From db8e7afa6b5d9a76b1f6cf8f6f9954bc27f724cb Mon Sep 17 00:00:00 2001 From: liyuan Date: Tue, 9 Dec 2025 14:28:24 +0800 Subject: [PATCH] update for download page 2512 release Signed-off-by: liyuan --- docs/archive.md | 91 ++++++++++++++++++++++++++++++++++++++++++++++++ docs/download.md | 34 +++++++++--------- 2 files changed, 107 insertions(+), 18 deletions(-) diff --git a/docs/archive.md b/docs/archive.md index 2d88bcd3cd6..78a1eb94958 100644 --- a/docs/archive.md +++ b/docs/archive.md @@ -5,6 +5,97 @@ nav_order: 15 --- Below are archived releases for RAPIDS Accelerator for Apache Spark. +## Release v25.10.0 +### 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 3.2.0, 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, 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 + Apache Spark 4.0.0, 4.0.1 + + Supported Databricks runtime versions for Azure and AWS: + 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) + Databricks 14.3 ML LTS (GPU, Scala 2.12, Spark 3.5.0) + + 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 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 v25.10.0 + +| Processor | Scala Version | Download Jar | Download Signature | Download From Maven | +|-----------|---------------|--------------|--------------------|---------------------| +| x86_64 | Scala 2.12 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.12</artifactId>
    <version>25.10.0</version>
</dependency>
| +| x86_64 | Scala 2.13 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.13</artifactId>
    <version>25.10.0</version>
</dependency>
| +| arm64 | Scala 2.12 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0-cuda12-arm64.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.12</artifactId>
    <version>25.10.0</version>
    <classifier>cuda12-arm64</classifier>
</dependency>
| +| arm64 | Scala 2.13 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0-cuda12-arm64.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.13</artifactId>
    <version>25.10.0</version>
    <classifier>cuda12-arm64</classifier>
</dependency>
| + +This package is built against CUDA 12.9. It is tested on V100, T4, A10, A100, L4, H100 and GB100 GPUs with +CUDA 12.9. + +### 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_2.12-25.10.0.jar.asc rapids-4-spark_2.12-25.10.0.jar` +* Verify the signature for Scala 2.13 jar: + `gpg --verify rapids-4-spark_2.13-25.10.0.jar.asc rapids-4-spark_2.13-25.10.0.jar` + +The output of signature verify: + + gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) " + +### Release Notes +* Delta Lake liquid clustering read/write/optimize support +* Delta Lake optimize support +* Delta Lake deletion vector support with two caveats: need to set `useMetadataRowIndex=false` and deletion vector support will fall back to the CPU when using the coalescing file reader (these limitations to be removed in a future release) +* Iceberg insert operations support and improved write job statistics tracking +* Improved performance for stddev and variance operations in hash based group by aggregations +* Support for uuid +* Added Spark 4.0.1 support +* Added CUDA 13 support, in addition to CUDA 12 support. + +Note: There is a known issue in the 25.10.0 release when decompressing gzip files on H100 GPUs. +Please find more details in [issue-16661](https://github.com/rapidsai/cudf/issues/16661). + ## Release v25.08.0 ### Hardware Requirements: diff --git a/docs/download.md b/docs/download.md index c705a75aeef..2ba3d23bed3 100644 --- a/docs/download.md +++ b/docs/download.md @@ -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 v25.10.0 +## Release v25.12.0 ### 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: @@ -72,14 +72,14 @@ 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 v25.10.0 +### Download RAPIDS Accelerator for Apache Spark v25.12.0 | Processor | Scala Version | Download Jar | Download Signature | Download From Maven | |-----------|---------------|--------------|--------------------|---------------------| -| x86_64 | Scala 2.12 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.12</artifactId>
    <version>25.10.0</version>
</dependency>
| -| x86_64 | Scala 2.13 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.13</artifactId>
    <version>25.10.0</version>
</dependency>
| -| arm64 | Scala 2.12 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.10.0/rapids-4-spark_2.12-25.10.0-cuda12-arm64.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.12</artifactId>
    <version>25.10.0</version>
    <classifier>cuda12-arm64</classifier>
</dependency>
| -| arm64 | Scala 2.13 | [RAPIDS Accelerator v25.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.10.0/rapids-4-spark_2.13-25.10.0-cuda12-arm64.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.13</artifactId>
    <version>25.10.0</version>
    <classifier>cuda12-arm64</classifier>
</dependency>
| +| x86_64 | Scala 2.12 | [RAPIDS Accelerator v25.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.12.0/rapids-4-spark_2.12-25.12.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.12.0/rapids-4-spark_2.12-25.12.0.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.12</artifactId>
    <version>25.12.0</version>
</dependency>
| +| x86_64 | Scala 2.13 | [RAPIDS Accelerator v25.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.12.0/rapids-4-spark_2.13-25.12.0.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.12.0/rapids-4-spark_2.13-25.12.0.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.13</artifactId>
    <version>25.12.0</version>
</dependency>
| +| arm64 | Scala 2.12 | [RAPIDS Accelerator v25.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.12.0/rapids-4-spark_2.12-25.12.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/25.12.0/rapids-4-spark_2.12-25.12.0-cuda12-arm64.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.12</artifactId>
    <version>25.12.0</version>
    <classifier>cuda12-arm64</classifier>
</dependency>
| +| arm64 | Scala 2.13 | [RAPIDS Accelerator v25.12.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.12.0/rapids-4-spark_2.13-25.12.0-cuda12-arm64.jar) | [Signature](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.13/25.12.0/rapids-4-spark_2.13-25.12.0-cuda12-arm64.jar.asc) | 
<dependency>
    <groupId>com.nvidia</groupId>
    <artifactId>rapids-4-spark_2.13</artifactId>
    <version>25.12.0</version>
    <classifier>cuda12-arm64</classifier>
</dependency>
| This package is built against CUDA 12.9. It is tested on V100, T4, A10, A100, L4, H100 and GB100 GPUs with CUDA 12.9. @@ -88,25 +88,23 @@ CUDA 12.9. * 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_2.12-25.10.0.jar.asc rapids-4-spark_2.12-25.10.0.jar` + `gpg --verify rapids-4-spark_2.12-25.12.0.jar.asc rapids-4-spark_2.12-25.12.0.jar` * Verify the signature for Scala 2.13 jar: - `gpg --verify rapids-4-spark_2.13-25.10.0.jar.asc rapids-4-spark_2.13-25.10.0.jar` + `gpg --verify rapids-4-spark_2.13-25.12.0.jar.asc rapids-4-spark_2.13-25.12.0.jar` The output of signature verify: gpg: Good signature from "NVIDIA Spark (For the signature of spark-rapids release jars) " ### Release Notes -* Delta Lake liquid clustering read/write/optimize support -* Delta Lake optimize support -* Delta Lake deletion vector support with two caveats: need to set `useMetadataRowIndex=false` and deletion vector support will fall back to the CPU when using the coalescing file reader (these limitations to be removed in a future release) -* Iceberg insert operations support and improved write job statistics tracking -* Improved performance for stddev and variance operations in hash based group by aggregations -* Support for uuid -* Added Spark 4.0.1 support -* Added CUDA 13 support, in addition to CUDA 12 support. - -Note: There is a known issue in the 25.10.0 release when decompressing gzip files on H100 GPUs. +* Iceberg enhancements including DML operations (delete, update, merge) for merge-on-read tables, partition transforms (year/month/day/hour/truncate), and write operations enabled by default. +* Delta Lake clustered tables DML support including update, merge, and delete operations with deletion vector enabled GPU by default. +* Join improvements including support for left-outer joins with no columns, new join strategies with logging and heuristic configurations, and improved gather map ordering. +* CSV support for GBK encoded data. +* Refine GpuTaskMetrics over the spill framework. +* Fix race condition due to premature disk handle exposure. + +Note: There is a known issue in the 25.12.0 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