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[DOC] update doc for 24.12 release [skip ci] (#11841)
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* update download page

Signed-off-by: liyuan <[email protected]>

* update download page

Signed-off-by: liyuan <[email protected]>

* update download page

Signed-off-by: liyuan <[email protected]>

* update download page

Signed-off-by: liyuan <[email protected]>

* update download page

Signed-off-by: liyuan <[email protected]>

---------

Signed-off-by: liyuan <[email protected]>
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nvliyuan authored Dec 13, 2024
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90 changes: 90 additions & 0 deletions docs/archive.md
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---
Below are archived releases for RAPIDS Accelerator for Apache Spark.

## Release v24.10.1
### Hardware Requirements:

The plugin is tested on the following architectures:

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

### Software Requirements:

OS: Spark RAPIDS is compatible with any Linux distribution with glibc >= 2.28 (Please check ldd --version output). glibc 2.28 was released August 1, 2018.
Tested on Ubuntu 20.04, Ubuntu 22.04, Rocky Linux 8 and Rocky Linux 9

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, 3.3.4
Apache Spark 3.4.0, 3.4.1, 3.4.2, 3.4.3
Apache Spark 3.5.0, 3.5.1, 3.5.2

Supported Databricks runtime versions for Azure and AWS:
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)
Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)

Supported Dataproc versions (Debian/Ubuntu/Rocky):
GCP Dataproc 2.1
GCP Dataproc 2.2

Supported Dataproc Serverless versions:
Spark runtime 1.1 LTS
Spark runtime 2.0
Spark runtime 2.1
Spark runtime 2.2

*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 v24.10.1

| Processor | Scala Version | Download Jar | Download Signature |
|-----------|---------------|--------------|--------------------|
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1.jar.asc) |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1.jar.asc) |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1-cuda11-arm64.jar.asc) |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1-cuda11-arm64.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_2.12-24.10.1.jar.asc rapids-4-spark_2.12-24.10.1.jar`
* Verify the signature for Scala 2.13 jar:
`gpg --verify rapids-4-spark_2.13-24.10.1.jar.asc rapids-4-spark_2.13-24.10.1.jar`

The output of signature verify:

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

### Release Notes
* Optimize scheduling policy for GPU Semaphore
* Support distinct join for right outer joins
* Support MinBy and MaxBy for non-float ordering
* Support ArrayJoin expression
* Optimize Expand and Aggregate expression performance
* Improve JSON related expressions
* For updates on RAPIDS Accelerator Tools, please visit [this link](https://github.com/NVIDIA/spark-rapids-tools/releases)

Note: There is a known issue in the 24.10.1 release when decompressing gzip files on H100 GPUs.
Please find more details in [issue-16661](https://github.com/rapidsai/cudf/issues/16661).

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

## Release v24.10.0
### Hardware Requirements:

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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://docs.nvidia.com/spark-rapids/user-guide/latest/getting-started/overview.html) for more details.

## Release v24.10.1
## Release v24.12.0
### Hardware Requirements:

The plugin is tested on the following architectures:
Expand Down Expand Up @@ -69,14 +69,14 @@ for your hardware's minimum driver version.
### 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 v24.10.1
### Download RAPIDS Accelerator for Apache Spark v24.12.0

| Processor | Scala Version | Download Jar | Download Signature |
|-----------|---------------|--------------|--------------------|
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1.jar.asc) |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1.jar.asc) |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.1/rapids-4-spark_2.12-24.10.1-cuda11-arm64.jar.asc) |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v24.10.1](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.10.1/rapids-4-spark_2.13-24.10.1-cuda11-arm64.jar.asc) |
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v24.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.12.0/rapids-4-spark_2.12-24.12.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.12.0/rapids-4-spark_2.12-24.12.0.jar.asc) |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v24.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.12.0/rapids-4-spark_2.13-24.12.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.12.0/rapids-4-spark_2.13-24.12.0.jar.asc) |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v24.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.12.0/rapids-4-spark_2.12-24.12.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.12.0/rapids-4-spark_2.12-24.12.0-cuda11-arm64.jar.asc) |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v24.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.12.0/rapids-4-spark_2.13-24.12.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.12.0/rapids-4-spark_2.13-24.12.0-cuda11-arm64.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.
Expand All @@ -85,24 +85,27 @@ CUDA 11.8 through CUDA 12.0.
* 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_2.12-24.10.1.jar.asc rapids-4-spark_2.12-24.10.1.jar`
`gpg --verify rapids-4-spark_2.12-24.12.0.jar.asc rapids-4-spark_2.12-24.12.0.jar`
* Verify the signature for Scala 2.13 jar:
`gpg --verify rapids-4-spark_2.13-24.10.1.jar.asc rapids-4-spark_2.13-24.10.1.jar`
`gpg --verify rapids-4-spark_2.13-24.12.0.jar.asc rapids-4-spark_2.13-24.12.0.jar`

The output of signature verify:

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

### Release Notes
* Optimize scheduling policy for GPU Semaphore
* Support distinct join for right outer joins
* Support MinBy and MaxBy for non-float ordering
* Support ArrayJoin expression
* Optimize Expand and Aggregate expression performance
* Improve JSON related expressions
* Add repartition-based algorithm fallback in hash aggregate
* Support Spark function months_between
* Support asynchronous writing for Parquet files
* Add retry support to improve sub hash-join stability
* Improve JSON scan and from_json
* Improved performance for CASE WHEN statements comparing a string column against multiple values
* Falling back to the CPU for ORC boolean writes by the GPU due to a bug in cudf's ORC writer
* Fix a device memory leak in timestamp operator in `incompatibleDateFormats` case
* Fix a host memory leak in GpuBroadcastNestedLoopJoinExecBase when `spillableBuiltBatch` is 0
* For updates on RAPIDS Accelerator Tools, please visit [this link](https://github.com/NVIDIA/spark-rapids-tools/releases)

Note: There is a known issue in the 24.10.1 release when decompressing gzip files on H100 GPUs.
Note: There is a known issue in the 24.12.0 release when decompressing gzip files on H100 GPUs.
Please find more details in [issue-16661](https://github.com/rapidsai/cudf/issues/16661).

For a detailed list of changes, please refer to the
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