[Doc] Update plugin versions for 24.10.0 [skip ci]

docs/get-started/xgboost-examples/csp/databricks/databricks.md

@@ -21,7 +21,7 @@ Navigate to your home directory in the UI and select **Create** > **File** from
 create an `init.sh` scripts with contents:   
    ```bash
    #!/bin/bash
-   sudo wget -O /databricks/jars/rapids-4-spark_2.12-24.08.1.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar
+   sudo wget -O /databricks/jars/rapids-4-spark_2.12-24.10.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar
    ```
 1. Select the Databricks Runtime Version from one of the supported runtimes specified in the
    Prerequisites section.
@@ -68,7 +68,7 @@ create an `init.sh` scripts with contents:
     ```bash
     spark.rapids.sql.python.gpu.enabled true
     spark.python.daemon.module rapids.daemon_databricks
-    spark.executorEnv.PYTHONPATH /databricks/jars/rapids-4-spark_2.12-24.08.1.jar:/databricks/spark/python
+    spark.executorEnv.PYTHONPATH /databricks/jars/rapids-4-spark_2.12-24.10.0.jar:/databricks/spark/python
     ```
    Note that since python memory pool require installing the cudf library, so you need to install cudf library in 
    each worker nodes `pip install cudf-cu11 --extra-index-url=https://pypi.nvidia.com` or disable python memory pool

docs/get-started/xgboost-examples/csp/databricks/init.sh

@@ -1,7 +1,7 @@
 sudo rm -f /databricks/jars/spark--maven-trees--ml--10.x--xgboost-gpu--ml.dmlc--xgboost4j-gpu_2.12--ml.dmlc__xgboost4j-gpu_2.12__1.5.2.jar
 sudo rm -f /databricks/jars/spark--maven-trees--ml--10.x--xgboost-gpu--ml.dmlc--xgboost4j-spark-gpu_2.12--ml.dmlc__xgboost4j-spark-gpu_2.12__1.5.2.jar
 
-sudo wget -O /databricks/jars/rapids-4-spark_2.12-24.08.1.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar
+sudo wget -O /databricks/jars/rapids-4-spark_2.12-24.10.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar
 sudo wget -O /databricks/jars/xgboost4j-gpu_2.12-1.7.1.jar https://repo1.maven.org/maven2/ml/dmlc/xgboost4j-gpu_2.12/1.7.1/xgboost4j-gpu_2.12-1.7.1.jar
 sudo wget -O /databricks/jars/xgboost4j-spark-gpu_2.12-1.7.1.jar https://repo1.maven.org/maven2/ml/dmlc/xgboost4j-spark-gpu_2.12/1.7.1/xgboost4j-spark-gpu_2.12-1.7.1.jar
 ls -ltr

docs/get-started/xgboost-examples/on-prem-cluster/kubernetes-scala.md

@@ -6,12 +6,12 @@ the reader will be able to run a sample Apache Spark XGBoost application on NVID
 Prerequisites
 -------------
 
-* Apache Spark 3.1.1+ (e.g.: Spark 3.1.1)
+* Apache Spark 3.2.0+ (e.g.: Spark 3.2.0)
 * Hardware Requirements
   * NVIDIA Pascal™ GPU architecture or better
   * Multi-node clusters with homogenous GPU configuration
 * Software Requirements
-  * Ubuntu 18.04, 20.04/CentOS7, Rocky Linux 8
+  * Ubuntu 20.04, 22.04/CentOS7, Rocky Linux 8
   * CUDA 11.0+
   * NVIDIA driver compatible with your CUDA
   * NCCL 2.7.8+
@@ -40,7 +40,7 @@ export SPARK_DOCKER_IMAGE=<gpu spark docker image repo and name>
 export SPARK_DOCKER_TAG=<spark docker image tag>
 
 pushd ${SPARK_HOME}
-wget https://github.com/NVIDIA/spark-rapids-examples/raw/branch-24.08/dockerfile/Dockerfile
+wget https://github.com/NVIDIA/spark-rapids-examples/raw/branch-24.10/dockerfile/Dockerfile
 
 # Optionally install additional jars into ${SPARK_HOME}/jars/
 

docs/get-started/xgboost-examples/on-prem-cluster/standalone-python.md

@@ -1,17 +1,17 @@
 Get Started with XGBoost4J-Spark on an Apache Spark Standalone Cluster
 ======================================================================
-This is a getting started guide to XGBoost4J-Spark on an Apache Spark 3.1+ Standalone Cluster.
+This is a getting started guide to XGBoost4J-Spark on an Apache Spark 3.2+ Standalone Cluster.
 At the end of this guide, the user can run a sample Apache Spark Python application that runs on NVIDIA GPUs.
 
 Prerequisites
 -------------
 
-* Apache Spark 3.1.1+ Standalone Cluster (e.g.: Spark 3.1.1)
+* Apache Spark 3.2.0+ (e.g.: Spark 3.2.0)
 * Hardware Requirements
   * NVIDIA Pascal™ GPU architecture or better
   * Multi-node clusters with homogenous GPU configuration
 * Software Requirements
-  * Ubuntu 18.04, 20.04/CentOS7, Rocky Linux 8
+  * Ubuntu 20.04, 22.04/CentOS7, Rocky Linux 8
   * CUDA 11.5+
   * NVIDIA driver compatible with your CUDA
   * NCCL 2.7.8+
@@ -31,7 +31,7 @@ In this example, we will limit the number of cores to 1, to match our dataset.
 Please see https://spark.apache.org/docs/latest/spark-standalone.html for more documentation regarding Standalone configuration.
 
 We use `SPARK_HOME` environment variable to point to the Apache Spark cluster.
-And here are the steps to enable the GPU resources discovery for Spark 3.1+.
+And here are the steps to enable the GPU resources discovery for Spark 3.2+.
 
 1. Copy the spark config file from template
 

docs/get-started/xgboost-examples/on-prem-cluster/standalone-scala.md

@@ -1,18 +1,18 @@
 Get Started with XGBoost4J-Spark on an Apache Spark Standalone Cluster
 ======================================================================
 
-This is a getting-started guide to XGBoost on an Apache Spark 3.1+ Standalone Cluster. At the end of this guide,
+This is a getting-started guide to XGBoost on an Apache Spark 3.2+ Standalone Cluster. At the end of this guide,
 the user can run a sample Apache Spark application that runs on NVIDIA GPUs.
 
 Prerequisites
 -------------
 
-* Apache Spark 3.1.1+ Standalone Cluster (e.g.: Spark 3.1.1)
+* Apache Spark 3.2.0+ Standalone Cluster (e.g.: Spark 3.2.0)
 * Hardware Requirements
   * NVIDIA Pascal™ GPU architecture or better
   * Multi-node clusters with homogenous GPU configuration
 * Software Requirements
-  * Ubuntu 18.04, 20.04/CentOS7, Rocky Linux 8
+  * Ubuntu 20.04, 22.04/CentOS7, Rocky Linux 8
   * CUDA 11.0+
   * NVIDIA driver compatible with your CUDA
   * NCCL 2.7.8+
@@ -28,7 +28,7 @@ In this example, we will limit the number of cores to 1, to match our dataset.
 Please see https://spark.apache.org/docs/latest/spark-standalone.html for more documentation regarding Standalone configuration.
 
 We use `SPARK_HOME` environment variable to point to the Apache Spark cluster.
-And here are steps to enable the GPU resources discovery for Spark 3.1+.
+And here are steps to enable the GPU resources discovery for Spark 3.2+.
 
 1. Copy the spark configure file from template.
 

docs/get-started/xgboost-examples/on-prem-cluster/yarn-python.md

@@ -6,12 +6,12 @@ At the end of this guide, the reader will be able to run a sample Apache Spark P
 Prerequisites
 -------------
 
-* Apache Spark 3.1.1+ running on YARN supporting GPU scheduling. (e.g.: Spark 3.1.1, Hadoop-Yarn 3.3.0)
+* Apache Spark 3.2.0+ running on YARN supporting GPU scheduling. (e.g.: Spark 3.2.0, Hadoop-Yarn 3.3.0)
 * Hardware Requirements
   * NVIDIA Pascal™ GPU architecture or better
   * Multi-node clusters with homogenous GPU configuration
 * Software Requirements
-  * Ubuntu 18.04, 20.04/CentOS7, Rocky Linux 8
+  * Ubuntu 20.04, 22.04/CentOS7, Rocky Linux 8
   * CUDA 11.5+
   * NVIDIA driver compatible with your CUDA
   * NCCL 2.7.8+

docs/get-started/xgboost-examples/on-prem-cluster/yarn-scala.md

@@ -7,12 +7,12 @@ At the end of this guide, the reader will be able to run a sample Apache Spark a
 Prerequisites
 -------------
 
-* Apache Spark 3.1.1+ running on YARN supporting GPU scheduling. (e.g.: Spark 3.1.1, Hadoop-Yarn 3.3.0)
+* Apache Spark 3.2.0+ running on YARN supporting GPU scheduling. (e.g.: Spark 3.2.0, Hadoop-Yarn 3.3.0)
 * Hardware Requirements
   * NVIDIA Pascal™ GPU architecture or better
   * Multi-node clusters with homogenous GPU configuration
 * Software Requirements
-  * Ubuntu 18.04, 20.04/CentOS7, Rocky Linux 8
+  * Ubuntu 20.04, 22.04/CentOS7, Rocky Linux 8
   * CUDA 11.0+
   * NVIDIA driver compatible with your CUDA
   * NCCL 2.7.8+

docs/get-started/xgboost-examples/prepare-package-data/preparation-python.md

@@ -5,7 +5,7 @@ For simplicity export the location to these jars. All examples assume the packag
 ### Download the jars
 
 Download the RAPIDS Accelerator for Apache Spark plugin jar
-  * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar)
+  * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar)
 
 ### Build XGBoost Python Examples
 

docs/get-started/xgboost-examples/prepare-package-data/preparation-scala.md

@@ -5,7 +5,7 @@ For simplicity export the location to these jars. All examples assume the packag
 ### Download the jars
 
 1. Download the RAPIDS Accelerator for Apache Spark plugin jar
-   * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar)
+   * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar)
 
 ### Build XGBoost Scala Examples
 

examples/ML+DL-Examples/Spark-Rapids-ML/pca/README.md

@@ -10,7 +10,7 @@ Please refer to the Spark-Rapids-ML [README](https://github.com/NVIDIA/spark-rap
 ## Download RAPIDS Jar from Maven Central
 
 Download the [Spark-Rapids plugin](https://nvidia.github.io/spark-rapids/docs/download.html#download-rapids-accelerator-for-apache-spark-v24081).  
-For Spark-RAPIDS-ML version 24.08, download the RAPIDS jar from Maven Central: [rapids-4-spark_2.12-24.08.1.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar). 
+For Spark-RAPIDS-ML version 24.10, download the RAPIDS jar from Maven Central: [rapids-4-spark_2.12-24.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar). 
 
 ## Running the Notebooks
 

examples/ML+DL-Examples/Spark-Rapids-ML/pca/notebooks/pca.ipynb

@@ -43,7 +43,7 @@
       "24/10/04 18:04:27 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n",
       "Setting default log level to \"WARN\".\n",
       "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
-      "24/10/04 18:04:27 WARN RapidsPluginUtils: RAPIDS Accelerator 24.08.1 using cudf 24.08.0, private revision 9fac64da220ddd6bf5626bd7bd1dd74c08603eac\n",
+      "24/10/04 18:04:27 WARN RapidsPluginUtils: RAPIDS Accelerator 24.10.0 using cudf 24.10.0, private revision 9fac64da220ddd6bf5626bd7bd1dd74c08603eac\n",
       "24/10/04 18:04:27 WARN RapidsPluginUtils: RAPIDS Accelerator is enabled, to disable GPU support set `spark.rapids.sql.enabled` to false.\n",
       "24/10/04 18:04:31 WARN GpuDeviceManager: RMM pool is disabled since spark.rapids.memory.gpu.pooling.enabled is set to false; however, this configuration is deprecated and the behavior may change in a future release.\n"
      ]
@@ -57,7 +57,7 @@
     "    import os\n",
     "    import requests\n",
     "\n",
-    "    SPARK_RAPIDS_VERSION = \"24.08.1\"\n",
+    "    SPARK_RAPIDS_VERSION = \"24.10.0\"\n",
     "    rapids_jar = f\"rapids-4-spark_2.12-{SPARK_RAPIDS_VERSION}.jar\"\n",
     "    if not os.path.exists(rapids_jar):\n",
     "        print(\"Downloading spark rapids jar\")\n",
@@ -539,7 +539,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "rapids-24.08",
+   "display_name": "rapids-24.10",
    "language": "python",
    "name": "python3"
   },

examples/SQL+DF-Examples/micro-benchmarks/notebooks/micro-benchmarks-gpu.ipynb

@@ -22,7 +22,7 @@
     "import os\n",
     "# Change to your cluster ip:port and directories\n",
     "SPARK_MASTER_URL = os.getenv(\"SPARK_MASTER_URL\", \"spark:your-ip:port\")\n",
-    "RAPIDS_JAR = os.getenv(\"RAPIDS_JAR\", \"/your-path/rapids-4-spark_2.12-24.08.1.jar\")\n"
+    "RAPIDS_JAR = os.getenv(\"RAPIDS_JAR\", \"/your-path/rapids-4-spark_2.12-24.10.0.jar\")\n"
    ]
   },
   {

examples/UDF-Examples/RAPIDS-accelerated-UDFs/README.md

@@ -186,7 +186,7 @@ then do the following inside the Docker container.
 
 ### Get jars from Maven Central
 
-[rapids-4-spark_2.12-24.08.1.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar)
+[rapids-4-spark_2.12-24.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar)
 
 
 ### Launch a local mode Spark

examples/UDF-Examples/RAPIDS-accelerated-UDFs/pom.xml

@@ -37,7 +37,7 @@
         <cuda.version>cuda11</cuda.version>
         <scala.binary.version>2.12</scala.binary.version>
         <!-- Depends on release version, Snapshot version is not published to the Maven Central -->
-        <rapids4spark.version>24.06.0</rapids4spark.version>
+        <rapids4spark.version>24.10.0</rapids4spark.version>
         <spark.version>3.1.1</spark.version>
         <scala.version>2.12.15</scala.version>
         <udf.native.build.path>${project.build.directory}/cpp-build</udf.native.build.path>

examples/XGBoost-Examples/agaricus/notebooks/python/agaricus-gpu.ipynb

@@ -73,7 +73,7 @@
       "Setting default log level to \"WARN\".\n",
       "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
       "2022-11-30 06:57:40,550 WARN resource.ResourceUtils: The configuration of cores (exec = 2 task = 1, runnable tasks = 2) will result in wasted resources due to resource gpu limiting the number of runnable tasks per executor to: 1. Please adjust your configuration.\n",
-      "2022-11-30 06:57:54,195 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator 24.08.1 using cudf 24.08.1.\n",
+      "2022-11-30 06:57:54,195 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator 24.10.0 using cudf 24.10.0.\n",
       "2022-11-30 06:57:54,210 WARN rapids.RapidsPluginUtils: spark.rapids.sql.multiThreadedRead.numThreads is set to 20.\n",
       "2022-11-30 06:57:54,214 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator is enabled, to disable GPU support set `spark.rapids.sql.enabled` to false.\n",
       "2022-11-30 06:57:54,214 WARN rapids.RapidsPluginUtils: spark.rapids.sql.explain is set to `NOT_ON_GPU`. Set it to 'NONE' to suppress the diagnostics logging about the query placement on the GPU.\n",

examples/XGBoost-Examples/mortgage/notebooks/python/MortgageETL.ipynb

@@ -6,18 +6,18 @@
    "source": [
     "## Prerequirement\n",
     "### 1. Download data\n",
-    "Dataset is derived from Fannie Mae’s [Single-Family Loan Performance Data](http://www.fanniemae.com/portal/funding-the-market/data/loan-performance-data.html) with all rights reserved by Fannie Mae. Refer to these [instructions](https://github.com/NVIDIA/spark-rapids-examples/blob/branch-24.08/docs/get-started/xgboost-examples/dataset/mortgage.md) to download the dataset.\n",
+    "Dataset is derived from Fannie Mae’s [Single-Family Loan Performance Data](http://www.fanniemae.com/portal/funding-the-market/data/loan-performance-data.html) with all rights reserved by Fannie Mae. Refer to these [instructions](https://github.com/NVIDIA/spark-rapids-examples/blob/branch-24.10/docs/get-started/xgboost-examples/dataset/mortgage.md) to download the dataset.\n",
     "\n",
     "### 2. Download needed jars\n",
-    "* [rapids-4-spark_2.12-24.08.1.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar)\n",
+    "* [rapids-4-spark_2.12-24.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar)\n",
     "\n",
     "\n",
     "### 3. Start Spark Standalone\n",
     "Before running the script, please setup Spark standalone mode\n",
     "\n",
     "### 4. Add ENV\n",
     "```\n",
-    "$ export SPARK_JARS=rapids-4-spark_2.12-24.08.1.jar\n",
+    "$ export SPARK_JARS=rapids-4-spark_2.12-24.10.0.jar\n",
     "$ export PYSPARK_DRIVER_PYTHON=jupyter \n",
     "$ export PYSPARK_DRIVER_PYTHON_OPTS=notebook\n",
     "```\n",

examples/XGBoost-Examples/mortgage/notebooks/python/cv-mortgage-gpu.ipynb

@@ -63,7 +63,7 @@
       "Setting default log level to \"WARN\".\n",
       "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
       "2022-11-25 09:34:43,952 WARN resource.ResourceUtils: The configuration of cores (exec = 4 task = 1, runnable tasks = 4) will result in wasted resources due to resource gpu limiting the number of runnable tasks per executor to: 1. Please adjust your configuration.\n",
-      "2022-11-25 09:34:58,155 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator 24.08.1 using cudf 24.08.1.\n",
+      "2022-11-25 09:34:58,155 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator 24.10.0 using cudf 24.10.0.\n",
       "2022-11-25 09:34:58,171 WARN rapids.RapidsPluginUtils: spark.rapids.sql.multiThreadedRead.numThreads is set to 20.\n",
       "2022-11-25 09:34:58,175 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator is enabled, to disable GPU support set `spark.rapids.sql.enabled` to false.\n",
       "2022-11-25 09:34:58,175 WARN rapids.RapidsPluginUtils: spark.rapids.sql.explain is set to `NOT_ON_GPU`. Set it to 'NONE' to suppress the diagnostics logging about the query placement on the GPU.\n"

examples/XGBoost-Examples/mortgage/notebooks/python/mortgage-gpu.ipynb

@@ -84,7 +84,7 @@
       "22/11/24 06:14:06 INFO org.apache.spark.SparkEnv: Registering BlockManagerMaster\n",
       "22/11/24 06:14:06 INFO org.apache.spark.SparkEnv: Registering BlockManagerMasterHeartbeat\n",
       "22/11/24 06:14:06 INFO org.apache.spark.SparkEnv: Registering OutputCommitCoordinator\n",
-      "22/11/24 06:14:07 WARN com.nvidia.spark.rapids.RapidsPluginUtils: RAPIDS Accelerator 24.08.1 using cudf 24.08.1.\n",
+      "22/11/24 06:14:07 WARN com.nvidia.spark.rapids.RapidsPluginUtils: RAPIDS Accelerator 24.10.0 using cudf 24.10.0.\n",
       "22/11/24 06:14:07 WARN com.nvidia.spark.rapids.RapidsPluginUtils: spark.rapids.sql.multiThreadedRead.numThreads is set to 20.\n",
       "22/11/24 06:14:07 WARN com.nvidia.spark.rapids.RapidsPluginUtils: RAPIDS Accelerator is enabled, to disable GPU support set `spark.rapids.sql.enabled` to false.\n",
       "22/11/24 06:14:07 WARN com.nvidia.spark.rapids.RapidsPluginUtils: spark.rapids.sql.explain is set to `NOT_ON_GPU`. Set it to 'NONE' to suppress the diagnostics logging about the query placement on the GPU.\n"

examples/XGBoost-Examples/mortgage/notebooks/scala/mortgage-ETL.ipynb

@@ -20,14 +20,14 @@
     "Refer to these [instructions](https://github.com/NVIDIA/spark-rapids-examples/blob/branch-23.12/docs/get-started/xgboost-examples/dataset/mortgage.md) to download the dataset.\n",
     "\n",
     "### 2. Download needed jars\n",
-    "* [rapids-4-spark_2.12-24.08.1.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar)\n",
+    "* [rapids-4-spark_2.12-24.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar)\n",
     "\n",
     "### 3. Start Spark Standalone\n",
     "Before Running the script, please setup Spark standalone mode\n",
     "\n",
     "### 4. Add ENV\n",
     "```\n",
-    "$ export SPARK_JARS=rapids-4-spark_2.12-24.08.1.jar\n",
+    "$ export SPARK_JARS=rapids-4-spark_2.12-24.10.0.jar\n",
     "\n",
     "```\n",
     "\n",

examples/XGBoost-Examples/taxi/notebooks/python/cv-taxi-gpu.ipynb

@@ -62,7 +62,7 @@
       "Setting default log level to \"WARN\".\n",
       "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
       "2022-11-30 08:02:10,103 WARN resource.ResourceUtils: The configuration of cores (exec = 2 task = 1, runnable tasks = 2) will result in wasted resources due to resource gpu limiting the number of runnable tasks per executor to: 1. Please adjust your configuration.\n",
-      "2022-11-30 08:02:23,737 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator 24.08.1 using cudf 24.08.1.\n",
+      "2022-11-30 08:02:23,737 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator 24.10.0 using cudf 24.10.0.\n",
       "2022-11-30 08:02:23,752 WARN rapids.RapidsPluginUtils: spark.rapids.sql.multiThreadedRead.numThreads is set to 20.\n",
       "2022-11-30 08:02:23,756 WARN rapids.RapidsPluginUtils: RAPIDS Accelerator is enabled, to disable GPU support set `spark.rapids.sql.enabled` to false.\n",
       "2022-11-30 08:02:23,757 WARN rapids.RapidsPluginUtils: spark.rapids.sql.explain is set to `NOT_ON_GPU`. Set it to 'NONE' to suppress the diagnostics logging about the query placement on the GPU.\n",

examples/XGBoost-Examples/taxi/notebooks/python/taxi-ETL.ipynb

@@ -19,14 +19,14 @@
     "All data could be found at https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page\n",
     "\n",
     "### 2. Download needed jars\n",
-    "* [rapids-4-spark_2.12-24.08.1.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.08.1/rapids-4-spark_2.12-24.08.1.jar)\n",
+    "* [rapids-4-spark_2.12-24.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/24.10.0/rapids-4-spark_2.12-24.10.0.jar)\n",
     "\n",
     "### 3. Start Spark Standalone\n",
     "Before running the script, please setup Spark standalone mode\n",
     "\n",
     "### 4. Add ENV\n",
     "```\n",
-    "$ export SPARK_JARS=rapids-4-spark_2.12-24.08.1.jar\n",
+    "$ export SPARK_JARS=rapids-4-spark_2.12-24.10.0.jar\n",
     "$ export PYSPARK_DRIVER_PYTHON=jupyter \n",
     "$ export PYSPARK_DRIVER_PYTHON_OPTS=notebook\n",
     "```\n",