diff --git a/README.md b/README.md
index fb17535aaa..b0b72fdb6f 100644
--- a/README.md
+++ b/README.md
@@ -19,58 +19,86 @@ under the License.
# Apache DataFusion Comet
-Apache DataFusion Comet is an Apache Spark plugin that uses [Apache DataFusion](https://datafusion.apache.org/)
-as native runtime to achieve improvement in terms of query efficiency and query runtime.
+Apache DataFusion Comet is a high-performance accelerator for Apache Spark, built on top of the powerful
+[Apache DataFusion](https://datafusion.apache.org) query engine. Comet is designed to significantly enhance the
+performance of Apache Spark workloads while leveraging commodity hardware and seamlessly integrating with the
+Spark ecosystem without requiring any code changes.
-Comet runs Spark SQL queries using the native DataFusion runtime, which is
-typically faster and more resource efficient than JVM based runtimes.
+# Benefits of Using Comet
-
+## Run Spark Queries at DataFusion Speeds
-Comet aims to support:
+Comet delivers a performance speedup for many queries, enabling faster data processing and shorter time-to-insights.
-- a native Parquet implementation, including both reader and writer
-- full implementation of Spark operators, including
- Filter/Project/Aggregation/Join/Exchange etc.
-- full implementation of Spark built-in expressions
-- a UDF framework for users to migrate their existing UDF to native
+The following chart shows the time it takes to run the 22 TPC-H queries against 100 GB of data in Parquet format
+using a single executor with 8 cores. See the [Comet Benchmarking Guide](https://datafusion.apache.org/comet/contributor-guide/benchmarking.html)
+for details of the environment used for these benchmarks.
-## Architecture
+When using Comet, the overall run time is reduced from 649 seconds to 440 seconds, a 1.5x speedup.
-The following diagram illustrates the architecture of Comet:
+Running the same queries with DataFusion standalone (without Spark) using the same number of cores results in a 3.9x
+speedup compared to Spark.
-
+Comet is not yet achieving full DataFusion speeds in all cases, but with future work we aim to provide a 2x-4x speedup
+for many use cases.
-## Current Status
+
-The project is currently integrated into Apache Spark 3.2, 3.3, and 3.4.
+Here is a breakdown showing relative performance of Spark, Comet, and DataFusion for each TPC-H query.
-## Feature Parity with Apache Spark
+
-The project strives to keep feature parity with Apache Spark, that is,
-users should expect the same behavior (w.r.t features, configurations,
-query results, etc) with Comet turned on or turned off in their Spark
-jobs. In addition, Comet extension should automatically detect unsupported
-features and fallback to Spark engine.
+The following chart shows how much Comet currently accelerates each query from the benchmark. Performance optimization
+is an ongoing task, and we welcome contributions from the community to help achieve even greater speedups in the future.
-To achieve this, besides unit tests within Comet itself, we also re-use
-Spark SQL tests and make sure they all pass with Comet extension
-enabled.
+
-## Supported Platforms
+These benchmarks can be reproduced in any environment using the documentation in the
+[Comet Benchmarking Guide](https://datafusion.apache.org/comet/contributor-guide/benchmarking.html). We encourage
+you to run your own benchmarks.
-Linux, Apple OSX (Intel and M1)
+## Use Commodity Hardware
-## Requirements
+Comet leverages commodity hardware, eliminating the need for costly hardware upgrades or
+specialized hardware accelerators, such as GPUs or FGPA. By maximizing the utilization of commodity hardware, Comet
+ensures cost-effectiveness and scalability for your Spark deployments.
-- Apache Spark 3.2, 3.3, or 3.4
-- JDK 8, 11 and 17 (JDK 11 recommended because Spark 3.2 doesn't support 17)
-- GLIBC 2.17 (Centos 7) and up
+## Spark Compatibility
-## Getting started
+Comet aims for 100% compatibility with all supported versions of Apache Spark, allowing you to integrate Comet into
+your existing Spark deployments and workflows seamlessly. With no code changes required, you can immediately harness
+the benefits of Comet's acceleration capabilities without disrupting your Spark applications.
-See the [DataFusion Comet User Guide](https://datafusion.apache.org/comet/user-guide/installation.html) for installation instructions.
+## Tight Integration with Apache DataFusion
+
+Comet tightly integrates with the core Apache DataFusion project, leveraging its powerful execution engine. With
+seamless interoperability between Comet and DataFusion, you can achieve optimal performance and efficiency in your
+Spark workloads.
+
+## Active Community
+
+Comet boasts a vibrant and active community of developers, contributors, and users dedicated to advancing the
+capabilities of Apache DataFusion and accelerating the performance of Apache Spark.
+
+## Getting Started
+
+To get started with Apache DataFusion Comet, follow the
+[installation instructions](https://datafusion.apache.org/comet/user-guide/installation.html). Join the
+[DataFusion Slack and Discord channels](https://datafusion.apache.org/contributor-guide/communication.html) to connect
+with other users, ask questions, and share your experiences with Comet.
## Contributing
-See the [DataFusion Comet Contribution Guide](https://datafusion.apache.org/comet/contributor-guide/contributing.html)
-for information on how to get started contributing to the project.
+
+We welcome contributions from the community to help improve and enhance Apache DataFusion Comet. Whether it's fixing
+bugs, adding new features, writing documentation, or optimizing performance, your contributions are invaluable in
+shaping the future of Comet. Check out our
+[contributor guide](https://datafusion.apache.org/comet/contributor-guide/contributing.html) to get started.
+
+## License
+
+Apache DataFusion Comet is licensed under the Apache License 2.0. See the [LICENSE.txt](LICENSE.txt) file for details.
+
+## Acknowledgments
+
+We would like to express our gratitude to the Apache DataFusion community for their support and contributions to
+Comet. Together, we're building a faster, more efficient future for big data processing with Apache Spark.
diff --git a/docs/source/_static/images/tpch_allqueries.png b/docs/source/_static/images/tpch_allqueries.png
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new file mode 100644
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diff --git a/docs/source/_static/images/tpch_queries_speedup.png b/docs/source/_static/images/tpch_queries_speedup.png
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diff --git a/docs/source/contributor-guide/benchmark-results/2024-05-30/comet-8-exec-5-runs.json b/docs/source/contributor-guide/benchmark-results/2024-05-30/comet-8-exec-5-runs.json
new file mode 100644
index 0000000000..38142151d1
--- /dev/null
+++ b/docs/source/contributor-guide/benchmark-results/2024-05-30/comet-8-exec-5-runs.json
@@ -0,0 +1,201 @@
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diff --git a/docs/source/contributor-guide/benchmark-results/2024-05-30/datafusion-python-8-cores.json b/docs/source/contributor-guide/benchmark-results/2024-05-30/datafusion-python-8-cores.json
new file mode 100644
index 0000000000..f032d536df
--- /dev/null
+++ b/docs/source/contributor-guide/benchmark-results/2024-05-30/datafusion-python-8-cores.json
@@ -0,0 +1,73 @@
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diff --git a/docs/source/contributor-guide/benchmark-results/2024-05-30/spark-8-exec-5-runs.json b/docs/source/contributor-guide/benchmark-results/2024-05-30/spark-8-exec-5-runs.json
new file mode 100644
index 0000000000..012b05c3ad
--- /dev/null
+++ b/docs/source/contributor-guide/benchmark-results/2024-05-30/spark-8-exec-5-runs.json
@@ -0,0 +1,184 @@
+{
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+ 11.654477834701538,
+ 11.805298805236816,
+ 11.822469234466553,
+ 12.79678750038147,
+ 13.64478850364685
+ ],
+ "13": [
+ 20.430822372436523,
+ 20.18759250640869,
+ 21.26596975326538,
+ 21.234288454055786,
+ 20.189200162887573
+ ],
+ "14": [
+ 5.60215950012207,
+ 5.160705089569092,
+ 5.080057382583618,
+ 4.937625408172607,
+ 5.853632688522339
+ ],
+ "15": [
+ 14.17775845527649,
+ 13.898571729660034,
+ 14.215840578079224,
+ 14.316090106964111,
+ 14.356236457824707
+ ],
+ "16": [
+ 6.252386808395386,
+ 6.010213375091553,
+ 6.054978370666504,
+ 5.886059522628784,
+ 5.923115253448486
+ ],
+ "17": [
+ 71.41593313217163,
+ 70.25399804115295,
+ 72.07622528076172,
+ 72.27566242218018,
+ 72.20579051971436
+ ],
+ "18": [
+ 65.72738265991211,
+ 65.47461080551147,
+ 67.14260482788086,
+ 65.95489883422852,
+ 69.51795554161072
+ ],
+ "19": [
+ 7.1520891189575195,
+ 6.516514301300049,
+ 6.580992698669434,
+ 6.486274242401123,
+ 6.418147087097168
+ ],
+ "20": [
+ 12.619760036468506,
+ 12.235978126525879,
+ 12.116347551345825,
+ 12.161245584487915,
+ 12.30910348892212
+ ],
+ "21": [
+ 60.795483350753784,
+ 60.484593629837036,
+ 61.27316427230835,
+ 60.475560426712036,
+ 81.21473670005798
+ ],
+ "22": [
+ 8.926804065704346,
+ 8.113754034042358,
+ 8.029133796691895,
+ 7.99291467666626,
+ 8.439452648162842
+ ]
+}
\ No newline at end of file
diff --git a/docs/source/contributor-guide/benchmarking.md b/docs/source/contributor-guide/benchmarking.md
index 502b35c29b..3e9a61efbb 100644
--- a/docs/source/contributor-guide/benchmarking.md
+++ b/docs/source/contributor-guide/benchmarking.md
@@ -19,44 +19,87 @@ under the License.
# Comet Benchmarking Guide
-To track progress on performance, we regularly run benchmarks derived from TPC-H and TPC-DS. Benchmarking scripts are
-available in the [DataFusion Benchmarks](https://github.com/apache/datafusion-benchmarks) GitHub repository.
+To track progress on performance, we regularly run benchmarks derived from TPC-H and TPC-DS. Data generation and
+benchmarking documentation and scripts are available in the [DataFusion Benchmarks](https://github.com/apache/datafusion-benchmarks) GitHub repository.
-Here is an example command for running the benchmarks. This command will need to be adapted based on the Spark
-environment and location of data files.
+Here are example commands for running the benchmarks against a Spark cluster. This command will need to be
+adapted based on the Spark environment and location of data files.
-This command assumes that `datafusion-benchmarks` is checked out in a parallel directory to `datafusion-comet`.
+These commands are intended to be run from the `runners/datafusion-comet` directory in the `datafusion-benchmarks`
+repository.
+
+## Running Benchmarks Against Apache Spark
```shell
-$SPARK_HOME/bin/spark-submit \
- --master "local[*]" \
- --conf spark.driver.memory=8G \
- --conf spark.executor.memory=64G \
- --conf spark.executor.cores=16 \
- --conf spark.cores.max=16 \
- --conf spark.eventLog.enabled=true \
- --conf spark.sql.autoBroadcastJoinThreshold=-1 \
- --jars $COMET_JAR \
- --conf spark.driver.extraClassPath=$COMET_JAR \
- --conf spark.executor.extraClassPath=$COMET_JAR \
- --conf spark.sql.extensions=org.apache.comet.CometSparkSessionExtensions \
- --conf spark.comet.enabled=true \
- --conf spark.comet.exec.enabled=true \
- --conf spark.comet.exec.all.enabled=true \
- --conf spark.comet.cast.allowIncompatible=true \
- --conf spark.comet.explainFallback.enabled=true \
- --conf spark.comet.parquet.io.enabled=false \
- --conf spark.comet.batchSize=8192 \
- --conf spark.comet.columnar.shuffle.enabled=false \
- --conf spark.comet.exec.shuffle.enabled=true \
- --conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
- --conf spark.sql.adaptive.coalescePartitions.enabled=false \
- --conf spark.comet.shuffle.enforceMode.enabled=true \
- ../datafusion-benchmarks/runners/datafusion-comet/tpcbench.py \
- --benchmark tpch \
- --data /mnt/bigdata/tpch/sf100-parquet/ \
- --queries ../datafusion-benchmarks/tpch/queries
+$SPARK_HOME/bin/spark-submit \
+ --master $SPARK_MASTER \
+ --conf spark.driver.memory=8G \
+ --conf spark.executor.memory=32G \
+ --conf spark.executor.cores=8 \
+ --conf spark.cores.max=8 \
+ --conf spark.sql.autoBroadcastJoinThreshold=-1 \
+ tpcbench.py \
+ --benchmark tpch \
+ --data /mnt/bigdata/tpch/sf100/ \
+ --queries ../../tpch/queries \
+ --iterations 5
```
-Comet performance can be compared to regular Spark performance by running the benchmark twice, once with
-`spark.comet.enabled` set to `true` and once with it set to `false`.
\ No newline at end of file
+## Running Benchmarks Against Apache Spark with Apache DataFusion Comet Enabled
+
+```shell
+$SPARK_HOME/bin/spark-submit \
+ --master $SPARK_MASTER \
+ --conf spark.driver.memory=8G \
+ --conf spark.executor.memory=64G \
+ --conf spark.executor.cores=8 \
+ --conf spark.cores.max=8 \
+ --conf spark.sql.autoBroadcastJoinThreshold=-1 \
+ --jars $COMET_JAR \
+ --conf spark.driver.extraClassPath=$COMET_JAR \
+ --conf spark.executor.extraClassPath=$COMET_JAR \
+ --conf spark.sql.extensions=org.apache.comet.CometSparkSessionExtensions \
+ --conf spark.comet.enabled=true \
+ --conf spark.comet.exec.enabled=true \
+ --conf spark.comet.exec.all.enabled=true \
+ --conf spark.comet.cast.allowIncompatible=true \
+ --conf spark.comet.explainFallback.enabled=true \
+ --conf spark.comet.parquet.io.enabled=false \
+ --conf spark.comet.batchSize=8192 \
+ --conf spark.comet.exec.shuffle.enabled=true \
+ --conf spark.comet.exec.shuffle.mode=auto \
+ --conf spark.shuffle.manager=org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager \
+ --conf spark.sql.adaptive.coalescePartitions.enabled=false \
+ tpcbench.py \
+ --benchmark tpch \
+ --data /mnt/bigdata/tpch/sf100/ \
+ --queries ../../tpch/queries \
+ --iterations 5
+```
+
+## Current Performance
+
+Comet is not yet achieving full DataFusion speeds in all cases, but with future work we aim to provide a 2x-4x speedup
+for many use cases.
+
+The following benchmarks were performed on a Linux workstation with PCIe 5, AMD 7950X CPU (16 cores), 128 GB RAM, and
+data stored locally on NVMe storage. Performance characteristics will vary in different environments and we encourage
+you to run these benchmarks in your own environments.
+
+
+
+Here is a breakdown showing relative performance of Spark, Comet, and DataFusion for each TPC-H query.
+
+
+
+The following chart shows how much Comet currently accelerates each query from the benchmark. Performance optimization
+is an ongoing task, and we welcome contributions from the community to help achieve even greater speedups in the future.
+
+
+
+The raw results of these benchmarks in JSON format is available here:
+
+- [Spark](./benchmark-results/2024-05-30/spark-8-exec-5-runs.json)
+- [Comet](./benchmark-results/2024-05-30/comet-8-exec-5-runs.json)
+- [DataFusion](./benchmark-results/2024-05-30/datafusion-python-8-cores.json)
+