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[Doc]Update docs for 23.08.2 version[skip ci] #9408

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[Doc]Update docs for 23.08.2 version[skip ci] #9408

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78 changes: 78 additions & 0 deletions docs/archive.md
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Expand Up @@ -5,6 +5,84 @@ nav_order: 15
---
Below are archived releases for RAPIDS Accelerator for Apache Spark.

## Release v23.08.1
### Hardware Requirements:

The plugin is tested on the following architectures:

GPU Models: NVIDIA P100, 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
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.
Please be aware that we do not currently support Spark builds with Scala 2.13.

Supported Spark versions:
Apache Spark 3.1.1, 3.1.2, 3.1.3
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
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

*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.

### Download v23.08.1
* Download the [RAPIDS
Accelerator for Apache Spark 23.08.1 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.1/rapids-4-spark_2.12-23.08.1.jar)

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.

Note that v23.08.0 is deprecated.

### Verify signature
* Download the [RAPIDS Accelerator for Apache Spark 23.08.1 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.1/rapids-4-spark_2.12-23.08.1.jar)
and [RAPIDS Accelerator for Apache Spark 23.08.1 jars.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.1/rapids-4-spark_2.12-23.08.1.jar.asc)
* Download the [PUB_KEY](https://keys.openpgp.org/[email protected]).
* Import the public key: `gpg --import PUB_KEY`
* Verify the signature: `gpg --verify rapids-4-spark_2.12-23.08.1.jar.asc rapids-4-spark_2.12-23.08.1.jar`

The output if 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:
* Compatibility with Databricks AWS & Azure 12.2 ML LTS.
* Enhanced stability and support for ORC and Parquet.
* Reduction of out-of-memory (OOM) occurrences.
* Corner case evaluation for data formats, operators and expressions
* Qualification and Profiling tool:
* Profiling tool now supports Azure Databricks and AWS Databricks.
* Qualification tool can provide advice on unaccelerated operations.
* Improve user experience through CLI design.
* Qualification tool provides configuration and migration recommendations for Dataproc and EMR.

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

## Release v23.06.0
Hardware Requirements:

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45 changes: 25 additions & 20 deletions docs/download.md
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Expand Up @@ -18,7 +18,7 @@ cuDF jar, that is either preinstalled in the Spark classpath on all nodes or sub
that uses the RAPIDS Accelerator For Apache Spark. See the [getting-started
guide](https://nvidia.github.io/spark-rapids/Getting-Started/) for more details.

## Release v23.08.1
## Release v23.08.2
### Hardware Requirements:

The plugin is tested on the following architectures:
Expand All @@ -29,49 +29,53 @@ The plugin is tested on the following architectures:

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

NVIDIA Driver*: 470+
NVIDIA Driver*: R470+

Python 3.6+, Scala 2.12, Java 8, Java 17
Runtime:
Scala 2.12
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.
Please be aware that we do not currently support Spark builds with Scala 2.13.

Supported Spark versions:
Apache Spark 3.1.1, 3.1.2, 3.1.3
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
Apache Spark 3.4.0, 3.4.1
Apache Spark 3.5.0

Supported Databricks runtime versions:
Azure/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 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

*Some hardware may have a minimum driver version greater than v450.80.02+. Check the GPU spec sheet
*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](./FAQ.md#which-distributions-are-supported) section of the FAQ.
[Distributions](https://docs.nvidia.com/spark-rapids/user-guide/latest/faq.html#which-distributions-are-supported) section of the FAQ.

### Download v23.08.1
### Download v23.08.2
* Download the [RAPIDS
Accelerator for Apache Spark 23.08.1 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.1/rapids-4-spark_2.12-23.08.1.jar)
Accelerator for Apache Spark 23.08.2 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.2/rapids-4-spark_2.12-23.08.2.jar)

This package is built against CUDA 11.8, all CUDA 11.x and 12.x versions are supported through [CUDA forward
compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html). It is tested
on V100, T4, A10, A100, L4 and H100 GPUs with CUDA 11.8-12.0. For those using other types of GPUs
which do not have CUDA forward compatibility (for example, GeForce), CUDA 11.8 or later is required.
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.

Note that v23.08.0 is deprecated.

### Verify signature
* Download the [RAPIDS Accelerator for Apache Spark 23.08.1 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.1/rapids-4-spark_2.12-23.08.1.jar)
and [RAPIDS Accelerator for Apache Spark 23.08.1 jars.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.1/rapids-4-spark_2.12-23.08.1.jar.asc)
* Download the [RAPIDS Accelerator for Apache Spark 23.08.2 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.2/rapids-4-spark_2.12-23.08.2.jar)
and [RAPIDS Accelerator for Apache Spark 23.08.2 jars.asc](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/23.08.2/rapids-4-spark_2.12-23.08.2.jar.asc)
* Download the [PUB_KEY](https://keys.openpgp.org/[email protected]).
* Import the public key: `gpg --import PUB_KEY`
* Verify the signature: `gpg --verify rapids-4-spark_2.12-23.08.1.jar.asc rapids-4-spark_2.12-23.08.1.jar`
* Verify the signature: `gpg --verify rapids-4-spark_2.12-23.08.2.jar.asc rapids-4-spark_2.12-23.08.2.jar`

The output if signature verify:

Expand All @@ -88,7 +92,8 @@ New functionality and performance improvements for this release include:
* Qualification tool can provide advice on unaccelerated operations.
* Improve user experience through CLI design.
* Qualification tool provides configuration and migration recommendations for Dataproc and EMR.

* Fixes Databricks build issues from the previous 23.08 release.

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

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