/queries/tpcds/q78.sql
new file mode 100644
index 0000000000..2cb7a97da2
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q78.sql
@@ -0,0 +1,59 @@
+-- CometBench-DS query 78 derived from TPC-DS query 78 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ws as
+  (select d_year AS ws_sold_year, ws_item_sk,
+    ws_bill_customer_sk ws_customer_sk,
+    sum(ws_quantity) ws_qty,
+    sum(ws_wholesale_cost) ws_wc,
+    sum(ws_sales_price) ws_sp
+   from web_sales
+   left join web_returns on wr_order_number=ws_order_number and ws_item_sk=wr_item_sk
+   join date_dim on ws_sold_date_sk = d_date_sk
+   where wr_order_number is null
+   group by d_year, ws_item_sk, ws_bill_customer_sk
+   ),
+cs as
+  (select d_year AS cs_sold_year, cs_item_sk,
+    cs_bill_customer_sk cs_customer_sk,
+    sum(cs_quantity) cs_qty,
+    sum(cs_wholesale_cost) cs_wc,
+    sum(cs_sales_price) cs_sp
+   from catalog_sales
+   left join catalog_returns on cr_order_number=cs_order_number and cs_item_sk=cr_item_sk
+   join date_dim on cs_sold_date_sk = d_date_sk
+   where cr_order_number is null
+   group by d_year, cs_item_sk, cs_bill_customer_sk
+   ),
+ss as
+  (select d_year AS ss_sold_year, ss_item_sk,
+    ss_customer_sk,
+    sum(ss_quantity) ss_qty,
+    sum(ss_wholesale_cost) ss_wc,
+    sum(ss_sales_price) ss_sp
+   from store_sales
+   left join store_returns on sr_ticket_number=ss_ticket_number and ss_item_sk=sr_item_sk
+   join date_dim on ss_sold_date_sk = d_date_sk
+   where sr_ticket_number is null
+   group by d_year, ss_item_sk, ss_customer_sk
+   )
+ select 
+ss_customer_sk,
+round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio,
+ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price,
+coalesce(ws_qty,0)+coalesce(cs_qty,0) other_chan_qty,
+coalesce(ws_wc,0)+coalesce(cs_wc,0) other_chan_wholesale_cost,
+coalesce(ws_sp,0)+coalesce(cs_sp,0) other_chan_sales_price
+from ss
+left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk)
+left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk)
+where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=2001
+order by 
+  ss_customer_sk,
+  ss_qty desc, ss_wc desc, ss_sp desc,
+  other_chan_qty,
+  other_chan_wholesale_cost,
+  other_chan_sales_price,
+  ratio
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q79.sql b/benchmarks/tpc/queries/tpcds/q79.sql
new file mode 100644
index 0000000000..3680d08400
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q79.sql
@@ -0,0 +1,24 @@
+-- CometBench-DS query 79 derived from TPC-DS query 79 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select 
+  c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit
+  from
+   (select ss_ticket_number
+          ,ss_customer_sk
+          ,store.s_city
+          ,sum(ss_coupon_amt) amt
+          ,sum(ss_net_profit) profit
+    from store_sales,date_dim,store,household_demographics
+    where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+    and store_sales.ss_store_sk = store.s_store_sk  
+    and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
+    and (household_demographics.hd_dep_count = 0 or household_demographics.hd_vehicle_count > 4)
+    and date_dim.d_dow = 1
+    and date_dim.d_year in (1999,1999+1,1999+2) 
+    and store.s_number_employees between 200 and 295
+    group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer
+    where ss_customer_sk = c_customer_sk
+ order by c_last_name,c_first_name,substr(s_city,1,30), profit
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q8.sql b/benchmarks/tpc/queries/tpcds/q8.sql
new file mode 100644
index 0000000000..63235faf45
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q8.sql
@@ -0,0 +1,109 @@
+-- CometBench-DS query 8 derived from TPC-DS query 8 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  s_store_name
+      ,sum(ss_net_profit)
+ from store_sales
+     ,date_dim
+     ,store,
+     (select ca_zip
+     from (
+      SELECT substr(ca_zip,1,5) ca_zip
+      FROM customer_address
+      WHERE substr(ca_zip,1,5) IN (
+                          '19100','41548','51640','49699','88329','55986',
+                          '85119','19510','61020','95452','26235',
+                          '51102','16733','42819','27823','90192',
+                          '31905','28865','62197','23750','81398',
+                          '95288','45114','82060','12313','25218',
+                          '64386','46400','77230','69271','43672',
+                          '36521','34217','13017','27936','42766',
+                          '59233','26060','27477','39981','93402',
+                          '74270','13932','51731','71642','17710',
+                          '85156','21679','70840','67191','39214',
+                          '35273','27293','17128','15458','31615',
+                          '60706','67657','54092','32775','14683',
+                          '32206','62543','43053','11297','58216',
+                          '49410','14710','24501','79057','77038',
+                          '91286','32334','46298','18326','67213',
+                          '65382','40315','56115','80162','55956',
+                          '81583','73588','32513','62880','12201',
+                          '11592','17014','83832','61796','57872',
+                          '78829','69912','48524','22016','26905',
+                          '48511','92168','63051','25748','89786',
+                          '98827','86404','53029','37524','14039',
+                          '50078','34487','70142','18697','40129',
+                          '60642','42810','62667','57183','46414',
+                          '58463','71211','46364','34851','54884',
+                          '25382','25239','74126','21568','84204',
+                          '13607','82518','32982','36953','86001',
+                          '79278','21745','64444','35199','83181',
+                          '73255','86177','98043','90392','13882',
+                          '47084','17859','89526','42072','20233',
+                          '52745','75000','22044','77013','24182',
+                          '52554','56138','43440','86100','48791',
+                          '21883','17096','15965','31196','74903',
+                          '19810','35763','92020','55176','54433',
+                          '68063','71919','44384','16612','32109',
+                          '28207','14762','89933','10930','27616',
+                          '56809','14244','22733','33177','29784',
+                          '74968','37887','11299','34692','85843',
+                          '83663','95421','19323','17406','69264',
+                          '28341','50150','79121','73974','92917',
+                          '21229','32254','97408','46011','37169',
+                          '18146','27296','62927','68812','47734',
+                          '86572','12620','80252','50173','27261',
+                          '29534','23488','42184','23695','45868',
+                          '12910','23429','29052','63228','30731',
+                          '15747','25827','22332','62349','56661',
+                          '44652','51862','57007','22773','40361',
+                          '65238','19327','17282','44708','35484',
+                          '34064','11148','92729','22995','18833',
+                          '77528','48917','17256','93166','68576',
+                          '71096','56499','35096','80551','82424',
+                          '17700','32748','78969','46820','57725',
+                          '46179','54677','98097','62869','83959',
+                          '66728','19716','48326','27420','53458',
+                          '69056','84216','36688','63957','41469',
+                          '66843','18024','81950','21911','58387',
+                          '58103','19813','34581','55347','17171',
+                          '35914','75043','75088','80541','26802',
+                          '28849','22356','57721','77084','46385',
+                          '59255','29308','65885','70673','13306',
+                          '68788','87335','40987','31654','67560',
+                          '92309','78116','65961','45018','16548',
+                          '67092','21818','33716','49449','86150',
+                          '12156','27574','43201','50977','52839',
+                          '33234','86611','71494','17823','57172',
+                          '59869','34086','51052','11320','39717',
+                          '79604','24672','70555','38378','91135',
+                          '15567','21606','74994','77168','38607',
+                          '27384','68328','88944','40203','37893',
+                          '42726','83549','48739','55652','27543',
+                          '23109','98908','28831','45011','47525',
+                          '43870','79404','35780','42136','49317',
+                          '14574','99586','21107','14302','83882',
+                          '81272','92552','14916','87533','86518',
+                          '17862','30741','96288','57886','30304',
+                          '24201','79457','36728','49833','35182',
+                          '20108','39858','10804','47042','20439',
+                          '54708','59027','82499','75311','26548',
+                          '53406','92060','41152','60446','33129',
+                          '43979','16903','60319','35550','33887',
+                          '25463','40343','20726','44429')
+     intersect
+      select ca_zip
+      from (SELECT substr(ca_zip,1,5) ca_zip,count(*) cnt
+            FROM customer_address, customer
+            WHERE ca_address_sk = c_current_addr_sk and
+                  c_preferred_cust_flag='Y'
+            group by ca_zip
+            having count(*) > 10)A1)A2) V1
+ where ss_store_sk = s_store_sk
+  and ss_sold_date_sk = d_date_sk
+  and d_qoy = 1 and d_year = 2000
+  and (substr(s_zip,1,2) = substr(V1.ca_zip,1,2))
+ group by s_store_name
+ order by s_store_name
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q80.sql b/benchmarks/tpc/queries/tpcds/q80.sql
new file mode 100644
index 0000000000..484aa4b28f
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q80.sql
@@ -0,0 +1,97 @@
+-- CometBench-DS query 80 derived from TPC-DS query 80 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ssr as
+ (select  s_store_id as store_id,
+          sum(ss_ext_sales_price) as sales,
+          sum(coalesce(sr_return_amt, 0)) as returns,
+          sum(ss_net_profit - coalesce(sr_net_loss, 0)) as profit
+  from store_sales left outer join store_returns on
+         (ss_item_sk = sr_item_sk and ss_ticket_number = sr_ticket_number),
+     date_dim,
+     store,
+     item,
+     promotion
+ where ss_sold_date_sk = d_date_sk
+       and d_date between cast('2002-08-04' as date) 
+                  and (cast('2002-08-04' as date) +  30 days)
+       and ss_store_sk = s_store_sk
+       and ss_item_sk = i_item_sk
+       and i_current_price > 50
+       and ss_promo_sk = p_promo_sk
+       and p_channel_tv = 'N'
+ group by s_store_id)
+ ,
+ csr as
+ (select  cp_catalog_page_id as catalog_page_id,
+          sum(cs_ext_sales_price) as sales,
+          sum(coalesce(cr_return_amount, 0)) as returns,
+          sum(cs_net_profit - coalesce(cr_net_loss, 0)) as profit
+  from catalog_sales left outer join catalog_returns on
+         (cs_item_sk = cr_item_sk and cs_order_number = cr_order_number),
+     date_dim,
+     catalog_page,
+     item,
+     promotion
+ where cs_sold_date_sk = d_date_sk
+       and d_date between cast('2002-08-04' as date)
+                  and (cast('2002-08-04' as date) +  30 days)
+        and cs_catalog_page_sk = cp_catalog_page_sk
+       and cs_item_sk = i_item_sk
+       and i_current_price > 50
+       and cs_promo_sk = p_promo_sk
+       and p_channel_tv = 'N'
+group by cp_catalog_page_id)
+ ,
+ wsr as
+ (select  web_site_id,
+          sum(ws_ext_sales_price) as sales,
+          sum(coalesce(wr_return_amt, 0)) as returns,
+          sum(ws_net_profit - coalesce(wr_net_loss, 0)) as profit
+  from web_sales left outer join web_returns on
+         (ws_item_sk = wr_item_sk and ws_order_number = wr_order_number),
+     date_dim,
+     web_site,
+     item,
+     promotion
+ where ws_sold_date_sk = d_date_sk
+       and d_date between cast('2002-08-04' as date)
+                  and (cast('2002-08-04' as date) +  30 days)
+        and ws_web_site_sk = web_site_sk
+       and ws_item_sk = i_item_sk
+       and i_current_price > 50
+       and ws_promo_sk = p_promo_sk
+       and p_channel_tv = 'N'
+group by web_site_id)
+  select  channel
+        , id
+        , sum(sales) as sales
+        , sum(returns) as returns
+        , sum(profit) as profit
+ from 
+ (select 'store channel' as channel
+        , 'store' || store_id as id
+        , sales
+        , returns
+        , profit
+ from   ssr
+ union all
+ select 'catalog channel' as channel
+        , 'catalog_page' || catalog_page_id as id
+        , sales
+        , returns
+        , profit
+ from  csr
+ union all
+ select 'web channel' as channel
+        , 'web_site' || web_site_id as id
+        , sales
+        , returns
+        , profit
+ from   wsr
+ ) x
+ group by rollup (channel, id)
+ order by channel
+         ,id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q81.sql b/benchmarks/tpc/queries/tpcds/q81.sql
new file mode 100644
index 0000000000..a768764099
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q81.sql
@@ -0,0 +1,32 @@
+-- CometBench-DS query 81 derived from TPC-DS query 81 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with customer_total_return as
+ (select cr_returning_customer_sk as ctr_customer_sk
+        ,ca_state as ctr_state, 
+ 	sum(cr_return_amt_inc_tax) as ctr_total_return
+ from catalog_returns
+     ,date_dim
+     ,customer_address
+ where cr_returned_date_sk = d_date_sk 
+   and d_year =1998
+   and cr_returning_addr_sk = ca_address_sk 
+ group by cr_returning_customer_sk
+         ,ca_state )
+  select  c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
+                   ,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
+                  ,ca_location_type,ctr_total_return
+ from customer_total_return ctr1
+     ,customer_address
+     ,customer
+ where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
+ 			  from customer_total_return ctr2 
+                  	  where ctr1.ctr_state = ctr2.ctr_state)
+       and ca_address_sk = c_current_addr_sk
+       and ca_state = 'TX'
+       and ctr1.ctr_customer_sk = c_customer_sk
+ order by c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
+                   ,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
+                  ,ca_location_type,ctr_total_return
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q82.sql b/benchmarks/tpc/queries/tpcds/q82.sql
new file mode 100644
index 0000000000..c967802b33
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q82.sql
@@ -0,0 +1,18 @@
+-- CometBench-DS query 82 derived from TPC-DS query 82 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  i_item_id
+       ,i_item_desc
+       ,i_current_price
+ from item, inventory, date_dim, store_sales
+ where i_current_price between 69 and 69+30
+ and inv_item_sk = i_item_sk
+ and d_date_sk=inv_date_sk
+ and d_date between cast('1998-06-06' as date) and (cast('1998-06-06' as date) +  60 days)
+ and i_manufact_id in (105,513,180,137)
+ and inv_quantity_on_hand between 100 and 500
+ and ss_item_sk = i_item_sk
+ group by i_item_id,i_item_desc,i_current_price
+ order by i_item_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q83.sql b/benchmarks/tpc/queries/tpcds/q83.sql
new file mode 100644
index 0000000000..85f25c7eea
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q83.sql
@@ -0,0 +1,68 @@
+-- CometBench-DS query 83 derived from TPC-DS query 83 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with sr_items as
+ (select i_item_id item_id,
+        sum(sr_return_quantity) sr_item_qty
+ from store_returns,
+      item,
+      date_dim
+ where sr_item_sk = i_item_sk
+ and   d_date    in 
+	(select d_date
+	from date_dim
+	where d_week_seq in 
+		(select d_week_seq
+		from date_dim
+	  where d_date in ('2000-04-29','2000-09-09','2000-11-02')))
+ and   sr_returned_date_sk   = d_date_sk
+ group by i_item_id),
+ cr_items as
+ (select i_item_id item_id,
+        sum(cr_return_quantity) cr_item_qty
+ from catalog_returns,
+      item,
+      date_dim
+ where cr_item_sk = i_item_sk
+ and   d_date    in 
+	(select d_date
+	from date_dim
+	where d_week_seq in 
+		(select d_week_seq
+		from date_dim
+	  where d_date in ('2000-04-29','2000-09-09','2000-11-02')))
+ and   cr_returned_date_sk   = d_date_sk
+ group by i_item_id),
+ wr_items as
+ (select i_item_id item_id,
+        sum(wr_return_quantity) wr_item_qty
+ from web_returns,
+      item,
+      date_dim
+ where wr_item_sk = i_item_sk
+ and   d_date    in 
+	(select d_date
+	from date_dim
+	where d_week_seq in 
+		(select d_week_seq
+		from date_dim
+		where d_date in ('2000-04-29','2000-09-09','2000-11-02')))
+ and   wr_returned_date_sk   = d_date_sk
+ group by i_item_id)
+  select  sr_items.item_id
+       ,sr_item_qty
+       ,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev
+       ,cr_item_qty
+       ,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev
+       ,wr_item_qty
+       ,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev
+       ,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average
+ from sr_items
+     ,cr_items
+     ,wr_items
+ where sr_items.item_id=cr_items.item_id
+   and sr_items.item_id=wr_items.item_id 
+ order by sr_items.item_id
+         ,sr_item_qty
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q84.sql b/benchmarks/tpc/queries/tpcds/q84.sql
new file mode 100644
index 0000000000..89fa1e44df
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q84.sql
@@ -0,0 +1,22 @@
+-- CometBench-DS query 84 derived from TPC-DS query 84 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  c_customer_id as customer_id
+       , coalesce(c_last_name,'') || ', ' || coalesce(c_first_name,'') as customername
+ from customer
+     ,customer_address
+     ,customer_demographics
+     ,household_demographics
+     ,income_band
+     ,store_returns
+ where ca_city	        =  'White Oak'
+   and c_current_addr_sk = ca_address_sk
+   and ib_lower_bound   >=  45626
+   and ib_upper_bound   <=  45626 + 50000
+   and ib_income_band_sk = hd_income_band_sk
+   and cd_demo_sk = c_current_cdemo_sk
+   and hd_demo_sk = c_current_hdemo_sk
+   and sr_cdemo_sk = cd_demo_sk
+ order by c_customer_id
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q85.sql b/benchmarks/tpc/queries/tpcds/q85.sql
new file mode 100644
index 0000000000..54e53149c5
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q85.sql
@@ -0,0 +1,85 @@
+-- CometBench-DS query 85 derived from TPC-DS query 85 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  substr(r_reason_desc,1,20)
+       ,avg(ws_quantity)
+       ,avg(wr_refunded_cash)
+       ,avg(wr_fee)
+ from web_sales, web_returns, web_page, customer_demographics cd1,
+      customer_demographics cd2, customer_address, date_dim, reason 
+ where ws_web_page_sk = wp_web_page_sk
+   and ws_item_sk = wr_item_sk
+   and ws_order_number = wr_order_number
+   and ws_sold_date_sk = d_date_sk and d_year = 2001
+   and cd1.cd_demo_sk = wr_refunded_cdemo_sk 
+   and cd2.cd_demo_sk = wr_returning_cdemo_sk
+   and ca_address_sk = wr_refunded_addr_sk
+   and r_reason_sk = wr_reason_sk
+   and
+   (
+    (
+     cd1.cd_marital_status = 'D'
+     and
+     cd1.cd_marital_status = cd2.cd_marital_status
+     and
+     cd1.cd_education_status = 'Primary'
+     and 
+     cd1.cd_education_status = cd2.cd_education_status
+     and
+     ws_sales_price between 100.00 and 150.00
+    )
+   or
+    (
+     cd1.cd_marital_status = 'U'
+     and
+     cd1.cd_marital_status = cd2.cd_marital_status
+     and
+     cd1.cd_education_status = 'Unknown' 
+     and
+     cd1.cd_education_status = cd2.cd_education_status
+     and
+     ws_sales_price between 50.00 and 100.00
+    )
+   or
+    (
+     cd1.cd_marital_status = 'M'
+     and
+     cd1.cd_marital_status = cd2.cd_marital_status
+     and
+     cd1.cd_education_status = 'Advanced Degree'
+     and
+     cd1.cd_education_status = cd2.cd_education_status
+     and
+     ws_sales_price between 150.00 and 200.00
+    )
+   )
+   and
+   (
+    (
+     ca_country = 'United States'
+     and
+     ca_state in ('SC', 'IN', 'VA')
+     and ws_net_profit between 100 and 200  
+    )
+    or
+    (
+     ca_country = 'United States'
+     and
+     ca_state in ('WA', 'KS', 'KY')
+     and ws_net_profit between 150 and 300  
+    )
+    or
+    (
+     ca_country = 'United States'
+     and
+     ca_state in ('SD', 'WI', 'NE')
+     and ws_net_profit between 50 and 250  
+    )
+   )
+group by r_reason_desc
+order by substr(r_reason_desc,1,20)
+        ,avg(ws_quantity)
+        ,avg(wr_refunded_cash)
+        ,avg(wr_fee)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q86.sql b/benchmarks/tpc/queries/tpcds/q86.sql
new file mode 100644
index 0000000000..c8d2d08b84
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q86.sql
@@ -0,0 +1,27 @@
+-- CometBench-DS query 86 derived from TPC-DS query 86 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select   
+    sum(ws_net_paid) as total_sum
+   ,i_category
+   ,i_class
+   ,grouping(i_category)+grouping(i_class) as lochierarchy
+   ,rank() over (
+ 	partition by grouping(i_category)+grouping(i_class),
+ 	case when grouping(i_class) = 0 then i_category end 
+ 	order by sum(ws_net_paid) desc) as rank_within_parent
+ from
+    web_sales
+   ,date_dim       d1
+   ,item
+ where
+    d1.d_month_seq between 1205 and 1205+11
+ and d1.d_date_sk = ws_sold_date_sk
+ and i_item_sk  = ws_item_sk
+ group by rollup(i_category,i_class)
+ order by
+   lochierarchy desc,
+   case when lochierarchy = 0 then i_category end,
+   rank_within_parent
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q87.sql b/benchmarks/tpc/queries/tpcds/q87.sql
new file mode 100644
index 0000000000..86e50e9ba6
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q87.sql
@@ -0,0 +1,24 @@
+-- CometBench-DS query 87 derived from TPC-DS query 87 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select count(*) 
+from ((select distinct c_last_name, c_first_name, d_date
+       from store_sales, date_dim, customer
+       where store_sales.ss_sold_date_sk = date_dim.d_date_sk
+         and store_sales.ss_customer_sk = customer.c_customer_sk
+         and d_month_seq between 1189 and 1189+11)
+       except
+      (select distinct c_last_name, c_first_name, d_date
+       from catalog_sales, date_dim, customer
+       where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
+         and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
+         and d_month_seq between 1189 and 1189+11)
+       except
+      (select distinct c_last_name, c_first_name, d_date
+       from web_sales, date_dim, customer
+       where web_sales.ws_sold_date_sk = date_dim.d_date_sk
+         and web_sales.ws_bill_customer_sk = customer.c_customer_sk
+         and d_month_seq between 1189 and 1189+11)
+) cool_cust
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q88.sql b/benchmarks/tpc/queries/tpcds/q88.sql
new file mode 100644
index 0000000000..d663b2738a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q88.sql
@@ -0,0 +1,95 @@
+-- CometBench-DS query 88 derived from TPC-DS query 88 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  *
+from
+ (select count(*) h8_30_to_9
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk   
+     and ss_hdemo_sk = household_demographics.hd_demo_sk 
+     and ss_store_sk = s_store_sk
+     and time_dim.t_hour = 8
+     and time_dim.t_minute >= 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2)) 
+     and store.s_store_name = 'ese') s1,
+ (select count(*) h9_to_9_30 
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk 
+     and time_dim.t_hour = 9 
+     and time_dim.t_minute < 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s2,
+ (select count(*) h9_30_to_10 
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk
+     and time_dim.t_hour = 9
+     and time_dim.t_minute >= 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s3,
+ (select count(*) h10_to_10_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk
+     and time_dim.t_hour = 10 
+     and time_dim.t_minute < 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s4,
+ (select count(*) h10_30_to_11
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk
+     and time_dim.t_hour = 10 
+     and time_dim.t_minute >= 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s5,
+ (select count(*) h11_to_11_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk 
+     and time_dim.t_hour = 11
+     and time_dim.t_minute < 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s6,
+ (select count(*) h11_30_to_12
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk
+     and time_dim.t_hour = 11
+     and time_dim.t_minute >= 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s7,
+ (select count(*) h12_to_12_30
+ from store_sales, household_demographics , time_dim, store
+ where ss_sold_time_sk = time_dim.t_time_sk
+     and ss_hdemo_sk = household_demographics.hd_demo_sk
+     and ss_store_sk = s_store_sk
+     and time_dim.t_hour = 12
+     and time_dim.t_minute < 30
+     and ((household_demographics.hd_dep_count = 2 and household_demographics.hd_vehicle_count<=2+2) or
+          (household_demographics.hd_dep_count = 1 and household_demographics.hd_vehicle_count<=1+2) or
+          (household_demographics.hd_dep_count = 4 and household_demographics.hd_vehicle_count<=4+2))
+     and store.s_store_name = 'ese') s8
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q89.sql b/benchmarks/tpc/queries/tpcds/q89.sql
new file mode 100644
index 0000000000..a9359808f0
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q89.sql
@@ -0,0 +1,29 @@
+-- CometBench-DS query 89 derived from TPC-DS query 89 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  *
+from(
+select i_category, i_class, i_brand,
+       s_store_name, s_company_name,
+       d_moy,
+       sum(ss_sales_price) sum_sales,
+       avg(sum(ss_sales_price)) over
+         (partition by i_category, i_brand, s_store_name, s_company_name)
+         avg_monthly_sales
+from item, store_sales, date_dim, store
+where ss_item_sk = i_item_sk and
+      ss_sold_date_sk = d_date_sk and
+      ss_store_sk = s_store_sk and
+      d_year in (2001) and
+        ((i_category in ('Children','Jewelry','Home') and
+          i_class in ('infants','birdal','flatware')
+         )
+      or (i_category in ('Electronics','Music','Books') and
+          i_class in ('audio','classical','science') 
+        ))
+group by i_category, i_class, i_brand,
+         s_store_name, s_company_name, d_moy) tmp1
+where case when (avg_monthly_sales <> 0) then (abs(sum_sales - avg_monthly_sales) / avg_monthly_sales) else null end > 0.1
+order by sum_sales - avg_monthly_sales, s_store_name
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q9.sql b/benchmarks/tpc/queries/tpcds/q9.sql
new file mode 100644
index 0000000000..7dab30e028
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q9.sql
@@ -0,0 +1,52 @@
+-- CometBench-DS query 9 derived from TPC-DS query 9 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select case when (select count(*) 
+                  from store_sales 
+                  where ss_quantity between 1 and 20) > 31002
+            then (select avg(ss_ext_discount_amt) 
+                  from store_sales 
+                  where ss_quantity between 1 and 20) 
+            else (select avg(ss_net_profit)
+                  from store_sales
+                  where ss_quantity between 1 and 20) end bucket1 ,
+       case when (select count(*)
+                  from store_sales
+                  where ss_quantity between 21 and 40) > 588
+            then (select avg(ss_ext_discount_amt)
+                  from store_sales
+                  where ss_quantity between 21 and 40) 
+            else (select avg(ss_net_profit)
+                  from store_sales
+                  where ss_quantity between 21 and 40) end bucket2,
+       case when (select count(*)
+                  from store_sales
+                  where ss_quantity between 41 and 60) > 2456
+            then (select avg(ss_ext_discount_amt)
+                  from store_sales
+                  where ss_quantity between 41 and 60)
+            else (select avg(ss_net_profit)
+                  from store_sales
+                  where ss_quantity between 41 and 60) end bucket3,
+       case when (select count(*)
+                  from store_sales
+                  where ss_quantity between 61 and 80) > 21645
+            then (select avg(ss_ext_discount_amt)
+                  from store_sales
+                  where ss_quantity between 61 and 80)
+            else (select avg(ss_net_profit)
+                  from store_sales
+                  where ss_quantity between 61 and 80) end bucket4,
+       case when (select count(*)
+                  from store_sales
+                  where ss_quantity between 81 and 100) > 20553
+            then (select avg(ss_ext_discount_amt)
+                  from store_sales
+                  where ss_quantity between 81 and 100)
+            else (select avg(ss_net_profit)
+                  from store_sales
+                  where ss_quantity between 81 and 100) end bucket5
+from reason
+where r_reason_sk = 1
+;
+
diff --git a/benchmarks/tpc/queries/tpcds/q90.sql b/benchmarks/tpc/queries/tpcds/q90.sql
new file mode 100644
index 0000000000..6c296c313d
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q90.sql
@@ -0,0 +1,23 @@
+-- CometBench-DS query 90 derived from TPC-DS query 90 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio
+ from ( select count(*) amc
+       from web_sales, household_demographics , time_dim, web_page
+       where ws_sold_time_sk = time_dim.t_time_sk
+         and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
+         and ws_web_page_sk = web_page.wp_web_page_sk
+         and time_dim.t_hour between 9 and 9+1
+         and household_demographics.hd_dep_count = 2
+         and web_page.wp_char_count between 5000 and 5200) at,
+      ( select count(*) pmc
+       from web_sales, household_demographics , time_dim, web_page
+       where ws_sold_time_sk = time_dim.t_time_sk
+         and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
+         and ws_web_page_sk = web_page.wp_web_page_sk
+         and time_dim.t_hour between 15 and 15+1
+         and household_demographics.hd_dep_count = 2
+         and web_page.wp_char_count between 5000 and 5200) pt
+ order by am_pm_ratio
+  LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q91.sql b/benchmarks/tpc/queries/tpcds/q91.sql
new file mode 100644
index 0000000000..a9ebbc090a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q91.sql
@@ -0,0 +1,32 @@
+-- CometBench-DS query 91 derived from TPC-DS query 91 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+        cc_call_center_id Call_Center,
+        cc_name Call_Center_Name,
+        cc_manager Manager,
+        sum(cr_net_loss) Returns_Loss
+from
+        call_center,
+        catalog_returns,
+        date_dim,
+        customer,
+        customer_address,
+        customer_demographics,
+        household_demographics
+where
+        cr_call_center_sk       = cc_call_center_sk
+and     cr_returned_date_sk     = d_date_sk
+and     cr_returning_customer_sk= c_customer_sk
+and     cd_demo_sk              = c_current_cdemo_sk
+and     hd_demo_sk              = c_current_hdemo_sk
+and     ca_address_sk           = c_current_addr_sk
+and     d_year                  = 2002 
+and     d_moy                   = 11
+and     ( (cd_marital_status       = 'M' and cd_education_status     = 'Unknown')
+        or(cd_marital_status       = 'W' and cd_education_status     = 'Advanced Degree'))
+and     hd_buy_potential like 'Unknown%'
+and     ca_gmt_offset           = -6
+group by cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status
+order by sum(cr_net_loss) desc;
+
diff --git a/benchmarks/tpc/queries/tpcds/q92.sql b/benchmarks/tpc/queries/tpcds/q92.sql
new file mode 100644
index 0000000000..2a858fc114
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q92.sql
@@ -0,0 +1,31 @@
+-- CometBench-DS query 92 derived from TPC-DS query 92 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   sum(ws_ext_discount_amt)  as "Excess Discount Amount" 
+from 
+    web_sales 
+   ,item 
+   ,date_dim
+where
+i_manufact_id = 914
+and i_item_sk = ws_item_sk 
+and d_date between '2001-01-25' and 
+        (cast('2001-01-25' as date) + 90 days)
+and d_date_sk = ws_sold_date_sk 
+and ws_ext_discount_amt  
+     > ( 
+         SELECT 
+            1.3 * avg(ws_ext_discount_amt) 
+         FROM 
+            web_sales 
+           ,date_dim
+         WHERE 
+              ws_item_sk = i_item_sk 
+          and d_date between '2001-01-25' and
+                             (cast('2001-01-25' as date) + 90 days)
+          and d_date_sk = ws_sold_date_sk 
+      ) 
+order by sum(ws_ext_discount_amt)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q93.sql b/benchmarks/tpc/queries/tpcds/q93.sql
new file mode 100644
index 0000000000..e09acd8505
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q93.sql
@@ -0,0 +1,19 @@
+-- CometBench-DS query 93 derived from TPC-DS query 93 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  ss_customer_sk
+            ,sum(act_sales) sumsales
+      from (select ss_item_sk
+                  ,ss_ticket_number
+                  ,ss_customer_sk
+                  ,case when sr_return_quantity is not null then (ss_quantity-sr_return_quantity)*ss_sales_price
+                                                            else (ss_quantity*ss_sales_price) end act_sales
+            from store_sales left outer join store_returns on (sr_item_sk = ss_item_sk
+                                                               and sr_ticket_number = ss_ticket_number)
+                ,reason
+            where sr_reason_sk = r_reason_sk
+              and r_reason_desc = 'Did not get it on time') t
+      group by ss_customer_sk
+      order by sumsales, ss_customer_sk
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q94.sql b/benchmarks/tpc/queries/tpcds/q94.sql
new file mode 100644
index 0000000000..ba9a1d9022
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q94.sql
@@ -0,0 +1,30 @@
+-- CometBench-DS query 94 derived from TPC-DS query 94 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   count(distinct ws_order_number) as "order count"
+  ,sum(ws_ext_ship_cost) as "total shipping cost"
+  ,sum(ws_net_profit) as "total net profit"
+from
+   web_sales ws1
+  ,date_dim
+  ,customer_address
+  ,web_site
+where
+    d_date between '1999-4-01' and 
+           (cast('1999-4-01' as date) + 60 days)
+and ws1.ws_ship_date_sk = d_date_sk
+and ws1.ws_ship_addr_sk = ca_address_sk
+and ca_state = 'WI'
+and ws1.ws_web_site_sk = web_site_sk
+and web_company_name = 'pri'
+and exists (select *
+            from web_sales ws2
+            where ws1.ws_order_number = ws2.ws_order_number
+              and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
+and not exists(select *
+               from web_returns wr1
+               where ws1.ws_order_number = wr1.wr_order_number)
+order by count(distinct ws_order_number)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q95.sql b/benchmarks/tpc/queries/tpcds/q95.sql
new file mode 100644
index 0000000000..01c3c8ccfe
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q95.sql
@@ -0,0 +1,33 @@
+-- CometBench-DS query 95 derived from TPC-DS query 95 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ws_wh as
+(select ws1.ws_order_number,ws1.ws_warehouse_sk wh1,ws2.ws_warehouse_sk wh2
+ from web_sales ws1,web_sales ws2
+ where ws1.ws_order_number = ws2.ws_order_number
+   and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
+ select  
+   count(distinct ws_order_number) as "order count"
+  ,sum(ws_ext_ship_cost) as "total shipping cost"
+  ,sum(ws_net_profit) as "total net profit"
+from
+   web_sales ws1
+  ,date_dim
+  ,customer_address
+  ,web_site
+where
+    d_date between '2002-5-01' and 
+           (cast('2002-5-01' as date) + 60 days)
+and ws1.ws_ship_date_sk = d_date_sk
+and ws1.ws_ship_addr_sk = ca_address_sk
+and ca_state = 'MA'
+and ws1.ws_web_site_sk = web_site_sk
+and web_company_name = 'pri'
+and ws1.ws_order_number in (select ws_order_number
+                            from ws_wh)
+and ws1.ws_order_number in (select wr_order_number
+                            from web_returns,ws_wh
+                            where wr_order_number = ws_wh.ws_order_number)
+order by count(distinct ws_order_number)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q96.sql b/benchmarks/tpc/queries/tpcds/q96.sql
new file mode 100644
index 0000000000..9642a924e1
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q96.sql
@@ -0,0 +1,17 @@
+-- CometBench-DS query 96 derived from TPC-DS query 96 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  count(*) 
+from store_sales
+    ,household_demographics 
+    ,time_dim, store
+where ss_sold_time_sk = time_dim.t_time_sk   
+    and ss_hdemo_sk = household_demographics.hd_demo_sk 
+    and ss_store_sk = s_store_sk
+    and time_dim.t_hour = 8
+    and time_dim.t_minute >= 30
+    and household_demographics.hd_dep_count = 5
+    and store.s_store_name = 'ese'
+order by count(*)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q97.sql b/benchmarks/tpc/queries/tpcds/q97.sql
new file mode 100644
index 0000000000..10b29bd126
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q97.sql
@@ -0,0 +1,26 @@
+-- CometBench-DS query 97 derived from TPC-DS query 97 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+with ssci as (
+select ss_customer_sk customer_sk
+      ,ss_item_sk item_sk
+from store_sales,date_dim
+where ss_sold_date_sk = d_date_sk
+  and d_month_seq between 1211 and 1211 + 11
+group by ss_customer_sk
+        ,ss_item_sk),
+csci as(
+ select cs_bill_customer_sk customer_sk
+      ,cs_item_sk item_sk
+from catalog_sales,date_dim
+where cs_sold_date_sk = d_date_sk
+  and d_month_seq between 1211 and 1211 + 11
+group by cs_bill_customer_sk
+        ,cs_item_sk)
+ select  sum(case when ssci.customer_sk is not null and csci.customer_sk is null then 1 else 0 end) store_only
+      ,sum(case when ssci.customer_sk is null and csci.customer_sk is not null then 1 else 0 end) catalog_only
+      ,sum(case when ssci.customer_sk is not null and csci.customer_sk is not null then 1 else 0 end) store_and_catalog
+from ssci full outer join csci on (ssci.customer_sk=csci.customer_sk
+                               and ssci.item_sk = csci.item_sk)
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpcds/q98.sql b/benchmarks/tpc/queries/tpcds/q98.sql
new file mode 100644
index 0000000000..c364ca900b
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q98.sql
@@ -0,0 +1,34 @@
+-- CometBench-DS query 98 derived from TPC-DS query 98 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select i_item_id
+      ,i_item_desc 
+      ,i_category 
+      ,i_class 
+      ,i_current_price
+      ,sum(ss_ext_sales_price) as itemrevenue 
+      ,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over
+          (partition by i_class) as revenueratio
+from	
+	store_sales
+    	,item 
+    	,date_dim
+where 
+	ss_item_sk = i_item_sk 
+  	and i_category in ('Shoes', 'Music', 'Men')
+  	and ss_sold_date_sk = d_date_sk
+	and d_date between cast('2000-01-05' as date) 
+				and (cast('2000-01-05' as date) + 30 days)
+group by 
+	i_item_id
+        ,i_item_desc 
+        ,i_category
+        ,i_class
+        ,i_current_price
+order by 
+	i_category
+        ,i_class
+        ,i_item_id
+        ,i_item_desc
+        ,revenueratio;
+
diff --git a/benchmarks/tpc/queries/tpcds/q99.sql b/benchmarks/tpc/queries/tpcds/q99.sql
new file mode 100644
index 0000000000..b4713752b7
--- /dev/null
+++ b/benchmarks/tpc/queries/tpcds/q99.sql
@@ -0,0 +1,36 @@
+-- CometBench-DS query 99 derived from TPC-DS query 99 under the terms of the TPC Fair Use Policy.
+-- TPC-DS queries are Copyright 2021 Transaction Processing Performance Council.
+-- This query was generated at scale factor 1.
+select  
+   substr(w_warehouse_name,1,20)
+  ,sm_type
+  ,cc_name
+  ,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end)  as "30 days" 
+  ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and 
+                 (cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end )  as "31-60 days" 
+  ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and 
+                 (cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end)  as "61-90 days" 
+  ,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and
+                 (cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end)  as "91-120 days" 
+  ,sum(case when (cs_ship_date_sk - cs_sold_date_sk  > 120) then 1 else 0 end)  as ">120 days" 
+from
+   catalog_sales
+  ,warehouse
+  ,ship_mode
+  ,call_center
+  ,date_dim
+where
+    d_month_seq between 1188 and 1188 + 11
+and cs_ship_date_sk   = d_date_sk
+and cs_warehouse_sk   = w_warehouse_sk
+and cs_ship_mode_sk   = sm_ship_mode_sk
+and cs_call_center_sk = cc_call_center_sk
+group by
+   substr(w_warehouse_name,1,20)
+  ,sm_type
+  ,cc_name
+order by substr(w_warehouse_name,1,20)
+        ,sm_type
+        ,cc_name
+ LIMIT 100;
+
diff --git a/benchmarks/tpc/queries/tpch/q1.sql b/benchmarks/tpc/queries/tpch/q1.sql
new file mode 100644
index 0000000000..f24b0e0615
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q1.sql
@@ -0,0 +1,23 @@
+-- CometBench-H query 1 derived from TPC-H query 1 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	l_returnflag,
+	l_linestatus,
+	sum(l_quantity) as sum_qty,
+	sum(l_extendedprice) as sum_base_price,
+	sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,
+	sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,
+	avg(l_quantity) as avg_qty,
+	avg(l_extendedprice) as avg_price,
+	avg(l_discount) as avg_disc,
+	count(*) as count_order
+from
+	lineitem
+where
+	l_shipdate <= date '1998-12-01' - interval '68 days'
+group by
+	l_returnflag,
+	l_linestatus
+order by
+	l_returnflag,
+	l_linestatus;
diff --git a/benchmarks/tpc/queries/tpch/q10.sql b/benchmarks/tpc/queries/tpch/q10.sql
new file mode 100644
index 0000000000..8475ae5fa2
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q10.sql
@@ -0,0 +1,33 @@
+-- CometBench-H query 10 derived from TPC-H query 10 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	c_custkey,
+	c_name,
+	sum(l_extendedprice * (1 - l_discount)) as revenue,
+	c_acctbal,
+	n_name,
+	c_address,
+	c_phone,
+	c_comment
+from
+	customer,
+	orders,
+	lineitem,
+	nation
+where
+	c_custkey = o_custkey
+	and l_orderkey = o_orderkey
+	and o_orderdate >= date '1993-07-01'
+	and o_orderdate < date '1993-07-01' + interval '3' month
+	and l_returnflag = 'R'
+	and c_nationkey = n_nationkey
+group by
+	c_custkey,
+	c_name,
+	c_acctbal,
+	c_phone,
+	n_name,
+	c_address,
+	c_comment
+order by
+	revenue desc limit 20;
diff --git a/benchmarks/tpc/queries/tpch/q11.sql b/benchmarks/tpc/queries/tpch/q11.sql
new file mode 100644
index 0000000000..314b1e6fc7
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q11.sql
@@ -0,0 +1,29 @@
+-- CometBench-H query 11 derived from TPC-H query 11 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	ps_partkey,
+	sum(ps_supplycost * ps_availqty) as value
+from
+	partsupp,
+	supplier,
+	nation
+where
+	ps_suppkey = s_suppkey
+	and s_nationkey = n_nationkey
+	and n_name = 'ALGERIA'
+group by
+	ps_partkey having
+		sum(ps_supplycost * ps_availqty) > (
+			select
+				sum(ps_supplycost * ps_availqty) * 0.0001000000
+			from
+				partsupp,
+				supplier,
+				nation
+			where
+				ps_suppkey = s_suppkey
+				and s_nationkey = n_nationkey
+				and n_name = 'ALGERIA'
+		)
+order by
+	value desc;
diff --git a/benchmarks/tpc/queries/tpch/q12.sql b/benchmarks/tpc/queries/tpch/q12.sql
new file mode 100644
index 0000000000..f1abd806aa
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q12.sql
@@ -0,0 +1,30 @@
+-- CometBench-H query 12 derived from TPC-H query 12 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	l_shipmode,
+	sum(case
+		when o_orderpriority = '1-URGENT'
+			or o_orderpriority = '2-HIGH'
+			then 1
+		else 0
+	end) as high_line_count,
+	sum(case
+		when o_orderpriority <> '1-URGENT'
+			and o_orderpriority <> '2-HIGH'
+			then 1
+		else 0
+	end) as low_line_count
+from
+	orders,
+	lineitem
+where
+	o_orderkey = l_orderkey
+	and l_shipmode in ('FOB', 'SHIP')
+	and l_commitdate < l_receiptdate
+	and l_shipdate < l_commitdate
+	and l_receiptdate >= date '1995-01-01'
+	and l_receiptdate < date '1995-01-01' + interval '1' year
+group by
+	l_shipmode
+order by
+	l_shipmode;
diff --git a/benchmarks/tpc/queries/tpch/q13.sql b/benchmarks/tpc/queries/tpch/q13.sql
new file mode 100644
index 0000000000..03c3f05818
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q13.sql
@@ -0,0 +1,22 @@
+-- CometBench-H query 13 derived from TPC-H query 13 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	c_count,
+	count(*) as custdist
+from
+	(
+		select
+			c_custkey,
+			count(o_orderkey)
+		from
+			customer left outer join orders on
+				c_custkey = o_custkey
+				and o_comment not like '%express%requests%'
+		group by
+			c_custkey
+	) as c_orders (c_custkey, c_count)
+group by
+	c_count
+order by
+	custdist desc,
+	c_count desc;
diff --git a/benchmarks/tpc/queries/tpch/q14.sql b/benchmarks/tpc/queries/tpch/q14.sql
new file mode 100644
index 0000000000..9f7b52e548
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q14.sql
@@ -0,0 +1,15 @@
+-- CometBench-H query 14 derived from TPC-H query 14 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	100.00 * sum(case
+		when p_type like 'PROMO%'
+			then l_extendedprice * (1 - l_discount)
+		else 0
+	end) / sum(l_extendedprice * (1 - l_discount)) as promo_revenue
+from
+	lineitem,
+	part
+where
+	l_partkey = p_partkey
+	and l_shipdate >= date '1995-02-01'
+	and l_shipdate < date '1995-02-01' + interval '1' month;
diff --git a/benchmarks/tpc/queries/tpch/q15.sql b/benchmarks/tpc/queries/tpch/q15.sql
new file mode 100644
index 0000000000..dda91adf7b
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q15.sql
@@ -0,0 +1,33 @@
+-- CometBench-H query 15 derived from TPC-H query 15 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+create view revenue0 (supplier_no, total_revenue) as
+	select
+		l_suppkey,
+		sum(l_extendedprice * (1 - l_discount))
+	from
+		lineitem
+	where
+		l_shipdate >= date '1996-08-01'
+		and l_shipdate < date '1996-08-01' + interval '3' month
+	group by
+		l_suppkey;
+select
+	s_suppkey,
+	s_name,
+	s_address,
+	s_phone,
+	total_revenue
+from
+	supplier,
+	revenue0
+where
+	s_suppkey = supplier_no
+	and total_revenue = (
+		select
+			max(total_revenue)
+		from
+			revenue0
+	)
+order by
+	s_suppkey;
+drop view revenue0;
diff --git a/benchmarks/tpc/queries/tpch/q16.sql b/benchmarks/tpc/queries/tpch/q16.sql
new file mode 100644
index 0000000000..6f6b023acb
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q16.sql
@@ -0,0 +1,32 @@
+-- CometBench-H query 16 derived from TPC-H query 16 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	p_brand,
+	p_type,
+	p_size,
+	count(distinct ps_suppkey) as supplier_cnt
+from
+	partsupp,
+	part
+where
+	p_partkey = ps_partkey
+	and p_brand <> 'Brand#14'
+	and p_type not like 'SMALL PLATED%'
+	and p_size in (14, 6, 5, 31, 49, 15, 41, 47)
+	and ps_suppkey not in (
+		select
+			s_suppkey
+		from
+			supplier
+		where
+			s_comment like '%Customer%Complaints%'
+	)
+group by
+	p_brand,
+	p_type,
+	p_size
+order by
+	supplier_cnt desc,
+	p_brand,
+	p_type,
+	p_size;
diff --git a/benchmarks/tpc/queries/tpch/q17.sql b/benchmarks/tpc/queries/tpch/q17.sql
new file mode 100644
index 0000000000..8b90e18002
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q17.sql
@@ -0,0 +1,19 @@
+-- CometBench-H query 17 derived from TPC-H query 17 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	sum(l_extendedprice) / 7.0 as avg_yearly
+from
+	lineitem,
+	part
+where
+	p_partkey = l_partkey
+	and p_brand = 'Brand#42'
+	and p_container = 'LG BAG'
+	and l_quantity < (
+		select
+			0.2 * avg(l_quantity)
+		from
+			lineitem
+		where
+			l_partkey = p_partkey
+	);
diff --git a/benchmarks/tpc/queries/tpch/q18.sql b/benchmarks/tpc/queries/tpch/q18.sql
new file mode 100644
index 0000000000..e0f733e088
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q18.sql
@@ -0,0 +1,34 @@
+-- CometBench-H query 18 derived from TPC-H query 18 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	c_name,
+	c_custkey,
+	o_orderkey,
+	o_orderdate,
+	o_totalprice,
+	sum(l_quantity)
+from
+	customer,
+	orders,
+	lineitem
+where
+	o_orderkey in (
+		select
+			l_orderkey
+		from
+			lineitem
+		group by
+			l_orderkey having
+				sum(l_quantity) > 313
+	)
+	and c_custkey = o_custkey
+	and o_orderkey = l_orderkey
+group by
+	c_name,
+	c_custkey,
+	o_orderkey,
+	o_orderdate,
+	o_totalprice
+order by
+	o_totalprice desc,
+	o_orderdate limit 100;
diff --git a/benchmarks/tpc/queries/tpch/q19.sql b/benchmarks/tpc/queries/tpch/q19.sql
new file mode 100644
index 0000000000..8777b2c887
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q19.sql
@@ -0,0 +1,37 @@
+-- CometBench-H query 19 derived from TPC-H query 19 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	sum(l_extendedprice* (1 - l_discount)) as revenue
+from
+	lineitem,
+	part
+where
+	(
+		p_partkey = l_partkey
+		and p_brand = 'Brand#21'
+		and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
+		and l_quantity >= 8 and l_quantity <= 8 + 10
+		and p_size between 1 and 5
+		and l_shipmode in ('AIR', 'AIR REG')
+		and l_shipinstruct = 'DELIVER IN PERSON'
+	)
+	or
+	(
+		p_partkey = l_partkey
+		and p_brand = 'Brand#13'
+		and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
+		and l_quantity >= 20 and l_quantity <= 20 + 10
+		and p_size between 1 and 10
+		and l_shipmode in ('AIR', 'AIR REG')
+		and l_shipinstruct = 'DELIVER IN PERSON'
+	)
+	or
+	(
+		p_partkey = l_partkey
+		and p_brand = 'Brand#52'
+		and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
+		and l_quantity >= 30 and l_quantity <= 30 + 10
+		and p_size between 1 and 15
+		and l_shipmode in ('AIR', 'AIR REG')
+		and l_shipinstruct = 'DELIVER IN PERSON'
+	);
diff --git a/benchmarks/tpc/queries/tpch/q2.sql b/benchmarks/tpc/queries/tpch/q2.sql
new file mode 100644
index 0000000000..947413fcf5
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q2.sql
@@ -0,0 +1,45 @@
+-- CometBench-H query 2 derived from TPC-H query 2 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	s_acctbal,
+	s_name,
+	n_name,
+	p_partkey,
+	p_mfgr,
+	s_address,
+	s_phone,
+	s_comment
+from
+	part,
+	supplier,
+	partsupp,
+	nation,
+	region
+where
+	p_partkey = ps_partkey
+	and s_suppkey = ps_suppkey
+	and p_size = 48
+	and p_type like '%TIN'
+	and s_nationkey = n_nationkey
+	and n_regionkey = r_regionkey
+	and r_name = 'ASIA'
+	and ps_supplycost = (
+		select
+			min(ps_supplycost)
+		from
+			partsupp,
+			supplier,
+			nation,
+			region
+		where
+			p_partkey = ps_partkey
+			and s_suppkey = ps_suppkey
+			and s_nationkey = n_nationkey
+			and n_regionkey = r_regionkey
+			and r_name = 'ASIA'
+	)
+order by
+	s_acctbal desc,
+	n_name,
+	s_name,
+	p_partkey limit 100;
diff --git a/benchmarks/tpc/queries/tpch/q20.sql b/benchmarks/tpc/queries/tpch/q20.sql
new file mode 100644
index 0000000000..d83bfcc696
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q20.sql
@@ -0,0 +1,39 @@
+-- CometBench-H query 20 derived from TPC-H query 20 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	s_name,
+	s_address
+from
+	supplier,
+	nation
+where
+	s_suppkey in (
+		select
+			ps_suppkey
+		from
+			partsupp
+		where
+			ps_partkey in (
+				select
+					p_partkey
+				from
+					part
+				where
+					p_name like 'blanched%'
+			)
+			and ps_availqty > (
+				select
+					0.5 * sum(l_quantity)
+				from
+					lineitem
+				where
+					l_partkey = ps_partkey
+					and l_suppkey = ps_suppkey
+					and l_shipdate >= date '1993-01-01'
+					and l_shipdate < date '1993-01-01' + interval '1' year
+			)
+	)
+	and s_nationkey = n_nationkey
+	and n_name = 'KENYA'
+order by
+	s_name;
diff --git a/benchmarks/tpc/queries/tpch/q21.sql b/benchmarks/tpc/queries/tpch/q21.sql
new file mode 100644
index 0000000000..ce6ade49a3
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q21.sql
@@ -0,0 +1,41 @@
+-- CometBench-H query 21 derived from TPC-H query 21 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	s_name,
+	count(*) as numwait
+from
+	supplier,
+	lineitem l1,
+	orders,
+	nation
+where
+	s_suppkey = l1.l_suppkey
+	and o_orderkey = l1.l_orderkey
+	and o_orderstatus = 'F'
+	and l1.l_receiptdate > l1.l_commitdate
+	and exists (
+		select
+			*
+		from
+			lineitem l2
+		where
+			l2.l_orderkey = l1.l_orderkey
+			and l2.l_suppkey <> l1.l_suppkey
+	)
+	and not exists (
+		select
+			*
+		from
+			lineitem l3
+		where
+			l3.l_orderkey = l1.l_orderkey
+			and l3.l_suppkey <> l1.l_suppkey
+			and l3.l_receiptdate > l3.l_commitdate
+	)
+	and s_nationkey = n_nationkey
+	and n_name = 'ARGENTINA'
+group by
+	s_name
+order by
+	numwait desc,
+	s_name limit 100;
diff --git a/benchmarks/tpc/queries/tpch/q22.sql b/benchmarks/tpc/queries/tpch/q22.sql
new file mode 100644
index 0000000000..012f1f698a
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q22.sql
@@ -0,0 +1,39 @@
+-- CometBench-H query 22 derived from TPC-H query 22 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	cntrycode,
+	count(*) as numcust,
+	sum(c_acctbal) as totacctbal
+from
+	(
+		select
+			substring(c_phone from 1 for 2) as cntrycode,
+			c_acctbal
+		from
+			customer
+		where
+			substring(c_phone from 1 for 2) in
+				('24', '34', '16', '30', '33', '14', '13')
+			and c_acctbal > (
+				select
+					avg(c_acctbal)
+				from
+					customer
+				where
+					c_acctbal > 0.00
+					and substring(c_phone from 1 for 2) in
+						('24', '34', '16', '30', '33', '14', '13')
+			)
+			and not exists (
+				select
+					*
+				from
+					orders
+				where
+					o_custkey = c_custkey
+			)
+	) as custsale
+group by
+	cntrycode
+order by
+	cntrycode;
diff --git a/benchmarks/tpc/queries/tpch/q3.sql b/benchmarks/tpc/queries/tpch/q3.sql
new file mode 100644
index 0000000000..e277402d88
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q3.sql
@@ -0,0 +1,24 @@
+-- CometBench-H query 3 derived from TPC-H query 3 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	l_orderkey,
+	sum(l_extendedprice * (1 - l_discount)) as revenue,
+	o_orderdate,
+	o_shippriority
+from
+	customer,
+	orders,
+	lineitem
+where
+	c_mktsegment = 'BUILDING'
+	and c_custkey = o_custkey
+	and l_orderkey = o_orderkey
+	and o_orderdate < date '1995-03-15'
+	and l_shipdate > date '1995-03-15'
+group by
+	l_orderkey,
+	o_orderdate,
+	o_shippriority
+order by
+	revenue desc,
+	o_orderdate limit 10;
diff --git a/benchmarks/tpc/queries/tpch/q4.sql b/benchmarks/tpc/queries/tpch/q4.sql
new file mode 100644
index 0000000000..814ea8a2ec
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q4.sql
@@ -0,0 +1,23 @@
+-- CometBench-H query 4 derived from TPC-H query 4 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	o_orderpriority,
+	count(*) as order_count
+from
+	orders
+where
+	o_orderdate >= date '1995-04-01'
+	and o_orderdate < date '1995-04-01' + interval '3' month
+	and exists (
+		select
+			*
+		from
+			lineitem
+		where
+			l_orderkey = o_orderkey
+			and l_commitdate < l_receiptdate
+	)
+group by
+	o_orderpriority
+order by
+	o_orderpriority;
diff --git a/benchmarks/tpc/queries/tpch/q5.sql b/benchmarks/tpc/queries/tpch/q5.sql
new file mode 100644
index 0000000000..5c462c397b
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q5.sql
@@ -0,0 +1,26 @@
+-- CometBench-H query 5 derived from TPC-H query 5 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	n_name,
+	sum(l_extendedprice * (1 - l_discount)) as revenue
+from
+	customer,
+	orders,
+	lineitem,
+	supplier,
+	nation,
+	region
+where
+	c_custkey = o_custkey
+	and l_orderkey = o_orderkey
+	and l_suppkey = s_suppkey
+	and c_nationkey = s_nationkey
+	and s_nationkey = n_nationkey
+	and n_regionkey = r_regionkey
+	and r_name = 'AFRICA'
+	and o_orderdate >= date '1994-01-01'
+	and o_orderdate < date '1994-01-01' + interval '1' year
+group by
+	n_name
+order by
+	revenue desc;
diff --git a/benchmarks/tpc/queries/tpch/q6.sql b/benchmarks/tpc/queries/tpch/q6.sql
new file mode 100644
index 0000000000..22b92f4e91
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q6.sql
@@ -0,0 +1,11 @@
+-- CometBench-H query 6 derived from TPC-H query 6 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	sum(l_extendedprice * l_discount) as revenue
+from
+	lineitem
+where
+	l_shipdate >= date '1994-01-01'
+	and l_shipdate < date '1994-01-01' + interval '1' year
+	and l_discount between 0.04 - 0.01 and 0.04 + 0.01
+	and l_quantity < 24;
diff --git a/benchmarks/tpc/queries/tpch/q7.sql b/benchmarks/tpc/queries/tpch/q7.sql
new file mode 100644
index 0000000000..26b4078ffc
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q7.sql
@@ -0,0 +1,41 @@
+-- CometBench-H query 7 derived from TPC-H query 7 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	supp_nation,
+	cust_nation,
+	l_year,
+	sum(volume) as revenue
+from
+	(
+		select
+			n1.n_name as supp_nation,
+			n2.n_name as cust_nation,
+			extract(year from l_shipdate) as l_year,
+			l_extendedprice * (1 - l_discount) as volume
+		from
+			supplier,
+			lineitem,
+			orders,
+			customer,
+			nation n1,
+			nation n2
+		where
+			s_suppkey = l_suppkey
+			and o_orderkey = l_orderkey
+			and c_custkey = o_custkey
+			and s_nationkey = n1.n_nationkey
+			and c_nationkey = n2.n_nationkey
+			and (
+				(n1.n_name = 'GERMANY' and n2.n_name = 'IRAQ')
+				or (n1.n_name = 'IRAQ' and n2.n_name = 'GERMANY')
+			)
+			and l_shipdate between date '1995-01-01' and date '1996-12-31'
+	) as shipping
+group by
+	supp_nation,
+	cust_nation,
+	l_year
+order by
+	supp_nation,
+	cust_nation,
+	l_year;
diff --git a/benchmarks/tpc/queries/tpch/q8.sql b/benchmarks/tpc/queries/tpch/q8.sql
new file mode 100644
index 0000000000..c0ac2ecf16
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q8.sql
@@ -0,0 +1,39 @@
+-- CometBench-H query 8 derived from TPC-H query 8 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	o_year,
+	sum(case
+		when nation = 'IRAQ' then volume
+		else 0
+	end) / sum(volume) as mkt_share
+from
+	(
+		select
+			extract(year from o_orderdate) as o_year,
+			l_extendedprice * (1 - l_discount) as volume,
+			n2.n_name as nation
+		from
+			part,
+			supplier,
+			lineitem,
+			orders,
+			customer,
+			nation n1,
+			nation n2,
+			region
+		where
+			p_partkey = l_partkey
+			and s_suppkey = l_suppkey
+			and l_orderkey = o_orderkey
+			and o_custkey = c_custkey
+			and c_nationkey = n1.n_nationkey
+			and n1.n_regionkey = r_regionkey
+			and r_name = 'MIDDLE EAST'
+			and s_nationkey = n2.n_nationkey
+			and o_orderdate between date '1995-01-01' and date '1996-12-31'
+			and p_type = 'LARGE PLATED STEEL'
+	) as all_nations
+group by
+	o_year
+order by
+	o_year;
diff --git a/benchmarks/tpc/queries/tpch/q9.sql b/benchmarks/tpc/queries/tpch/q9.sql
new file mode 100644
index 0000000000..ab525c371e
--- /dev/null
+++ b/benchmarks/tpc/queries/tpch/q9.sql
@@ -0,0 +1,34 @@
+-- CometBench-H query 9 derived from TPC-H query 9 under the terms of the TPC Fair Use Policy.
+-- TPC-H queries are Copyright 1993-2022 Transaction Processing Performance Council.
+select
+	nation,
+	o_year,
+	sum(amount) as sum_profit
+from
+	(
+		select
+			n_name as nation,
+			extract(year from o_orderdate) as o_year,
+			l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity as amount
+		from
+			part,
+			supplier,
+			lineitem,
+			partsupp,
+			orders,
+			nation
+		where
+			s_suppkey = l_suppkey
+			and ps_suppkey = l_suppkey
+			and ps_partkey = l_partkey
+			and p_partkey = l_partkey
+			and o_orderkey = l_orderkey
+			and s_nationkey = n_nationkey
+			and p_name like '%moccasin%'
+	) as profit
+group by
+	nation,
+	o_year
+order by
+	nation,
+	o_year desc;
diff --git a/benchmarks/tpc/requirements.txt b/benchmarks/tpc/requirements.txt
new file mode 100644
index 0000000000..48f63d718f
--- /dev/null
+++ b/benchmarks/tpc/requirements.txt
@@ -0,0 +1 @@
+pyspark==3.5.2
diff --git a/benchmarks/tpc/run.py b/benchmarks/tpc/run.py
new file mode 100755
index 0000000000..6cd10636ba
--- /dev/null
+++ b/benchmarks/tpc/run.py
@@ -0,0 +1,411 @@
+#!/usr/bin/env python3
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""Consolidated TPC benchmark runner for Spark-based engines.
+
+Usage:
+    python3 run.py --engine comet --benchmark tpch
+    python3 run.py --engine comet --benchmark tpcds --iterations 3
+    python3 run.py --engine comet-iceberg --benchmark tpch
+    python3 run.py --engine comet --benchmark tpch --dry-run
+    python3 run.py --engine spark --benchmark tpch --no-restart
+"""
+
+import argparse
+import os
+import re
+import subprocess
+import sys
+
+# ---------------------------------------------------------------------------
+# TOML loading – prefer stdlib tomllib (3.11+), else minimal fallback
+# ---------------------------------------------------------------------------
+
+try:
+    import tomllib  # Python 3.11+
+
+    def load_toml(path):
+        with open(path, "rb") as f:
+            return tomllib.load(f)
+
+except ModuleNotFoundError:
+
+    def _parse_toml(text):
+        """Minimal TOML parser supporting tables, quoted-key strings, plain
+        strings, arrays of strings, booleans, and comments.  Sufficient for
+        the engine config files used by this runner."""
+        root = {}
+        current = root
+        for line in text.splitlines():
+            line = line.strip()
+            if not line or line.startswith("#"):
+                continue
+            # Table header: [env.defaults] or [spark_conf]
+            m = re.match(r"^\[([^\]]+)\]$", line)
+            if m:
+                keys = m.group(1).split(".")
+                current = root
+                for k in keys:
+                    current = current.setdefault(k, {})
+                continue
+            # Key = value
+            m = re.match(r'^("(?:[^"\\]|\\.)*"|[A-Za-z0-9_.]+)\s*=\s*(.+)$', line)
+            if not m:
+                continue
+            raw_key, raw_val = m.group(1), m.group(2).strip()
+            key = raw_key.strip('"')
+            val = _parse_value(raw_val)
+            current[key] = val
+        return root
+
+    def _parse_value(raw):
+        if raw == "true":
+            return True
+        if raw == "false":
+            return False
+        if raw.startswith('"') and raw.endswith('"'):
+            return raw[1:-1]
+        if raw.startswith("["):
+            # Simple array of strings
+            items = []
+            for m in re.finditer(r'"((?:[^"\\]|\\.)*)"', raw):
+                items.append(m.group(1))
+            return items
+        if raw.startswith("{"):
+            # Inline table: { KEY = "VAL", ... }
+            tbl = {}
+            for m in re.finditer(r'([A-Za-z0-9_]+)\s*=\s*"((?:[^"\\]|\\.)*)"', raw):
+                tbl[m.group(1)] = m.group(2)
+            return tbl
+        return raw
+
+    def load_toml(path):
+        with open(path, "r") as f:
+            return _parse_toml(f.read())
+
+
+# ---------------------------------------------------------------------------
+# Common Spark configuration (shared across all engines)
+# ---------------------------------------------------------------------------
+
+COMMON_SPARK_CONF = {
+    "spark.driver.memory": "8G",
+    "spark.executor.memory": "16g",
+    "spark.memory.offHeap.enabled": "true",
+    "spark.memory.offHeap.size": "16g",
+    "spark.eventLog.enabled": "true",
+    "spark.hadoop.fs.s3a.impl": "org.apache.hadoop.fs.s3a.S3AFileSystem",
+    "spark.hadoop.fs.s3a.aws.credentials.provider": "com.amazonaws.auth.DefaultAWSCredentialsProviderChain",
+}
+
+# ---------------------------------------------------------------------------
+# Benchmark profiles
+# ---------------------------------------------------------------------------
+
+BENCHMARK_PROFILES = {
+    "tpch": {
+        "executor_instances": "2",
+        "executor_cores": "8",
+        "max_cores": "16",
+        "data_env": "TPCH_DATA",
+        "format": "parquet",
+    },
+    "tpcds": {
+        "executor_instances": "2",
+        "executor_cores": "8",
+        "max_cores": "16",
+        "data_env": "TPCDS_DATA",
+        "format": None,  # omit --format for TPC-DS
+    },
+}
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+def resolve_env(value):
+    """Expand $VAR and ${VAR} references using os.environ."""
+    if not isinstance(value, str):
+        return value
+    return re.sub(
+        r"\$\{([^}]+)\}|\$([A-Za-z_][A-Za-z0-9_]*)",
+        lambda m: os.environ.get(m.group(1) or m.group(2), ""),
+        value,
+    )
+
+
+def resolve_env_in_list(lst):
+    return [resolve_env(v) for v in lst]
+
+
+def load_engine_config(engine_name):
+    """Load and return the TOML config for the given engine."""
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    config_path = os.path.join(script_dir, "engines", f"{engine_name}.toml")
+    if not os.path.exists(config_path):
+        available = sorted(
+            f.removesuffix(".toml")
+            for f in os.listdir(os.path.join(script_dir, "engines"))
+            if f.endswith(".toml")
+        )
+        print(f"Error: Unknown engine '{engine_name}'", file=sys.stderr)
+        print(f"Available engines: {', '.join(available)}", file=sys.stderr)
+        sys.exit(1)
+    return load_toml(config_path)
+
+
+def apply_env_defaults(config):
+    """Set environment variable defaults from [env.defaults]."""
+    defaults = config.get("env", {}).get("defaults", {})
+    for key, val in defaults.items():
+        if key not in os.environ:
+            os.environ[key] = val
+
+
+def apply_env_exports(config):
+    """Export environment variables from [env.exports]."""
+    exports = config.get("env", {}).get("exports", {})
+    for key, val in exports.items():
+        os.environ[key] = val
+
+
+def check_required_env(config):
+    """Validate that required environment variables are set."""
+    required = config.get("env", {}).get("required", [])
+    missing = [v for v in required if not os.environ.get(v)]
+    if missing:
+        print(
+            f"Error: Required environment variable(s) not set: {', '.join(missing)}",
+            file=sys.stderr,
+        )
+        sys.exit(1)
+
+
+def check_common_env():
+    """Validate SPARK_HOME and SPARK_MASTER are set."""
+    for var in ("SPARK_HOME", "SPARK_MASTER"):
+        if not os.environ.get(var):
+            print(f"Error: {var} is not set", file=sys.stderr)
+            sys.exit(1)
+
+
+def check_benchmark_env(config, benchmark):
+    """Validate benchmark-specific environment variables."""
+    profile = BENCHMARK_PROFILES[benchmark]
+    use_iceberg = config.get("tpcbench_args", {}).get("use_iceberg", False)
+
+    required = []
+    if not use_iceberg:
+        required.append(profile["data_env"])
+
+    missing = [v for v in required if not os.environ.get(v)]
+    if missing:
+        print(
+            f"Error: Required environment variable(s) not set for "
+            f"{benchmark}: {', '.join(missing)}",
+            file=sys.stderr,
+        )
+        sys.exit(1)
+
+    # Default ICEBERG_DATABASE to the benchmark name if not already set
+    if use_iceberg and not os.environ.get("ICEBERG_DATABASE"):
+        os.environ["ICEBERG_DATABASE"] = benchmark
+
+
+def build_spark_submit_cmd(config, benchmark, args):
+    """Build the spark-submit command list."""
+    spark_home = os.environ["SPARK_HOME"]
+    spark_master = os.environ["SPARK_MASTER"]
+    profile = BENCHMARK_PROFILES[benchmark]
+
+    cmd = [os.path.join(spark_home, "bin", "spark-submit")]
+    cmd += ["--master", spark_master]
+
+    # --jars
+    jars = config.get("spark_submit", {}).get("jars", [])
+    if jars:
+        cmd += ["--jars", ",".join(resolve_env_in_list(jars))]
+
+    # --driver-class-path
+    driver_cp = config.get("spark_submit", {}).get("driver_class_path", [])
+    if driver_cp:
+        cmd += ["--driver-class-path", ":".join(resolve_env_in_list(driver_cp))]
+
+    # Merge spark confs: common + benchmark profile + engine overrides
+    conf = dict(COMMON_SPARK_CONF)
+    conf["spark.executor.instances"] = profile["executor_instances"]
+    conf["spark.executor.cores"] = profile["executor_cores"]
+    conf["spark.cores.max"] = profile["max_cores"]
+
+    engine_conf = config.get("spark_conf", {})
+    for key, val in engine_conf.items():
+        if isinstance(val, bool):
+            val = "true" if val else "false"
+        conf[resolve_env(key)] = resolve_env(str(val))
+
+    for key, val in sorted(conf.items()):
+        cmd += ["--conf", f"{key}={val}"]
+
+    # tpcbench.py path
+    cmd.append("tpcbench.py")
+
+    # tpcbench args
+    engine_name = config.get("engine", {}).get("name", args.engine)
+    cmd += ["--name", engine_name]
+    cmd += ["--benchmark", benchmark]
+
+    use_iceberg = config.get("tpcbench_args", {}).get("use_iceberg", False)
+    if use_iceberg:
+        cmd += ["--catalog", resolve_env("${ICEBERG_CATALOG}")]
+        cmd += ["--database", resolve_env("${ICEBERG_DATABASE}")]
+    else:
+        data_var = profile["data_env"]
+        data_val = os.environ.get(data_var, "")
+        cmd += ["--data", data_val]
+
+    cmd += ["--output", args.output]
+    cmd += ["--iterations", str(args.iterations)]
+
+    if args.query is not None:
+        cmd += ["--query", str(args.query)]
+
+    if profile["format"] and not use_iceberg:
+        cmd += ["--format", profile["format"]]
+
+    if args.profile:
+        cmd += ["--profile"]
+        cmd += ["--profile-interval", str(args.profile_interval)]
+
+    return cmd
+
+
+def restart_spark():
+    """Stop and start Spark master and worker."""
+    spark_home = os.environ["SPARK_HOME"]
+    sbin = os.path.join(spark_home, "sbin")
+    spark_master = os.environ["SPARK_MASTER"]
+
+    # Stop (ignore errors)
+    subprocess.run(
+        [os.path.join(sbin, "stop-master.sh")],
+        stdout=subprocess.DEVNULL,
+        stderr=subprocess.DEVNULL,
+    )
+    subprocess.run(
+        [os.path.join(sbin, "stop-worker.sh")],
+        stdout=subprocess.DEVNULL,
+        stderr=subprocess.DEVNULL,
+    )
+
+    # Start (check errors)
+    r = subprocess.run([os.path.join(sbin, "start-master.sh")])
+    if r.returncode != 0:
+        print("Error: Failed to start Spark master", file=sys.stderr)
+        sys.exit(1)
+
+    r = subprocess.run([os.path.join(sbin, "start-worker.sh"), spark_master])
+    if r.returncode != 0:
+        print("Error: Failed to start Spark worker", file=sys.stderr)
+        sys.exit(1)
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Consolidated TPC benchmark runner for Spark-based engines."
+    )
+    parser.add_argument(
+        "--engine",
+        required=True,
+        help="Engine name (matches a TOML file in engines/)",
+    )
+    parser.add_argument(
+        "--benchmark",
+        required=True,
+        choices=["tpch", "tpcds"],
+        help="Benchmark to run",
+    )
+    parser.add_argument(
+        "--iterations", type=int, default=1, help="Number of iterations (default: 1)"
+    )
+    parser.add_argument(
+        "--output", default=".", help="Output directory (default: .)"
+    )
+    parser.add_argument(
+        "--query", type=int, default=None, help="Run a single query number"
+    )
+    parser.add_argument(
+        "--no-restart",
+        action="store_true",
+        help="Skip Spark master/worker restart",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Print the spark-submit command without executing",
+    )
+    parser.add_argument(
+        "--profile",
+        action="store_true",
+        help="Enable executor metrics profiling via Spark REST API",
+    )
+    parser.add_argument(
+        "--profile-interval",
+        type=float,
+        default=2.0,
+        help="Profiling poll interval in seconds (default: 2.0)",
+    )
+    args = parser.parse_args()
+
+    config = load_engine_config(args.engine)
+
+    # Apply env defaults and exports before validation
+    apply_env_defaults(config)
+    apply_env_exports(config)
+
+    check_common_env()
+    check_required_env(config)
+    check_benchmark_env(config, args.benchmark)
+
+    # Restart Spark unless --no-restart or --dry-run
+    if not args.no_restart and not args.dry_run:
+        restart_spark()
+
+    cmd = build_spark_submit_cmd(config, args.benchmark, args)
+
+    if args.dry_run:
+        # Group paired arguments (e.g. --conf key=value) on one line
+        parts = []
+        i = 0
+        while i < len(cmd):
+            token = cmd[i]
+            if token.startswith("--") and i + 1 < len(cmd) and not cmd[i + 1].startswith("--"):
+                parts.append(f"{token} {cmd[i + 1]}")
+                i += 2
+            else:
+                parts.append(token)
+                i += 1
+        print(" \\\n    ".join(parts))
+    else:
+        r = subprocess.run(cmd)
+        sys.exit(r.returncode)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/dev/benchmarks/tpcbench.py b/benchmarks/tpc/tpcbench.py
similarity index 87%
rename from dev/benchmarks/tpcbench.py
rename to benchmarks/tpc/tpcbench.py
index 400ccd175a..1ff54ed3c7 100644
--- a/dev/benchmarks/tpcbench.py
+++ b/benchmarks/tpc/tpcbench.py
@@ -26,6 +26,7 @@
 import argparse
 from datetime import datetime
 import json
+import os
 from pyspark.sql import SparkSession
 import time
 from typing import Dict
@@ -50,22 +51,33 @@ def main(
     data_path: str,
     catalog: str,
     database: str,
-    query_path: str,
     iterations: int,
     output: str,
     name: str,
     format: str,
     query_num: int = None,
     write_path: str = None,
-    options: Dict[str, str] = None
+    options: Dict[str, str] = None,
+    profile: bool = False,
+    profile_interval: float = 2.0,
 ):
     if options is None:
         options = {}
 
+    query_path = os.path.join(
+        os.path.dirname(os.path.abspath(__file__)), "queries", benchmark
+    )
+
     spark = SparkSession.builder \
         .appName(f"{name} benchmark derived from {benchmark}") \
         .getOrCreate()
 
+    profiler = None
+    if profile:
+        from profiling import SparkMetricsProfiler
+        profiler = SparkMetricsProfiler(spark, interval_secs=profile_interval)
+        profiler.start()
+
     # Define tables for each benchmark
     if benchmark == "tpch":
         num_queries = 22
@@ -94,7 +106,10 @@ def main(
             print(f"Registering table {table} from {source}")
             df = spark.table(source)
         else:
+            # Support both "customer/" and "customer.parquet/" layouts
             source = f"{data_path}/{table}.{format}"
+            if not os.path.exists(source):
+                source = f"{data_path}/{table}"
             print(f"Registering table {table} from {source}")
             df = spark.read.format(format).options(**options).load(source)
         df.createOrReplaceTempView(table)
@@ -104,7 +119,6 @@ def main(
     results = {
         'engine': 'datafusion-comet',
         'benchmark': benchmark,
-        'query_path': query_path,
         'spark_conf': conf_dict,
     }
     if using_iceberg:
@@ -176,6 +190,12 @@ def main(
     with open(results_path, "w") as f:
         f.write(result_str)
 
+    if profiler is not None:
+        profiler.stop()
+        metrics_path = f"{output}/{name}-{benchmark}-metrics.csv"
+        profiler.write_csv(metrics_path)
+        profiler.snapshot_cgroup_metrics(output, name, benchmark)
+
     spark.stop()
 
 
@@ -215,10 +235,6 @@ def main(
         help="Database containing TPC tables (only used with --catalog)"
     )
 
-    parser.add_argument(
-        "--queries", required=True,
-        help="Path to query SQL files"
-    )
     parser.add_argument(
         "--iterations", type=int, default=1,
         help="Number of iterations"
@@ -239,6 +255,14 @@ def main(
         "--write",
         help="Path to save query results as Parquet"
     )
+    parser.add_argument(
+        "--profile", action="store_true",
+        help="Enable executor metrics profiling via Spark REST API"
+    )
+    parser.add_argument(
+        "--profile-interval", type=float, default=2.0,
+        help="Profiling poll interval in seconds (default: 2.0)"
+    )
     args = parser.parse_args()
 
     main(
@@ -246,12 +270,13 @@ def main(
         args.data,
         args.catalog,
         args.database,
-        args.queries,
         args.iterations,
         args.output,
         args.name,
         args.format,
         args.query,
         args.write,
-        args.options
+        args.options,
+        args.profile,
+        args.profile_interval,
     )
diff --git a/benchmarks/tpc/visualize-metrics.py b/benchmarks/tpc/visualize-metrics.py
new file mode 100644
index 0000000000..4859265135
--- /dev/null
+++ b/benchmarks/tpc/visualize-metrics.py
@@ -0,0 +1,403 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import argparse
+import csv
+import os
+from collections import defaultdict
+
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+
+
+# Stable colors: driver=blue, executor-0/worker-1=orange, executor-1/worker-2=green
+ENTITY_COLORS = {
+    'driver': 'tab:blue',
+    '0': 'tab:orange',
+    '1': 'tab:green',
+    '2': 'tab:red',
+    '3': 'tab:purple',
+    'worker-1': 'tab:orange',
+    'worker-2': 'tab:green',
+}
+
+DEFAULT_COLORS = ['tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink']
+
+PEAK_SERIES = [
+    ('peak_JVMHeapMemory', 'Heap', 'solid', 'tab:blue'),
+    ('peak_JVMOffHeapMemory', 'OffHeap', 'solid', 'tab:orange'),
+    ('peak_OffHeapExecutionMemory', 'OffHeapExec', 'solid', 'tab:red'),
+]
+
+PEAK_BAR_FIELDS = [
+    'peak_JVMHeapMemory',
+    'peak_JVMOffHeapMemory',
+    'peak_OnHeapExecutionMemory',
+    'peak_OffHeapExecutionMemory',
+]
+
+
+def color_for(entity_id):
+    """Return a stable color for the given entity identifier."""
+    if entity_id in ENTITY_COLORS:
+        return ENTITY_COLORS[entity_id]
+    # Hash-based fallback for unknown entities
+    idx = hash(entity_id) % len(DEFAULT_COLORS)
+    return DEFAULT_COLORS[idx]
+
+
+def auto_unit(max_bytes):
+    """Pick MB or GB and return (divisor, label)."""
+    if max_bytes > 1e9:
+        return 1e9, 'GB'
+    return 1e6, 'MB'
+
+
+def load_jvm_metrics(path):
+    """Load JVM metrics CSV and return data grouped by executor_id."""
+    data = defaultdict(lambda: defaultdict(list))
+    with open(path, newline='') as f:
+        reader = csv.DictReader(f)
+        for row in reader:
+            eid = row['executor_id']
+            for key, val in row.items():
+                if key == 'executor_id':
+                    data[eid][key].append(val)
+                elif key == 'is_active':
+                    data[eid][key].append(val == 'True')
+                else:
+                    data[eid][key].append(float(val))
+    return data
+
+
+def load_cgroup_metrics(path, label):
+    """Load a cgroup metrics CSV and return dict with lists of values."""
+    data = {'label': label}
+    with open(path, newline='') as f:
+        reader = csv.DictReader(f)
+        rows = list(reader)
+    if not rows:
+        return data
+    timestamps = [float(r['timestamp_ms']) for r in rows]
+    data['timestamp_ms'] = timestamps
+    min_ts = min(timestamps)
+    data['elapsed_secs'] = [(ts - min_ts) / 1000.0 for ts in timestamps]
+    for key in ['memory_usage_bytes', 'memory_limit_bytes', 'rss_bytes', 'cache_bytes', 'swap_bytes']:
+        if key in rows[0]:
+            data[key] = [float(r[key]) for r in rows]
+    return data
+
+
+def _shared_time_zero(jvm_data, cgroup_datasets):
+    """Compute the global time-zero from absolute timestamps across both sources.
+
+    Returns ``t_zero`` (ms) or ``None`` if absolute timestamps are unavailable.
+    """
+    exec_data = {eid: s for eid, s in jvm_data.items() if eid != 'driver'}
+    has_jvm_ts = any('timestamp_ms' in s for s in exec_data.values())
+    has_cg_ts = any('timestamp_ms' in ds for ds in cgroup_datasets)
+    if not (has_jvm_ts and has_cg_ts):
+        return None
+    all_abs = []
+    for s in exec_data.values():
+        all_abs.extend(s['timestamp_ms'])
+    for ds in cgroup_datasets:
+        all_abs.extend(ds.get('timestamp_ms', []))
+    return min(all_abs)
+
+
+def _jvm_time_range(jvm_data, cgroup_datasets):
+    """Compute the x-axis limits from JVM data using absolute timestamps.
+
+    Returns ``(x_min, x_max)`` — the elapsed-time window (in seconds, relative
+    to the global time-zero across both data sources) during which the JVM
+    profiler was active, or ``None`` if absolute timestamps are not available.
+    """
+    t_zero = _shared_time_zero(jvm_data, cgroup_datasets)
+    if t_zero is None:
+        return None
+    exec_data = {eid: s for eid, s in jvm_data.items() if eid != 'driver'}
+    jvm_min = float('inf')
+    jvm_max = 0
+    for s in exec_data.values():
+        jvm_min = min(jvm_min, min(s['timestamp_ms']))
+        jvm_max = max(jvm_max, max(s['timestamp_ms']))
+    return ((jvm_min - t_zero) / 1000.0, (jvm_max - t_zero) / 1000.0)
+
+
+def generate_jvm_memory_usage(jvm_data, output_dir, title):
+    """Generate one JVM peak-memory time-series chart per executor (driver excluded)."""
+    executors = {eid: s for eid, s in jvm_data.items() if eid != 'driver'}
+    if not executors:
+        print('  Skipped jvm_memory (no executor data)')
+        return
+
+    for eid, series in sorted(executors.items()):
+        all_values = []
+        for field, _, _, _ in PEAK_SERIES:
+            all_values.extend(series.get(field, []))
+        if not all_values or max(all_values) == 0:
+            print(f'  Skipped jvm_memory_executor_{eid}.png (all peak values are zero)')
+            continue
+
+        divisor, unit = auto_unit(max(all_values))
+
+        fig, ax = plt.subplots(figsize=(14, 6))
+        for field, label, ls, color in PEAK_SERIES:
+            vals = series.get(field, [])
+            if vals and max(vals) > 0:
+                ax.plot(series['elapsed_secs'],
+                        [v / divisor for v in vals],
+                        color=color, linestyle=ls, linewidth=1.5,
+                        label=label)
+
+        suffix = f' — Executor {eid} JVM Peak Memory' if title else f'Executor {eid} JVM Peak Memory'
+        ax.set_title(f'{title}{suffix}')
+        ax.set_xlabel('Elapsed Time (seconds)')
+        ax.set_ylabel(f'Peak Memory ({unit})')
+        ax.legend(fontsize=8)
+        ax.yaxis.grid(True)
+        plt.tight_layout()
+        fname = f'jvm_memory_executor_{eid}.png'
+        plt.savefig(os.path.join(output_dir, fname), format='png')
+        plt.close(fig)
+        print(f'  Created {fname}')
+
+
+def generate_jvm_peak_memory(jvm_data, output_dir, title):
+    """Peak memory breakdown per executor, excluding driver (grouped bar)."""
+    executor_data = {eid: s for eid, s in jvm_data.items() if eid != 'driver'}
+
+    # Check if all peak values are zero — skip chart if so
+    all_zero = True
+    for eid, series in executor_data.items():
+        for field in PEAK_BAR_FIELDS:
+            if field in series and max(series[field]) > 0:
+                all_zero = False
+                break
+        if not all_zero:
+            break
+    if all_zero:
+        print('  Skipped jvm_peak_memory.png (all peak values are zero)')
+        return
+
+    executors = sorted(executor_data.keys())
+    # Use the max of each peak field per executor
+    peak_values = {}
+    all_vals = []
+    for eid in executors:
+        peak_values[eid] = {}
+        for field in PEAK_BAR_FIELDS:
+            val = max(executor_data[eid].get(field, [0]))
+            peak_values[eid][field] = val
+            all_vals.append(val)
+
+    divisor, unit = auto_unit(max(all_vals)) if all_vals else (1e6, 'MB')
+
+    import numpy as np
+    x = np.arange(len(executors))
+    n_fields = len(PEAK_BAR_FIELDS)
+    bar_width = 0.8 / n_fields
+    field_colors = ['tab:blue', 'tab:orange', 'tab:green', 'tab:red']
+
+    fig, ax = plt.subplots(figsize=(max(8, len(executors) * 2), 6))
+    for i, field in enumerate(PEAK_BAR_FIELDS):
+        vals = [peak_values[eid][field] / divisor for eid in executors]
+        short_label = field.replace('peak_', '')
+        ax.bar(x + i * bar_width, vals, bar_width, label=short_label, color=field_colors[i])
+
+    ax.set_title(f'{title} — JVM Peak Memory' if title else 'JVM Peak Memory')
+    ax.set_xlabel('Executor')
+    ax.set_ylabel(f'Peak Memory ({unit})')
+    ax.set_xticks(x + bar_width * (n_fields - 1) / 2)
+    ax.set_xticklabels([f'executor {eid}' for eid in executors])
+    ax.legend(fontsize=8)
+    ax.yaxis.grid(True)
+    plt.tight_layout()
+    plt.savefig(os.path.join(output_dir, 'jvm_peak_memory.png'), format='png')
+    plt.close(fig)
+    print(f'  Created jvm_peak_memory.png')
+
+
+def generate_cgroup_memory(cgroup_datasets, jvm_data, output_dir, title):
+    """Generate one cgroup memory chart per worker."""
+    jvm_range = _jvm_time_range(jvm_data, cgroup_datasets)
+    t_zero = _shared_time_zero(jvm_data, cgroup_datasets)
+
+    for ds in cgroup_datasets:
+        label = ds['label']
+        c = color_for(label)
+
+        if t_zero is not None and 'timestamp_ms' in ds:
+            elapsed = [(t - t_zero) / 1000.0 for t in ds['timestamp_ms']]
+        else:
+            elapsed = ds.get('elapsed_secs', [])
+
+        all_values = []
+        all_values.extend(ds.get('memory_usage_bytes', []))
+        all_values.extend(ds.get('rss_bytes', []))
+        if not all_values:
+            continue
+
+        divisor, unit = auto_unit(max(all_values))
+
+        fig, ax = plt.subplots(figsize=(14, 6))
+        if 'memory_usage_bytes' in ds:
+            ax.plot(elapsed,
+                    [v / divisor for v in ds['memory_usage_bytes']],
+                    color='tab:blue', linewidth=1.5, label='usage')
+        if 'rss_bytes' in ds:
+            ax.plot(elapsed,
+                    [v / divisor for v in ds['rss_bytes']],
+                    color='tab:orange', linewidth=1.5, label='RSS')
+
+        if jvm_range is not None:
+            x_min, x_max = jvm_range
+            ax.set_xlim(left=x_min, right=x_max * 1.02)
+
+        suffix = f' — {label} Container Memory (cgroup)'
+        ax.set_title(f'{title}{suffix}' if title else suffix.lstrip(' — '))
+        ax.set_xlabel('Elapsed Time (seconds)')
+        ax.set_ylabel(f'Memory ({unit})')
+        ax.legend(fontsize=8)
+        ax.yaxis.grid(True)
+        plt.tight_layout()
+        fname = f'cgroup_memory_{label}.png'
+        plt.savefig(os.path.join(output_dir, fname), format='png')
+        plt.close(fig)
+        print(f'  Created {fname}')
+
+
+def generate_combined_memory(jvm_data, cgroup_datasets, cgroup_offset, output_dir, title):
+    """Generate one combined log-scale chart per worker, pairing executor N with worker-(N+1)."""
+    exec_data = {eid: s for eid, s in jvm_data.items() if eid != 'driver'}
+    t_zero = _shared_time_zero(jvm_data, cgroup_datasets)
+    jvm_range = _jvm_time_range(jvm_data, cgroup_datasets)
+
+    # Build elapsed-time helpers
+    if t_zero is not None:
+        def jvm_elapsed(series):
+            return [(t - t_zero) / 1000.0 for t in series['timestamp_ms']]
+        def cg_elapsed(ds):
+            return [(t - t_zero) / 1000.0 for t in ds['timestamp_ms']]
+    else:
+        def jvm_elapsed(series):
+            return series['elapsed_secs']
+        def cg_elapsed(ds):
+            elapsed = ds.get('elapsed_secs', [])
+            if cgroup_offset != 0:
+                return [t + cgroup_offset for t in elapsed]
+            return elapsed
+
+    # Pair executor IDs with cgroup datasets by index:
+    # sorted executors ['0','1'] map to cgroup_datasets [worker-1, worker-2]
+    sorted_eids = sorted(exec_data.keys())
+
+    for idx, ds in enumerate(cgroup_datasets):
+        label = ds['label']
+        eid = sorted_eids[idx] if idx < len(sorted_eids) else None
+
+        fig, ax = plt.subplots(figsize=(14, 6))
+
+        # All series plotted in GB on a single log-scale axis
+        divisor = 1e9
+        unit = 'GB'
+
+        # --- JVM: peak memory for this executor ---
+        if eid is not None:
+            series = exec_data[eid]
+            for field, flabel, ls, color in PEAK_SERIES:
+                vals = series.get(field, [])
+                if vals and max(vals) > 0:
+                    ax.plot(jvm_elapsed(series),
+                            [v / divisor for v in vals],
+                            color=color, linestyle=ls, linewidth=1.5,
+                            label=f'JVM {flabel}')
+
+        # --- Cgroup: usage for this worker ---
+        if 'memory_usage_bytes' in ds:
+            ax.plot(cg_elapsed(ds),
+                    [v / divisor for v in ds['memory_usage_bytes']],
+                    color='tab:purple', linewidth=1.5, linestyle='--', label='cgroup usage')
+        if 'rss_bytes' in ds:
+            ax.plot(cg_elapsed(ds),
+                    [v / divisor for v in ds['rss_bytes']],
+                    color='tab:brown', linewidth=1, linestyle='--', label='cgroup RSS')
+
+        ax.set_yscale('log')
+        ax.set_xlabel('Elapsed Time (seconds)')
+        ax.set_ylabel(f'Memory ({unit}, log scale)')
+
+        if jvm_range is not None:
+            x_min, x_max = jvm_range
+            ax.set_xlim(left=x_min, right=x_max * 1.02)
+
+        ax.legend(fontsize=8, loc='upper left')
+
+        eid_label = f'executor {eid} / {label}' if eid else label
+        suffix = f' — {eid_label} Combined Memory'
+        ax.set_title(f'{title}{suffix}' if title else suffix.lstrip(' — '))
+        ax.yaxis.grid(True, which='both')
+        plt.tight_layout()
+        fname = f'combined_memory_{label}.png'
+        plt.savefig(os.path.join(output_dir, fname), format='png')
+        plt.close(fig)
+        print(f'  Created {fname}')
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description='Visualize TPC benchmark memory metrics as time-series charts.')
+    parser.add_argument('--jvm-metrics', type=str, required=True,
+                        help='Path to JVM metrics CSV (comet-tpch-metrics.csv)')
+    parser.add_argument('--cgroup-metrics', type=str, nargs='+', default=None,
+                        help='Paths to cgroup metrics CSVs (container-metrics-worker-*.csv)')
+    parser.add_argument('--output-dir', type=str, default='.',
+                        help='Directory to write chart PNGs (default: current directory)')
+    parser.add_argument('--title', type=str, default='',
+                        help='Title prefix for charts')
+    parser.add_argument('--cgroup-offset', type=float, default=0,
+                        help='Seconds to shift cgroup timestamps for alignment with JVM data (default: 0)')
+    args = parser.parse_args()
+
+    os.makedirs(args.output_dir, exist_ok=True)
+
+    print(f'Loading JVM metrics from {args.jvm_metrics}')
+    jvm_data = load_jvm_metrics(args.jvm_metrics)
+    print(f'  Found executors: {", ".join(sorted(jvm_data.keys()))}')
+
+    generate_jvm_memory_usage(jvm_data, args.output_dir, args.title)
+    generate_jvm_peak_memory(jvm_data, args.output_dir, args.title)
+
+    if args.cgroup_metrics:
+        cgroup_datasets = []
+        for i, path in enumerate(args.cgroup_metrics, start=1):
+            label = f'worker-{i}'
+            print(f'Loading cgroup metrics from {path} (as {label})')
+            cgroup_datasets.append(load_cgroup_metrics(path, label))
+
+        generate_cgroup_memory(cgroup_datasets, jvm_data,
+                               args.output_dir, args.title)
+        generate_combined_memory(jvm_data, cgroup_datasets, args.cgroup_offset,
+                                 args.output_dir, args.title)
+
+    print(f'Done. Charts written to {args.output_dir}')
+
+
+if __name__ == '__main__':
+    main()
diff --git a/dev/benchmarks/README.md b/dev/benchmarks/README.md
deleted file mode 100644
index b3ea674199..0000000000
--- a/dev/benchmarks/README.md
+++ /dev/null
@@ -1,151 +0,0 @@
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
-regarding copyright ownership.  The ASF licenses this file
-to you under the Apache License, Version 2.0 (the
-"License"); you may not use this file except in compliance
-with the License.  You may obtain a copy of the License at
-
-  http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing,
-software distributed under the License is distributed on an
-"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-KIND, either express or implied.  See the License for the
-specific language governing permissions and limitations
-under the License.
--->
-
-# Comet Benchmarking Scripts
-
-This directory contains scripts used for generating benchmark results that are published in this repository and in
-the Comet documentation.
-
-For full instructions on running these benchmarks on an EC2 instance, see the [Comet Benchmarking on EC2 Guide].
-
-[Comet Benchmarking on EC2 Guide]: https://datafusion.apache.org/comet/contributor-guide/benchmarking_aws_ec2.html
-
-## Example usage
-
-Set Spark environment variables:
-
-```shell
-export SPARK_HOME=/opt/spark-3.5.3-bin-hadoop3/
-export SPARK_MASTER=spark://yourhostname:7077
-```
-
-Set path to queries and data:
-
-```shell
-export TPCH_QUERIES=/mnt/bigdata/tpch/queries/
-export TPCH_DATA=/mnt/bigdata/tpch/sf100/
-```
-
-Run Spark benchmark:
-
-```shell
-export JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
-sudo ./drop-caches.sh
-./spark-tpch.sh
-```
-
-Run Comet benchmark:
-
-```shell
-export JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
-export COMET_JAR=/opt/comet/comet-spark-spark3.5_2.12-0.10.0.jar
-sudo ./drop-caches.sh
-./comet-tpch.sh
-```
-
-Run Gluten benchmark:
-
-```shell
-export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64
-export GLUTEN_JAR=/opt/gluten/gluten-velox-bundle-spark3.5_2.12-linux_amd64-1.4.0.jar
-sudo ./drop-caches.sh
-./gluten-tpch.sh
-```
-
-Generating charts:
-
-```shell
-python3 generate-comparison.py --benchmark tpch --labels "Spark 3.5.3" "Comet 0.9.0" "Gluten 1.4.0" --title "TPC-H @ 100 GB (single executor, 8 cores, local Parquet files)" spark-tpch-1752338506381.json comet-tpch-1752337818039.json gluten-tpch-1752337474344.json
-```
-
-## Iceberg Benchmarking
-
-Comet includes native Iceberg support via iceberg-rust integration. This enables benchmarking TPC-H queries
-against Iceberg tables with native scan acceleration.
-
-### Prerequisites
-
-Download the Iceberg Spark runtime JAR (required for running the benchmark):
-
-```shell
-wget https://repo1.maven.org/maven2/org/apache/iceberg/iceberg-spark-runtime-3.5_2.12/1.8.1/iceberg-spark-runtime-3.5_2.12-1.8.1.jar
-export ICEBERG_JAR=/path/to/iceberg-spark-runtime-3.5_2.12-1.8.1.jar
-```
-
-Note: Table creation uses `--packages` which auto-downloads the dependency.
-
-### Create Iceberg TPC-H tables
-
-Convert existing Parquet TPC-H data to Iceberg format:
-
-```shell
-export ICEBERG_WAREHOUSE=/mnt/bigdata/iceberg-warehouse
-export ICEBERG_CATALOG=${ICEBERG_CATALOG:-local}
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=1 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=8 \
-    --conf spark.executor.memory=16g \
-    --conf spark.sql.catalog.${ICEBERG_CATALOG}=org.apache.iceberg.spark.SparkCatalog \
-    --conf spark.sql.catalog.${ICEBERG_CATALOG}.type=hadoop \
-    --conf spark.sql.catalog.${ICEBERG_CATALOG}.warehouse=$ICEBERG_WAREHOUSE \
-    create-iceberg-tpch.py \
-    --parquet-path $TPCH_DATA \
-    --catalog $ICEBERG_CATALOG \
-    --database tpch
-```
-
-### Run Iceberg benchmark
-
-```shell
-export JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64
-export COMET_JAR=/opt/comet/comet-spark-spark3.5_2.12-0.10.0.jar
-export ICEBERG_JAR=/path/to/iceberg-spark-runtime-3.5_2.12-1.8.1.jar
-export ICEBERG_WAREHOUSE=/mnt/bigdata/iceberg-warehouse
-export TPCH_QUERIES=/mnt/bigdata/tpch/queries/
-sudo ./drop-caches.sh
-./comet-tpch-iceberg.sh
-```
-
-The benchmark uses `spark.comet.scan.icebergNative.enabled=true` to enable Comet's native iceberg-rust
-integration. Verify native scanning is active by checking for `CometIcebergNativeScanExec` in the
-physical plan output.
-
-### Iceberg-specific options
-
-| Environment Variable | Default    | Description                         |
-| -------------------- | ---------- | ----------------------------------- |
-| `ICEBERG_CATALOG`    | `local`    | Iceberg catalog name                |
-| `ICEBERG_DATABASE`   | `tpch`     | Database containing TPC-H tables    |
-| `ICEBERG_WAREHOUSE`  | (required) | Path to Iceberg warehouse directory |
-
-### Comparing Parquet vs Iceberg performance
-
-Run both benchmarks and compare:
-
-```shell
-python3 generate-comparison.py --benchmark tpch \
-    --labels "Comet (Parquet)" "Comet (Iceberg)" \
-    --title "TPC-H @ 100 GB: Parquet vs Iceberg" \
-    comet-tpch-*.json comet-iceberg-tpch-*.json
-```
diff --git a/dev/benchmarks/blaze-tpcds.sh b/dev/benchmarks/blaze-tpcds.sh
deleted file mode 100755
index 90a4a48468..0000000000
--- a/dev/benchmarks/blaze-tpcds.sh
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --jars $BLAZE_JAR \
-    --driver-class-path $BLAZE_JAR \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=2 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=16 \
-    --conf spark.executor.memory=16g \
-    --conf spark.executor.memoryOverhead=16g \
-    --conf spark.memory.offHeap.enabled=false \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.driver.extraClassPath=$BLAZE_JAR \
-    --conf spark.executor.extraClassPath=$BLAZE_JAR \
-    --conf spark.sql.extensions=org.apache.spark.sql.blaze.BlazeSparkSessionExtension \
-    --conf spark.shuffle.manager=org.apache.spark.sql.execution.blaze.shuffle.BlazeShuffleManager \
-    --conf spark.blaze.enable=true \
-    --conf spark.blaze.forceShuffledHashJoin=true \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name blaze \
-    --benchmark tpcds \
-    --data $TPCDS_DATA \
-    --queries $TPCDS_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/blaze-tpch.sh b/dev/benchmarks/blaze-tpch.sh
deleted file mode 100755
index 2c6878737d..0000000000
--- a/dev/benchmarks/blaze-tpch.sh
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --jars $BLAZE_JAR \
-    --driver-class-path $BLAZE_JAR \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=1 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=8 \
-    --conf spark.executor.memory=16g \
-    --conf spark.executor.memoryOverhead=16g \
-    --conf spark.memory.offHeap.enabled=false \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.driver.extraClassPath=$BLAZE_JAR \
-    --conf spark.executor.extraClassPath=$BLAZE_JAR \
-    --conf spark.sql.extensions=org.apache.spark.sql.blaze.BlazeSparkSessionExtension \
-    --conf spark.shuffle.manager=org.apache.spark.sql.execution.blaze.shuffle.BlazeShuffleManager \
-    --conf spark.blaze.enable=true \
-    --conf spark.blaze.forceShuffledHashJoin=true \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name blaze \
-    --benchmark tpch \
-    --data $TPCH_DATA \
-    --queries $TPCH_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/comet-tpcds.sh b/dev/benchmarks/comet-tpcds.sh
deleted file mode 100755
index b55b27188c..0000000000
--- a/dev/benchmarks/comet-tpcds.sh
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --jars $COMET_JAR \
-    --driver-class-path $COMET_JAR \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=2 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=16 \
-    --conf spark.executor.memory=16g \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.driver.extraClassPath=$COMET_JAR \
-    --conf spark.executor.extraClassPath=$COMET_JAR \
-    --conf spark.plugins=org.apache.spark.CometPlugin \
-    --conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
-    --conf spark.comet.scan.impl=native_datafusion \
-    --conf spark.comet.expression.Cast.allowIncompatible=true \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name comet \
-    --benchmark tpcds \
-    --data $TPCDS_DATA \
-    --queries $TPCDS_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/comet-tpch-iceberg.sh b/dev/benchmarks/comet-tpch-iceberg.sh
deleted file mode 100755
index 7907125c82..0000000000
--- a/dev/benchmarks/comet-tpch-iceberg.sh
+++ /dev/null
@@ -1,114 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-# TPC-H benchmark using Iceberg tables with Comet's native iceberg-rust integration.
-#
-# Required environment variables:
-#   SPARK_HOME      - Path to Spark installation
-#   SPARK_MASTER    - Spark master URL (e.g., spark://localhost:7077)
-#   COMET_JAR       - Path to Comet JAR
-#   ICEBERG_JAR     - Path to Iceberg Spark runtime JAR
-#   ICEBERG_WAREHOUSE - Path to Iceberg warehouse directory
-#   TPCH_QUERIES    - Path to TPC-H query files
-#
-# Optional:
-#   ICEBERG_CATALOG - Catalog name (default: local)
-#   ICEBERG_DATABASE - Database name (default: tpch)
-#
-# Setup (run once to create Iceberg tables from Parquet):
-#   $SPARK_HOME/bin/spark-submit \
-#       --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
-#       --conf spark.sql.catalog.local=org.apache.iceberg.spark.SparkCatalog \
-#       --conf spark.sql.catalog.local.type=hadoop \
-#       --conf spark.sql.catalog.local.warehouse=$ICEBERG_WAREHOUSE \
-#       create-iceberg-tpch.py \
-#       --parquet-path $TPCH_DATA \
-#       --catalog local \
-#       --database tpch
-
-set -e
-
-# Defaults
-ICEBERG_CATALOG=${ICEBERG_CATALOG:-local}
-ICEBERG_DATABASE=${ICEBERG_DATABASE:-tpch}
-
-# Validate required variables
-if [ -z "$SPARK_HOME" ]; then
-    echo "Error: SPARK_HOME is not set"
-    exit 1
-fi
-if [ -z "$COMET_JAR" ]; then
-    echo "Error: COMET_JAR is not set"
-    exit 1
-fi
-if [ -z "$ICEBERG_JAR" ]; then
-    echo "Error: ICEBERG_JAR is not set"
-    echo "Download from: https://repo1.maven.org/maven2/org/apache/iceberg/iceberg-spark-runtime-3.5_2.12/1.8.1/"
-    exit 1
-fi
-if [ -z "$ICEBERG_WAREHOUSE" ]; then
-    echo "Error: ICEBERG_WAREHOUSE is not set"
-    exit 1
-fi
-if [ -z "$TPCH_QUERIES" ]; then
-    echo "Error: TPCH_QUERIES is not set"
-    exit 1
-fi
-
-$SPARK_HOME/sbin/stop-master.sh 2>/dev/null || true
-$SPARK_HOME/sbin/stop-worker.sh 2>/dev/null || true
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --jars $COMET_JAR,$ICEBERG_JAR \
-    --driver-class-path $COMET_JAR:$ICEBERG_JAR \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=1 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=8 \
-    --conf spark.executor.memory=16g \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.driver.extraClassPath=$COMET_JAR:$ICEBERG_JAR \
-    --conf spark.executor.extraClassPath=$COMET_JAR:$ICEBERG_JAR \
-    --conf spark.plugins=org.apache.spark.CometPlugin \
-    --conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
-    --conf spark.comet.exec.replaceSortMergeJoin=true \
-    --conf spark.comet.expression.Cast.allowIncompatible=true \
-    --conf spark.comet.enabled=true \
-    --conf spark.comet.exec.enabled=true \
-    --conf spark.comet.scan.icebergNative.enabled=true \
-    --conf spark.comet.explainFallback.enabled=true \
-    --conf spark.sql.catalog.${ICEBERG_CATALOG}=org.apache.iceberg.spark.SparkCatalog \
-    --conf spark.sql.catalog.${ICEBERG_CATALOG}.type=hadoop \
-    --conf spark.sql.catalog.${ICEBERG_CATALOG}.warehouse=$ICEBERG_WAREHOUSE \
-    --conf spark.sql.defaultCatalog=${ICEBERG_CATALOG} \
-    tpcbench.py \
-    --name comet-iceberg \
-    --benchmark tpch \
-    --catalog $ICEBERG_CATALOG \
-    --database $ICEBERG_DATABASE \
-    --queries $TPCH_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/comet-tpch.sh b/dev/benchmarks/comet-tpch.sh
deleted file mode 100755
index a748a02319..0000000000
--- a/dev/benchmarks/comet-tpch.sh
+++ /dev/null
@@ -1,55 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --jars $COMET_JAR \
-    --driver-class-path $COMET_JAR \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=1 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=8 \
-    --conf spark.executor.memory=16g \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.driver.extraClassPath=$COMET_JAR \
-    --conf spark.executor.extraClassPath=$COMET_JAR \
-    --conf spark.plugins=org.apache.spark.CometPlugin \
-    --conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
-    --conf spark.comet.scan.impl=native_datafusion \
-    --conf spark.comet.exec.replaceSortMergeJoin=true \
-    --conf spark.comet.expression.Cast.allowIncompatible=true \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name comet \
-    --benchmark tpch \
-    --data $TPCH_DATA \
-    --queries $TPCH_QUERIES \
-    --output . \
-    --iterations 1 \
-    --format parquet
diff --git a/dev/benchmarks/create-iceberg-tpch.py b/dev/benchmarks/create-iceberg-tpch.py
deleted file mode 100644
index 44f0f63a2e..0000000000
--- a/dev/benchmarks/create-iceberg-tpch.py
+++ /dev/null
@@ -1,88 +0,0 @@
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-
-"""
-Convert TPC-H Parquet data to Iceberg tables.
-
-Usage:
-    spark-submit \
-        --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.8.1 \
-        --conf spark.sql.catalog.local=org.apache.iceberg.spark.SparkCatalog \
-        --conf spark.sql.catalog.local.type=hadoop \
-        --conf spark.sql.catalog.local.warehouse=/path/to/iceberg-warehouse \
-        create-iceberg-tpch.py \
-        --parquet-path /path/to/tpch/parquet \
-        --catalog local \
-        --database tpch
-"""
-
-import argparse
-from pyspark.sql import SparkSession
-import time
-
-
-def main(parquet_path: str, catalog: str, database: str):
-    spark = SparkSession.builder \
-        .appName("Create Iceberg TPC-H Tables") \
-        .getOrCreate()
-
-    table_names = [
-        "customer",
-        "lineitem",
-        "nation",
-        "orders",
-        "part",
-        "partsupp",
-        "region",
-        "supplier"
-    ]
-
-    # Create database if it doesn't exist
-    spark.sql(f"CREATE DATABASE IF NOT EXISTS {catalog}.{database}")
-
-    for table in table_names:
-        parquet_table_path = f"{parquet_path}/{table}.parquet"
-        iceberg_table = f"{catalog}.{database}.{table}"
-
-        print(f"Converting {parquet_table_path} -> {iceberg_table}")
-        start_time = time.time()
-
-        # Drop table if exists to allow re-running
-        spark.sql(f"DROP TABLE IF EXISTS {iceberg_table}")
-
-        # Read parquet and write as Iceberg
-        df = spark.read.parquet(parquet_table_path)
-        df.writeTo(iceberg_table).using("iceberg").create()
-
-        row_count = spark.table(iceberg_table).count()
-        elapsed = time.time() - start_time
-        print(f"  Created {iceberg_table} with {row_count} rows in {elapsed:.2f}s")
-
-    print("\nAll TPC-H tables created successfully!")
-    print(f"Tables available at: {catalog}.{database}.*")
-
-    spark.stop()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Convert TPC-H Parquet data to Iceberg tables")
-    parser.add_argument("--parquet-path", required=True, help="Path to TPC-H Parquet data directory")
-    parser.add_argument("--catalog", required=True, help="Iceberg catalog name (e.g., 'local')")
-    parser.add_argument("--database", default="tpch", help="Database name to create tables in")
-    args = parser.parse_args()
-
-    main(args.parquet_path, args.catalog, args.database)
diff --git a/dev/benchmarks/gluten-tpcds.sh b/dev/benchmarks/gluten-tpcds.sh
deleted file mode 100755
index 7c475c79c0..0000000000
--- a/dev/benchmarks/gluten-tpcds.sh
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-export TZ=UTC
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=2 \
-    --conf spark.executor.memory=16G \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=16 \
-    --conf spark.eventLog.enabled=true \
-    --jars $GLUTEN_JAR \
-    --conf spark.plugins=org.apache.gluten.GlutenPlugin \
-    --conf spark.driver.extraClassPath=${GLUTEN_JAR} \
-    --conf spark.executor.extraClassPath=${GLUTEN_JAR} \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.gluten.sql.columnar.forceShuffledHashJoin=true \
-    --conf spark.shuffle.manager=org.apache.spark.shuffle.sort.ColumnarShuffleManager \
-    --conf spark.sql.session.timeZone=UTC \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name gluten \
-    --benchmark tpcds \
-    --data $TPCDS_DATA \
-    --queries $TPCDS_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/gluten-tpch.sh b/dev/benchmarks/gluten-tpch.sh
deleted file mode 100755
index 46c3ed7527..0000000000
--- a/dev/benchmarks/gluten-tpch.sh
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-export TZ=UTC
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=1 \
-    --conf spark.executor.memory=16G \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=8 \
-    --conf spark.eventLog.enabled=true \
-    --jars $GLUTEN_JAR \
-    --conf spark.plugins=org.apache.gluten.GlutenPlugin \
-    --conf spark.driver.extraClassPath=${GLUTEN_JAR} \
-    --conf spark.executor.extraClassPath=${GLUTEN_JAR} \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.gluten.sql.columnar.forceShuffledHashJoin=true \
-    --conf spark.shuffle.manager=org.apache.spark.shuffle.sort.ColumnarShuffleManager \
-    --conf spark.sql.session.timeZone=UTC \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name gluten \
-    --benchmark tpch \
-    --data $TPCH_DATA \
-    --queries $TPCH_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/spark-tpcds.sh b/dev/benchmarks/spark-tpcds.sh
deleted file mode 100755
index dad079ba23..0000000000
--- a/dev/benchmarks/spark-tpcds.sh
+++ /dev/null
@@ -1,45 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=2 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=16 \
-    --conf spark.executor.memory=16g \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name spark \
-    --benchmark tpcds \
-    --data $TPCDS_DATA \
-    --queries $TPCDS_QUERIES \
-    --output . \
-    --iterations 1
diff --git a/dev/benchmarks/spark-tpch.sh b/dev/benchmarks/spark-tpch.sh
deleted file mode 100755
index ae359f049f..0000000000
--- a/dev/benchmarks/spark-tpch.sh
+++ /dev/null
@@ -1,46 +0,0 @@
-#!/bin/bash
-#
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements.  See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership.  The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License.  You may obtain a copy of the License at
-#
-#   http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied.  See the License for the
-# specific language governing permissions and limitations
-# under the License.
-#
-
-$SPARK_HOME/sbin/stop-master.sh
-$SPARK_HOME/sbin/stop-worker.sh
-
-$SPARK_HOME/sbin/start-master.sh
-$SPARK_HOME/sbin/start-worker.sh $SPARK_MASTER
-
-$SPARK_HOME/bin/spark-submit \
-    --master $SPARK_MASTER \
-    --conf spark.driver.memory=8G \
-    --conf spark.executor.instances=1 \
-    --conf spark.executor.cores=8 \
-    --conf spark.cores.max=8 \
-    --conf spark.executor.memory=16g \
-    --conf spark.memory.offHeap.enabled=true \
-    --conf spark.memory.offHeap.size=16g \
-    --conf spark.eventLog.enabled=true \
-    --conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
-    --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
-    tpcbench.py \
-    --name spark \
-    --benchmark tpch \
-    --data $TPCH_DATA \
-    --queries $TPCH_QUERIES \
-    --output . \
-    --iterations 1 \
-    --format parquet
diff --git a/dev/release/rat_exclude_files.txt b/dev/release/rat_exclude_files.txt
index 4ea10c1dff..6553aafc5b 100644
--- a/dev/release/rat_exclude_files.txt
+++ b/dev/release/rat_exclude_files.txt
@@ -28,3 +28,6 @@ spark/src/test/resources/tpch-extended/q*.sql
 spark/src/test/resources/test-data/*.csv
 spark/src/test/resources/test-data/*.ndjson
 spark/inspections/CometTPC*results.txt
+benchmarks/tpc/queries/tpch/q*.sql
+benchmarks/tpc/queries/tpcds/q*.sql
+benchmarks/tpc/requirements.txt
diff --git a/docs/source/about/gluten_comparison.md b/docs/source/about/gluten_comparison.md
index 492479bb9d..40c6c2741a 100644
--- a/docs/source/about/gluten_comparison.md
+++ b/docs/source/about/gluten_comparison.md
@@ -86,7 +86,7 @@ on your existing Spark jobs.
 
 ![tpch_allqueries_comet_gluten.png](/_static/images/tpch_allqueries_comet_gluten.png)
 
-The scripts that were used to generate these results can be found [here](https://github.com/apache/datafusion-comet/tree/main/dev/benchmarks).
+The scripts that were used to generate these results can be found [here](https://github.com/apache/datafusion-comet/tree/main/benchmarks/tpc).
 
 ## Ease of Development & Contributing
 
diff --git a/docs/source/contributor-guide/benchmark-results/tpc-ds.md b/docs/source/contributor-guide/benchmark-results/tpc-ds.md
index 66ff2e51a7..bea254cc08 100644
--- a/docs/source/contributor-guide/benchmark-results/tpc-ds.md
+++ b/docs/source/contributor-guide/benchmark-results/tpc-ds.md
@@ -46,4 +46,4 @@ The raw results of these benchmarks in JSON format is available here:
 - [Spark](spark-3.5.3-tpcds.json)
 - [Comet](comet-0.11.0-tpcds.json)
 
-The scripts that were used to generate these results can be found [here](https://github.com/apache/datafusion-comet/tree/main/dev/benchmarks).
+The scripts that were used to generate these results can be found [here](https://github.com/apache/datafusion-comet/tree/main/benchmarks/tpc).
diff --git a/docs/source/contributor-guide/benchmark-results/tpc-h.md b/docs/source/contributor-guide/benchmark-results/tpc-h.md
index 4424d9eac7..2170426c05 100644
--- a/docs/source/contributor-guide/benchmark-results/tpc-h.md
+++ b/docs/source/contributor-guide/benchmark-results/tpc-h.md
@@ -46,4 +46,4 @@ The raw results of these benchmarks in JSON format is available here:
 - [Spark](spark-3.5.3-tpch.json)
 - [Comet](comet-0.11.0-tpch.json)
 
-The scripts that were used to generate these results can be found [here](https://github.com/apache/datafusion-comet/tree/main/dev/benchmarks).
+The scripts that were used to generate these results can be found [here](https://github.com/apache/datafusion-comet/tree/main/benchmarks/tpc).
diff --git a/docs/source/contributor-guide/benchmarking.md b/docs/source/contributor-guide/benchmarking.md
index 768089c955..ce98fc4be6 100644
--- a/docs/source/contributor-guide/benchmarking.md
+++ b/docs/source/contributor-guide/benchmarking.md
@@ -21,7 +21,7 @@ under the License.
 
 To track progress on performance, we regularly run benchmarks derived from TPC-H and TPC-DS.
 
-The benchmarking scripts are contained at [https://github.com/apache/datafusion-comet/tree/main/dev/benchmarks](https://github.com/apache/datafusion-comet/tree/main/dev/benchmarks).
+The benchmarking scripts are contained at [https://github.com/apache/datafusion-comet/tree/main/benchmarks/tpc](https://github.com/apache/datafusion-comet/tree/main/benchmarks/tpc).
 
 Data generation scripts are available in the [DataFusion Benchmarks](https://github.com/apache/datafusion-benchmarks) GitHub repository.
 
diff --git a/docs/source/contributor-guide/benchmarking_aws_ec2.md b/docs/source/contributor-guide/benchmarking_aws_ec2.md
index 922b0379fe..81f15d64ea 100644
--- a/docs/source/contributor-guide/benchmarking_aws_ec2.md
+++ b/docs/source/contributor-guide/benchmarking_aws_ec2.md
@@ -109,23 +109,23 @@ export COMET_JAR=/home/ec2-user/datafusion-comet/spark/target/comet-spark-spark3
 
 ## Run Benchmarks
 
-Use the scripts in `dev/benchmarks` in the Comet repository.
+Use the scripts in `benchmarks/tpc` in the Comet repository.
 
 ```shell
-cd dev/benchmarks
+cd benchmarks/tpc
 export TPCH_QUERIES=/home/ec2-user/datafusion-benchmarks/tpch/queries/
 ```
 
 Run Spark benchmark:
 
 ```shell
-./spark-tpch.sh
+python3 run.py --engine spark --benchmark tpch
 ```
 
 Run Comet benchmark:
 
 ```shell
-./comet-tpch.sh
+python3 run.py --engine comet --benchmark tpch
 ```
 
 ## Running Benchmarks with S3
@@ -164,4 +164,9 @@ Modify the scripts to add the following configurations.
 --conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.DefaultAWSCredentialsProviderChain \
 ```
 
-Now run the `spark-tpch.sh` and `comet-tpch.sh` scripts.
+Now run the benchmarks:
+
+```shell
+python3 run.py --engine spark --benchmark tpch
+python3 run.py --engine comet --benchmark tpch
+```
diff --git a/pom.xml b/pom.xml
index 1b33fc4757..c5923196ba 100644
--- a/pom.xml
+++ b/pom.xml
@@ -1069,6 +1069,8 @@ under the License.
             <exclude>dev/release/rat_exclude_files.txt</exclude>
             <exclude>dev/release/requirements.txt</exclude>
             <exclude>native/proto/src/generated/**</exclude>
+            <exclude>benchmarks/tpc/queries/**</exclude>
+            <exclude>benchmarks/tpc/requirements.txt</exclude>
           </excludes>
         </configuration>
       </plugin>