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pxLi merged 1 commit into from
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[DOC] update download page for 26.04.1 hot release [skip ci] #14719

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103 changes: 103 additions & 0 deletions docs/archive.md
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---
Below are archived releases for RAPIDS Accelerator for Apache Spark.

## Release v26.04.0
### Hardware Requirements:

The plugin is designed to work on NVIDIA Volta, Turing, Ampere, Ada Lovelace, Hopper and Blackwell generation datacenter GPUs. The plugin jar is tested on the following GPUs:

GPU Models: NVIDIA V100, T4, A10, A100, L4, H100 and B100 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 22.04, Ubuntu 24.04, Rocky Linux 8 and Rocky Linux 9

NVIDIA Driver*: R525+

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 3.3.0, 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, 3.4.4
Apache Spark 3.5.0, 3.5.1, 3.5.2, 3.5.3, 3.5.4, 3.5.5, 3.5.6, 3.5.7, 3.5.8
Apache Spark 4.0.0, 4.0.1, 4.0.2
Apache Spark 4.1.1
Scala 2.12: Spark 3.3.0 through 3.5.8
Scala 2.13: Spark 3.5.0 through 3.5.8, and Spark 4.0.0, 4.0.1, 4.0.2, and 4.1.1

Supported Databricks runtime versions for Azure and AWS:
Databricks 13.3 ML LTS (GPU, Scala 2.12, Spark 3.4.1)
Databricks 14.3 ML LTS (GPU, Scala 2.12, Spark 3.5.0)
Databricks 17.3 ML LTS (GPU, Scala 2.13, Spark 4.0.0)

Supported Dataproc versions (Debian/Ubuntu/Rocky):
GCP Dataproc 2.1
GCP Dataproc 2.2
GCP Dataproc 2.3

Supported Dataproc Serverless versions:
Spark runtime 1.1 LTS
Spark runtime 1.2
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 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 v26.04.0

#### CUDA 12

| Processor | Scala Version | Download Jar | Download Signature | Download From Maven |
|-----------|---------------|--------------|--------------------|---------------------|
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/>&lt;/dependency&gt;</pre> |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/>&lt;/dependency&gt;</pre> |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0-cuda12-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda12-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0-cuda12-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda12-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |


#### CUDA 13

| Processor | Scala Version | Download Jar | Download Signature | Download From Maven |
|-----------|---------------|--------------|--------------------|---------------------|
| x86_64 | Scala 2.12 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0-cuda13.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0-cuda13.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda13&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
| x86_64 | Scala 2.13 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0-cuda13.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0-cuda13.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda13&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
| arm64 | Scala 2.12 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0-cuda13-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.04.0/rapids-4-spark_2.12-26.04.0-cuda13-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.12&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda13-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |
| arm64 | Scala 2.13 | [RAPIDS Accelerator v26.04.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0-cuda13-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/26.04.0/rapids-4-spark_2.13-26.04.0-cuda13-arm64.jar.asc) | <pre>&lt;dependency&gt;<br/> &lt;groupId&gt;com.nvidia&lt;/groupId&gt;<br/> &lt;artifactId&gt;rapids-4-spark_2.13&lt;/artifactId&gt;<br/> &lt;version&gt;26.04.0&lt;/version&gt;<br/> &lt;classifier&gt;cuda13-arm64&lt;/classifier&gt;<br/>&lt;/dependency&gt;</pre> |


The above packages are built against CUDA 12.9 or CUDA 13.1. They are tested on V100, T4, A10, A100, L4, H100 and GB100 GPUs.

### 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_2.12-26.04.0.jar.asc rapids-4-spark_2.12-26.04.0.jar`
* Verify the signature for Scala 2.13 jar:
`gpg --verify rapids-4-spark_2.13-26.04.0.jar.asc rapids-4-spark_2.13-26.04.0.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
* Databricks 17.3 ML LTS (Spark 4.0) support (Delta Lake fallback to CPU); Databricks 12.2 ML LTS no longer supported ([#14518](https://github.com/NVIDIA/spark-rapids/pull/14518))
* Iceberg 1.10.1 support with Spark 4.0.2 ([#14459](https://github.com/NVIDIA/spark-rapids/pull/14459))
* Bloom filter v2 support on Databricks ([#14406](https://github.com/NVIDIA/spark-rapids/pull/14406))
* Parquet GPU reader: defer resource collection until close ([#14490](https://github.com/NVIDIA/spark-rapids/pull/14490)); row-to-column per-batch retry for OOM recovery ([#14428](https://github.com/NVIDIA/spark-rapids/pull/14428))
* Shuffle and spilling: shuffle fanout OOM fix ([#14525](https://github.com/NVIDIA/spark-rapids/pull/14525)), thread-safe shuffle unregister ([#14513](https://github.com/NVIDIA/spark-rapids/pull/14513)), bounded retry logging for shuffle coalesce ([#14537](https://github.com/NVIDIA/spark-rapids/pull/14537))
* Window execution fixes for mixed ROWS windows ([#14533](https://github.com/NVIDIA/spark-rapids/pull/14533))

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

## Release v26.02.2
### Hardware Requirements:

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