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[DOC] Update docs for 24.04.0 release [skip ci] #10676

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[DOC] Update docs for 24.04.0 release [skip ci] #10676

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update docs 24.04
SurajAralihalli Apr 9, 2024
faea4d8
update docs 24.04
SurajAralihalli Apr 9, 2024
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update docs 24.04
SurajAralihalli Apr 10, 2024
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91 changes: 91 additions & 0 deletions docs/archive.md
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Expand Up @@ -5,6 +5,97 @@ nav_order: 15
---
Below are archived releases for RAPIDS Accelerator for Apache Spark.

## Release v24.02.0
### 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)
Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)

Supported Dataproc versions:
GCP Dataproc 2.0
GCP Dataproc 2.1

Supported Dataproc Serverless versions:
Spark runtime 1.1 LTS
Spark runtime 2.0
Spark runtime 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.

### 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 v24.02.0

| Processor | Scala Version | Download Jar | Download Signature |
|-----------|---------------|--------------|--------------------|
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0.jar.asc) |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0.jar.asc) |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0-cuda11-arm64.jar.asc) |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0-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.

### Verify signature
* Download the [PUB_KEY](https://keys.openpgp.org/search?q=sw-spark@nvidia.com).
* Import the public key: `gpg --import PUB_KEY`
* Verify the signature for Scala 2.12 jar:
`gpg --verify rapids-4-spark_2.12-24.02.0.jar.asc rapids-4-spark_2.12-24.02.0.jar`
* Verify the signature for Scala 2.13 jar:
`gpg --verify rapids-4-spark_2.13-24.02.0.jar.asc rapids-4-spark_2.13-24.02.0.jar`

The output of signature verify:

gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) <sw-spark@nvidia.com>"

### Release Notes
New functionality and performance improvements for this release include:
* Discontinued support for Nvidia GPUs based on Pascal architecture.
* Set get_json_object functionality to disabled by default.
* Implemented string comparison in AST expressions.
* Expanded timezone support to include options beyond UTC.
* Optional checksums for cached files in the file cache.
* Introduced support for Databricks 13.3 ML LTS.
* Added support for parse_url functionality.
* Introducing Lazy Quantifier support for regular expression functions.
* Added support for the format_number function.
* Enhanced batching support for row-based bounded window functions.
* For updates on RAPIDS Accelerator Tools, please visit [this link](https://github.com/NVIDIA/spark-rapids-tools/releases).

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

## Release v23.12.2
### Hardware Requirements:

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44 changes: 20 additions & 24 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://docs.nvidia.com/spark-rapids/user-guide/latest/getting-started/overview.html) for more details.

## Release v24.02.0
## Release v24.04.0
### Hardware Requirements:

The plugin is tested on the following architectures:
Expand All @@ -40,17 +40,16 @@ The plugin is tested on the following architectures:

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
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
Apache Spark 3.5.0, 3.5.1

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)
Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)

Supported Dataproc versions:
Supported Dataproc versions (Debian/Ubuntu):
GCP Dataproc 2.0
GCP Dataproc 2.1

Expand All @@ -68,14 +67,14 @@ 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 v24.02.0
### Download RAPIDS Accelerator for Apache Spark v24.04.0

| Processor | Scala Version | Download Jar | Download Signature |
|-----------|---------------|--------------|--------------------|
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0.jar.asc) |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0.jar.asc) |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.02.0/rapids-4-spark_2.12-24.02.0-cuda11-arm64.jar.asc) |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v24.02.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.02.0/rapids-4-spark_2.13-24.02.0-cuda11-arm64.jar.asc) |
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v24.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.04.0/rapids-4-spark_2.12-24.04.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.04.0/rapids-4-spark_2.12-24.04.0.jar.asc) |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v24.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.04.0/rapids-4-spark_2.13-24.04.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.04.0/rapids-4-spark_2.13-24.04.0.jar.asc) |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v24.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.04.0/rapids-4-spark_2.12-24.04.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.04.0/rapids-4-spark_2.12-24.04.0-cuda11-arm64.jar.asc) |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v24.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.04.0/rapids-4-spark_2.13-24.04.0-cuda11-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/24.04.0/rapids-4-spark_2.13-24.04.0-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 @@ -84,26 +83,23 @@ CUDA 11.8 through CUDA 12.0.
* Download the [PUB_KEY](https://keys.openpgp.org/search?q=sw-spark@nvidia.com).
* Import the public key: `gpg --import PUB_KEY`
* Verify the signature for Scala 2.12 jar:
`gpg --verify rapids-4-spark_2.12-24.02.0.jar.asc rapids-4-spark_2.12-24.02.0.jar`
`gpg --verify rapids-4-spark_2.12-24.04.0.jar.asc rapids-4-spark_2.12-24.04.0.jar`
* Verify the signature for Scala 2.13 jar:
`gpg --verify rapids-4-spark_2.13-24.02.0.jar.asc rapids-4-spark_2.13-24.02.0.jar`
`gpg --verify rapids-4-spark_2.13-24.04.0.jar.asc rapids-4-spark_2.13-24.04.0.jar`

The output of signature verify:

gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) <sw-spark@nvidia.com>"

### Release Notes
New functionality and performance improvements for this release include:
* Discontinued support for Nvidia GPUs based on Pascal architecture.
* Set get_json_object functionality to disabled by default.
* Implemented string comparison in AST expressions.
* Expanded timezone support to include options beyond UTC.
* Optional checksums for cached files in the file cache.
* Introduced support for Databricks 13.3 ML LTS.
* Added support for parse_url functionality.
* Introducing Lazy Quantifier support for regular expression functions.
* Added support for the format_number function.
* Enhanced batching support for row-based bounded window functions.
* New functionality and performance improvements for this release include:
* Performance improvements for S3 reading.
Refer to perfio.s3.enabled in [advanced_configs](./additional-functionality/advanced_configs.md) for more details.
* Performance improvements when doing a joins on unique keys.
* Enhanced decompression kernels for zstd and snappy.
* Enhanced Parquet reading performance with modular kernels.
* Added compatibility with Spark version 3.5.1.
* Deprecated support for Databricks 10.4 ML LTS.
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* For updates on RAPIDS Accelerator Tools, please visit [this link](https://github.com/NVIDIA/spark-rapids-tools/releases).

For a detailed list of changes, please refer to the
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