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update 23.12.2 (NVIDIA#10384)
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Signed-off-by: Suraj Aralihalli <[email protected]>
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SurajAralihalli authored Feb 6, 2024
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Below are archived releases for RAPIDS Accelerator for Apache Spark.

## Release v23.12.1
### Hardware Requirements:

The plugin is tested on the following architectures:

GPU Models: NVIDIA V100, T4, A10/A100, L4 and H100 GPUs

### Software Requirements:

OS: Ubuntu 20.04, Ubuntu 22.04, CentOS 7, or Rocky Linux 8

NVIDIA Driver*: R470+

Runtime:
Scala 2.12, 2.13
Python, Java Virtual Machine (JVM) compatible with your spark-version.

* Check the Spark documentation for Python and Java version compatibility with your specific
Spark version. For instance, visit `https://spark.apache.org/docs/3.4.1` for Spark 3.4.1.

Supported Spark versions:
Apache Spark 3.2.0, 3.2.1, 3.2.2, 3.2.3, 3.2.4
Apache Spark 3.3.0, 3.3.1, 3.3.2, 3.3.3
Apache Spark 3.4.0, 3.4.1
Apache Spark 3.5.0

Supported Databricks runtime versions for Azure and AWS:
Databricks 10.4 ML LTS (GPU, Scala 2.12, Spark 3.2.1)
Databricks 11.3 ML LTS (GPU, Scala 2.12, Spark 3.3.0)
Databricks 12.2 ML LTS (GPU, Scala 2.12, Spark 3.3.2)

Supported Dataproc versions:
GCP Dataproc 2.0
GCP Dataproc 2.1

Supported Dataproc Serverless versions:
Spark runtime 1.1 LTS

*Some hardware may have a minimum driver version greater than R470. Check the GPU spec sheet
for your hardware's minimum driver version.

*For Cloudera and EMR support, please refer to the
[Distributions](https://docs.nvidia.com/spark-rapids/user-guide/latest/faq.html#which-distributions-are-supported) section of the FAQ.

### RAPIDS Accelerator's Support Policy for Apache Spark
The RAPIDS Accelerator maintains support for Apache Spark versions available for download from [Apache Spark](https://spark.apache.org/downloads.html)

### Download RAPIDS Accelerator for Apache Spark v23.12.1
- **Scala 2.12:**
- [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.12 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.12.1/rapids-4-spark_2.12-23.12.1.jar)
- [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.12 jar.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.12.1/rapids-4-spark_2.12-23.12.1.jar.asc)

- **Scala 2.13:**
- [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.13 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/23.12.1/rapids-4-spark_2.13-23.12.1.jar)
- [RAPIDS Accelerator for Apache Spark 23.12.1 - Scala 2.13 jar.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/23.12.1/rapids-4-spark_2.13-23.12.1.jar.asc)

This package is built against CUDA 11.8. It is tested on V100, T4, A10, A100, L4 and H100 GPUs with
CUDA 11.8 through CUDA 12.0.

### Verify signature
* Download the [PUB_KEY](https://keys.openpgp.org/[email protected]).
* Import the public key: `gpg --import PUB_KEY`
* Verify the signature for Scala 2.12 jar:
`gpg --verify rapids-4-spark_2.12-23.12.1.jar.asc rapids-4-spark_2.12-23.12.1.jar`
* Verify the signature for Scala 2.13 jar:
`gpg --verify rapids-4-spark_2.13-23.12.1.jar.asc rapids-4-spark_2.13-23.12.1.jar`

The output of signature verify:

gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) <[email protected]>"

### Release Notes
New functionality and performance improvements for this release include:
* Introduced support for chunked reading of ORC files.
* Enhanced support for additional time zones and added stack function support.
* Enhanced performance for join and aggregation operations.
* Kernel optimizations have been implemented to improve Parquet read performance.
* RAPIDS Accelerator also built and tested with Scala 2.13.
* Last version to support Pascal-based Nvidia GPUs; discontinued in the next release.
* Introduced support for parquet Legacy rebase mode (spark.sql.parquet.datetimeRebaseModeInRead=LEGACY and spark.sql.parquet.int96RebaseModeInRead=LEGACY)
* Introduced support for Percentile function.
* Delta lake 2.3 support.
* Qualification and Profiling tool:
* Profiling Tool now processes Spark Driver log for GPU runs, enhancing feature analysis.
* Auto-tuner recommendations include AQE settings for optimized performance.
* New configurations in Profiler for enabling off-default features: udfCompiler, incompatibleDateFormats, hasExtendedYearValues.

For a detailed list of changes, please refer to the
[CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md).

## Release v23.12.0
### Hardware Requirements:

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