merge dev-2210 branch to Main branch (#237)

* Init 22.10.0-SNAPSHOT (#214)

Signed-off-by: Peixin Li <[email protected]>

Signed-off-by: Peixin Li <[email protected]>

* update version and fix some document error, add more comments for running xgboost notebooks on GCP (#215) (#222)

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

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

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

* update version and fix some document error, add more comments for running xgboost notebooks on GCP (#215) (#224)

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

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

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

* Update default cmake to 3.23.X in udf exmaple dockerfile (#227)

Signed-off-by: Peixin Li <[email protected]>

Signed-off-by: Peixin Li <[email protected]>

* [xgboost] Remove default parameters (#226)

* remove the default parameters for xgboost examples

* remove the default parameters

Signed-off-by: Bobby Wang <[email protected]>

* remove unused variables for mortgage-ETL

Signed-off-by: Bobby Wang <[email protected]>

* add more details/notes for the mortgage perforamcne tests (#229)

* add more details/notes for the mortgage perforamcne tests

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

* Update examples/XGBoost-Examples/README.md

Co-authored-by: Hao Zhu <[email protected]>

* Update examples/XGBoost-Examples/README.md

Co-authored-by: Hao Zhu <[email protected]>

* Update examples/XGBoost-Examples/README.md

Co-authored-by: Hao Zhu <[email protected]>

Signed-off-by: liyuan <[email protected]>
Co-authored-by: Hao Zhu <[email protected]>

* Enable automerge from 22.10 to 22.12 (#230)

Signed-off-by: Peixin Li <[email protected]>

Signed-off-by: Peixin Li <[email protected]>

* update versions for v22.10 release (#235)

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

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

Signed-off-by: Peixin Li <[email protected]>
Signed-off-by: liyuan <[email protected]>
Signed-off-by: Bobby Wang <[email protected]>
Co-authored-by: Jenkins Automation <[email protected]>
Co-authored-by: Peixin <[email protected]>
Co-authored-by: Bobby Wang <[email protected]>
Co-authored-by: Hao Zhu <[email protected]>

Author: 5 people

.github/workflows/auto-merge.yml

@@ -18,7 +18,7 @@ name: auto-merge HEAD to BASE
 on:
   pull_request_target:
     branches:
-    - branch-22.08
+    - branch-22.10
     types: [closed]
 
 jobs:
@@ -29,13 +29,13 @@ jobs:
     steps:
       - uses: actions/checkout@v2
         with:
-          ref: branch-22.08 # force to fetch from latest upstream instead of PR ref
+          ref: branch-22.10 # force to fetch from latest upstream instead of PR ref
 
       - name: auto-merge job
         uses: ./.github/workflows/auto-merge
         env:
           OWNER: NVIDIA
           REPO_NAME: spark-rapids-examples
-          HEAD: branch-22.08
-          BASE: branch-22.10
+          HEAD: branch-22.10
+          BASE: branch-22.12
           AUTOMERGE_TOKEN: ${{ secrets.AUTOMERGE_TOKEN }} # use to merge PR

docs/get-started/xgboost-examples/csp/databricks/generate-init-script-10.4.ipynb

@@ -24,7 +24,7 @@
    "source": [
     "%sh\n",
     "cd ../../dbfs/FileStore/jars/\n",
-    "sudo wget -O rapids-4-spark_2.12-22.08.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar\n",
+    "sudo wget -O rapids-4-spark_2.12-22.10.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar\n",
     "sudo wget -O xgboost4j-gpu_2.12-1.6.1.jar https://repo1.maven.org/maven2/ml/dmlc/xgboost4j-gpu_2.12/1.6.1/xgboost4j-gpu_2.12-1.6.1.jar\n",
     "sudo wget -O xgboost4j-spark-gpu_2.12-1.6.1.jar https://repo1.maven.org/maven2/ml/dmlc/xgboost4j-spark-gpu_2.12/1.6.1/xgboost4j-spark-gpu_2.12-1.6.1.jar\n",
     "ls -ltr\n",
@@ -60,7 +60,7 @@
     "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\n",
     "\n",
     "sudo cp /dbfs/FileStore/jars/xgboost4j-gpu_2.12-1.6.1.jar /databricks/jars/\n",
-    "sudo cp /dbfs/FileStore/jars/rapids-4-spark_2.12-22.08.0.jar /databricks/jars/\n",
+    "sudo cp /dbfs/FileStore/jars/rapids-4-spark_2.12-22.10.0.jar /databricks/jars/\n",
     "sudo cp /dbfs/FileStore/jars/xgboost4j-spark-gpu_2.12-1.6.1.jar /databricks/jars/\"\"\", True)"
    ]
   },
@@ -133,7 +133,7 @@
     "1. Edit your cluster, adding an initialization script from `dbfs:/databricks/init_scripts/init.sh` in the \"Advanced Options\" under \"Init Scripts\" tab\n",
     "2. Reboot the cluster\n",
     "3. Go to \"Libraries\" tab under your cluster and install `dbfs:/FileStore/jars/xgboost4j-spark-gpu_2.12-1.6.1.jar` in your cluster by selecting the \"DBFS\" option for installing jars\n",
-    "4. Import the mortgage example notebook from `https://github.com/NVIDIA/spark-rapids-examples/blob/branch-22.08/examples/XGBoost-Examples/mortgage/notebooks/python/mortgage-gpu.ipynb`\n",
+    "4. Import the mortgage example notebook from `https://github.com/NVIDIA/spark-rapids-examples/blob/branch-22.10/examples/XGBoost-Examples/mortgage/notebooks/python/mortgage-gpu.ipynb`\n",
     "5. Inside the mortgage example notebook, update the data paths\n",
     "  `train_data = reader.schema(schema).option('header', True).csv('/data/mortgage/csv/small-train.csv')`\n",
     "  `trans_data = reader.schema(schema).option('header', True).csv('/data/mortgage/csv/small-trans.csv')`"

docs/get-started/xgboost-examples/csp/databricks/generate-init-script.ipynb

@@ -24,7 +24,7 @@
    "source": [
     "%sh\n",
     "cd ../../dbfs/FileStore/jars/\n",
-    "sudo wget -O rapids-4-spark_2.12-22.08.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar\n",
+    "sudo wget -O rapids-4-spark_2.12-22.10.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar\n",
     "sudo wget -O xgboost4j-gpu_2.12-1.6.1.jar https://repo1.maven.org/maven2/ml/dmlc/xgboost4j-gpu_2.12/1.6.1/xgboost4j-gpu_2.12-1.6.1.jar\n",
     "sudo wget -O xgboost4j-spark-gpu_2.12-1.6.1.jar https://repo1.maven.org/maven2/ml/dmlc/xgboost4j-spark-gpu_2.12/1.6.1/xgboost4j-spark-gpu_2.12-1.6.1.jar\n",
     "ls -ltr\n",
@@ -60,7 +60,7 @@
     "sudo rm -f /databricks/jars/spark--maven-trees--ml--9.x--xgboost-gpu--ml.dmlc--xgboost4j-spark-gpu_2.12--ml.dmlc__xgboost4j-spark-gpu_2.12__1.4.1.jar\n",
     "\n",
     "sudo cp /dbfs/FileStore/jars/xgboost4j-gpu_2.12-1.6.1.jar /databricks/jars/\n",
-    "sudo cp /dbfs/FileStore/jars/rapids-4-spark_2.12-22.08.0.jar /databricks/jars/\n",
+    "sudo cp /dbfs/FileStore/jars/rapids-4-spark_2.12-22.10.0.jar /databricks/jars/\n",
     "sudo cp /dbfs/FileStore/jars/xgboost4j-spark-gpu_2.12-1.6.1.jar /databricks/jars/\"\"\", True)"
    ]
   },
@@ -133,7 +133,7 @@
     "1. Edit your cluster, adding an initialization script from `dbfs:/databricks/init_scripts/init.sh` in the \"Advanced Options\" under \"Init Scripts\" tab\n",
     "2. Reboot the cluster\n",
     "3. Go to \"Libraries\" tab under your cluster and install `dbfs:/FileStore/jars/xgboost4j-spark-gpu_2.12-1.6.1.jar` in your cluster by selecting the \"DBFS\" option for installing jars\n",
-    "4. Import the mortgage example notebook from `https://github.com/NVIDIA/spark-rapids-examples/blob/branch-22.08/examples/XGBoost-Examples/mortgage/notebooks/python/mortgage-gpu.ipynb`\n",
+    "4. Import the mortgage example notebook from `https://github.com/NVIDIA/spark-rapids-examples/blob/branch-22.10/examples/XGBoost-Examples/mortgage/notebooks/python/mortgage-gpu.ipynb`\n",
     "5. Inside the mortgage example notebook, update the data paths\n",
     "  `train_data = reader.schema(schema).option('header', True).csv('/data/mortgage/csv/small-train.csv')`\n",
     "  `trans_data = reader.schema(schema).option('header', True).csv('/data/mortgage/csv/small-trans.csv')`"

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

@@ -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-22.08/dockerfile/Dockerfile
+wget https://github.com/NVIDIA/spark-rapids-examples/raw/branch-22.10/dockerfile/Dockerfile
 
 # Optionally install additional jars into ${SPARK_HOME}/jars/
 

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

@@ -9,7 +9,7 @@ For simplicity export the location to these jars. All examples assume the packag
    * [XGBoost4j-Spark Package](https://repo1.maven.org/maven2/com/nvidia/xgboost4j-spark_3.0/1.4.2-0.3.0/)
 
 2. Download the RAPIDS Accelerator for Apache Spark plugin jar
-   * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar)
+   * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar)
 
 ### Build XGBoost Python Examples
 
@@ -26,7 +26,7 @@ You need to copy the dataset to `/opt/xgboost`. Use the following links to downl
 
 ``` bash
 export SPARK_XGBOOST_DIR=/opt/xgboost
-export RAPIDS_JAR=${SPARK_XGBOOST_DIR}/rapids-4-spark_2.12-22.08.0.jar
+export RAPIDS_JAR=${SPARK_XGBOOST_DIR}/rapids-4-spark_2.12-22.10.0.jar
 export XGBOOST4J_JAR=${SPARK_XGBOOST_DIR}/xgboost4j_3.0-1.4.2-0.3.0.jar
 export XGBOOST4J_SPARK_JAR=${SPARK_XGBOOST_DIR}/xgboost4j-spark_3.0-1.4.2-0.3.0.jar
 export SAMPLE_ZIP=${SPARK_XGBOOST_DIR}/samples.zip

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_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar)
+   * [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar)
 
 ### Build XGBoost Scala Examples
 
@@ -22,6 +22,6 @@ You need to copy the dataset to `/opt/xgboost`. Use the following links to downl
 
 ``` bash
 export SPARK_XGBOOST_DIR=/opt/xgboost
-export RAPIDS_JAR=${SPARK_XGBOOST_DIR}/rapids-4-spark_2.12-22.08.0.jar
+export RAPIDS_JAR=${SPARK_XGBOOST_DIR}/rapids-4-spark_2.12-22.10.0.jar
 export SAMPLE_JAR=${SPARK_XGBOOST_DIR}/sample_xgboost_apps-0.2.3-jar-with-dependencies.jar
 ```

examples/ML+DL-Examples/Spark-cuML/pca/Dockerfile

@@ -17,7 +17,7 @@
 
 ARG CUDA_VER=11.5.1
 FROM nvidia/cuda:${CUDA_VER}-devel-ubuntu20.04
-ARG BRANCH_VER=22.08
+ARG BRANCH_VER=22.10
 
 RUN apt-get update
 RUN apt-get install -y wget ninja-build git

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

@@ -12,7 +12,7 @@ User can also download the release jar from Maven central:
 
 [rapids-4-spark-ml_2.12-22.02.0-cuda11.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark-ml_2.12/22.02.0/rapids-4-spark-ml_2.12-22.02.0-cuda11.jar)
 
-[rapids-4-spark_2.12-22.08.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar)
+[rapids-4-spark_2.12-22.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar)
 
 
 ## Sample code
@@ -48,7 +48,7 @@ It is assumed that a Standalone Spark cluster has been set up, the `SPARK_MASTER
 
     ``` bash
     RAPIDS_ML_JAR=PATH_TO_rapids-4-spark-ml_2.12-22.02.0-cuda11.jar
-    PLUGIN_JAR=PATH_TO_rapids-4-spark_2.12-22.08.0.jar
+    PLUGIN_JAR=PATH_TO_rapids-4-spark_2.12-22.10.0.jar
 
     jupyter toree install                                \
     --spark_home=${SPARK_HOME}                             \

examples/ML+DL-Examples/Spark-cuML/pca/pom.xml

@@ -21,7 +21,7 @@
     <groupId>com.nvidia</groupId>
     <artifactId>PCAExample</artifactId>
     <packaging>jar</packaging>
-    <version>22.08.0-SNAPSHOT</version>
+    <version>22.10.0-SNAPSHOT</version>
 
     <properties>
         <maven.compiler.source>8</maven.compiler.source>
@@ -51,7 +51,7 @@
         <dependency>
             <groupId>com.nvidia</groupId>
             <artifactId>rapids-4-spark-ml_2.12</artifactId>
-            <version>22.08.0-SNAPSHOT</version>
+            <version>22.10.0-SNAPSHOT</version>
         </dependency>
     </dependencies>
 

examples/ML+DL-Examples/Spark-cuML/pca/spark-submit.sh

@@ -15,8 +15,8 @@
 # limitations under the License.
 #
 
-ML_JAR=/root/.m2/repository/com/nvidia/rapids-4-spark-ml_2.12/22.08.0-SNAPSHOT/rapids-4-spark-ml_2.12-22.08.0-SNAPSHOT.jar
-PLUGIN_JAR=/root/.m2/repository/com/nvidia/rapids-4-spark_2.12/22.08.0-SNAPSHOT/rapids-4-spark_2.12-22.08.0-SNAPSHOT.jar
+ML_JAR=/root/.m2/repository/com/nvidia/rapids-4-spark-ml_2.12/22.10.0-SNAPSHOT/rapids-4-spark-ml_2.12-22.10.0-SNAPSHOT.jar
+PLUGIN_JAR=/root/.m2/repository/com/nvidia/rapids-4-spark_2.12/22.10.0-SNAPSHOT/rapids-4-spark_2.12-22.10.0-SNAPSHOT.jar
 
 $SPARK_HOME/bin/spark-submit \
 --master spark://127.0.0.1:7077  \
@@ -38,4 +38,4 @@ $SPARK_HOME/bin/spark-submit \
 --conf spark.network.timeout=1000s \
 --jars $ML_JAR,$PLUGIN_JAR \
 --class com.nvidia.spark.examples.pca.Main \
-/workspace/target/PCAExample-22.08.0-SNAPSHOT.jar
+/workspace/target/PCAExample-22.10.0-SNAPSHOT.jar

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_2.12-22.08.0.jar\")\n"
+    "RAPIDS_JAR = os.getenv(\"RAPIDS_JAR\", \"/your-path/rapids-4-spark_2.12-22.10.0.jar\")\n"
    ]
   },
   {

examples/UDF-Examples/RAPIDS-accelerated-UDFs/Dockerfile

@@ -58,7 +58,7 @@ CUDA_VERSION_MINOR=$(echo $CUDA_VERSION | tr -d '.' | cut -c 3); \
 # Set JDK8 as the default Java
 && update-alternatives --set java /usr/lib/jvm/java-8-openjdk-amd64/jre/bin/java
 
-ARG CMAKE_VERSION=3.20.5
+ARG CMAKE_VERSION=3.23.3
 
 # Install CMake
 RUN cd /tmp \

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

@@ -108,7 +108,7 @@ See above Prerequisites section
 First finish the steps in "Building with Native Code Examples and run test cases" section, then do the following in the docker.
 
 ### Get jars from Maven Central
-[rapids-4-spark_2.12-22.08.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar)
+[rapids-4-spark_2.12-22.10.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar)
 
 ### Launch a local mode Spark
 

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

@@ -25,7 +25,7 @@
         user defined functions for use with the RAPIDS Accelerator
         for Apache Spark
     </description>
-    <version>22.08.0-SNAPSHOT</version>
+    <version>22.10.0-SNAPSHOT</version>
 
     <properties>
         <maven.compiler.source>1.8</maven.compiler.source>
@@ -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>22.08.0</rapids4spark.version>
+        <rapids4spark.version>22.10.0</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/UDF-Examples/RAPIDS-accelerated-UDFs/src/main/cpp/CMakeLists.txt

@@ -14,9 +14,9 @@
 # limitations under the License.
 #=============================================================================
 
-cmake_minimum_required(VERSION 3.20.1 FATAL_ERROR)
+cmake_minimum_required(VERSION 3.23.1 FATAL_ERROR)
 
-file(DOWNLOAD https://raw.githubusercontent.com/rapidsai/rapids-cmake/branch-22.08/RAPIDS.cmake
+file(DOWNLOAD https://raw.githubusercontent.com/rapidsai/rapids-cmake/branch-22.10/RAPIDS.cmake
      ${CMAKE_BINARY_DIR}/RAPIDS.cmake)
 include(${CMAKE_BINARY_DIR}/RAPIDS.cmake)
 
@@ -32,7 +32,7 @@ if(DEFINED GPU_ARCHS)
 endif()
 rapids_cuda_init_architectures(UDFEXAMPLESJNI)
 
-project(UDFEXAMPLESJNI VERSION 22.08.0 LANGUAGES C CXX CUDA)
+project(UDFEXAMPLESJNI VERSION 22.10.0 LANGUAGES C CXX CUDA)
 
 option(PER_THREAD_DEFAULT_STREAM "Build with per-thread default stream" OFF)
 option(BUILD_UDF_BENCHMARKS "Build the benchmarks" OFF)
@@ -84,10 +84,10 @@ set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -w --expt-extended-lambda --expt-relax
 set(CUDA_USE_STATIC_CUDA_RUNTIME OFF)
 
 rapids_cpm_init()
-rapids_cpm_find(cudf 22.08.00
+rapids_cpm_find(cudf 22.10.00
         CPM_ARGS
         GIT_REPOSITORY  https://github.com/rapidsai/cudf.git
-        GIT_TAG         branch-22.08
+        GIT_TAG         branch-22.10
         GIT_SHALLOW     TRUE
         SOURCE_SUBDIR   cpp
         OPTIONS         "BUILD_TESTS OFF"

examples/UDF-Examples/Spark-cuSpatial/Dockerfile

@@ -39,7 +39,7 @@ RUN conda --version
 RUN conda install -c conda-forge openjdk=8 maven=3.8.1 -y
 
 # install cuDF dependency.
-RUN conda install -c rapidsai -c nvidia -c conda-forge -c defaults libcuspatial=22.08 python=3.8 -y
+RUN conda install -c rapidsai -c nvidia -c conda-forge -c defaults libcuspatial=22.10 python=3.8 -y
 
 RUN wget --quiet \
     https://github.com/Kitware/CMake/releases/download/v3.21.3/cmake-3.21.3-linux-x86_64.tar.gz \

examples/UDF-Examples/Spark-cuSpatial/Dockerfile.awsdb

@@ -48,7 +48,7 @@ RUN wget -q https://repo.continuum.io/miniconda/Miniconda3-py38_4.9.2-Linux-x86_
     conda config --system --set always_yes True && \
     conda clean --all
 
-RUN conda install -c rapidsai-nightly -c nvidia -c conda-forge  -c defaults libcuspatial=22.08
+RUN conda install -c rapidsai-nightly -c nvidia -c conda-forge  -c defaults libcuspatial=22.10
 RUN conda install -c conda-forge libgdal==3.3.1
 RUN pip install jupyter
 ENV JAVA_HOME /usr/lib/jvm/java-1.8.0-openjdk-amd64

examples/UDF-Examples/Spark-cuSpatial/README.md

@@ -65,9 +65,9 @@ Note: The docker env is just for building the jar, not for running the applicati
 4. [cuspatial](https://github.com/rapidsai/cuspatial): install libcuspatial
     ```Bash
     # Install libcuspatial from conda
-    conda install -c rapidsai -c nvidia -c conda-forge  -c defaults libcuspatial=22.06
+    conda install -c rapidsai -c nvidia -c conda-forge  -c defaults libcuspatial=22.10
     # or below command for the nightly (aka SNAPSHOT) version.
-    conda install -c rapidsai-nightly -c nvidia -c conda-forge  -c defaults libcuspatial=22.08
+    conda install -c rapidsai-nightly -c nvidia -c conda-forge  -c defaults libcuspatial=22.10
     ```
 5. Build the JAR using `mvn package`.
      ```Bash
@@ -86,7 +86,7 @@ Note: The docker env is just for building the jar, not for running the applicati
 2. Set up [a standalone cluster](/docs/get-started/xgboost-examples/on-prem-cluster/standalone-scala.md) of Spark. Make sure the conda/lib is included in LD_LIBRARY_PATH, so that spark executors can load libcuspatial.so.
 
 3. Download Spark RAPIDS JAR
-   * [Spark RAPIDS JAR v22.08.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.08.0/rapids-4-spark_2.12-22.08.0.jar) or above
+   * [Spark RAPIDS JAR v22.10.0](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/22.10.0/rapids-4-spark_2.12-22.10.0.jar) or above
 4. Prepare sample dataset and JARs. Copy the [sample dataset](../../../datasets/cuspatial_data.tar.gz) to `/data/cuspatial_data/`.
     Copy Spark RAPIDS JAR and `spark-cuspatial-<version>.jar` to `/data/cuspatial_data/jars/`.
     If you build the `spark-cuspatial-<version>.jar` in docker, please copy the jar from docker to local:

examples/UDF-Examples/Spark-cuSpatial/gpu-run.sh

@@ -31,7 +31,7 @@ rm -rf $DATA_OUT_PATH
 # the path to keep the jars of spark-rapids & spark-cuspatial
 JARS=$ROOT_PATH/jars
 
-JARS_PATH=${JARS_PATH:-$JARS/rapids-4-spark_2.12-22.08.0.jar,$JARS/spark-cuspatial-22.08.0-SNAPSHOT.jar}
+JARS_PATH=${JARS_PATH:-$JARS/rapids-4-spark_2.12-22.10.0.jar,$JARS/spark-cuspatial-22.10.0-SNAPSHOT.jar}
 
 $SPARK_HOME/bin/spark-submit --master spark://$HOSTNAME:7077 \
 --name "Gpu Spatial Join UDF" \

examples/UDF-Examples/Spark-cuSpatial/notebooks/cuspatial_sample_standalone.ipynb

@@ -9,7 +9,7 @@
    "source": [
     "from pyspark.sql import SparkSession\n",
     "import os\n",
-    "jarsPath = os.getenv(\"JARS_PATH\", \"/data/cuspatial_data/jars/rapids-4-spark_2.12-22.08.0.jar,/data/cuspatial_data/jars/spark-cuspatial-22.08.0-SNAPSHOT.jar\")\n",
+    "jarsPath = os.getenv(\"JARS_PATH\", \"/data/cuspatial_data/jars/rapids-4-spark_2.12-22.10.0.jar,/data/cuspatial_data/jars/spark-cuspatial-22.10.0-SNAPSHOT.jar\")\n",
     "spark = SparkSession.builder \\\n",
     "    .config(\"spark.jars\", jarsPath) \\\n",
     "    .config(\"spark.sql.adaptive.enabled\", \"false\") \\\n",

examples/UDF-Examples/Spark-cuSpatial/pom.xml

@@ -24,13 +24,13 @@
   <name>UDF of the cuSpatial case for the RAPIDS Accelerator</name>
   <description>The RAPIDS accelerated user defined function of the cuSpatial case
     for use with the RAPIDS Accelerator for Apache Spark</description>
-  <version>22.08.0-SNAPSHOT</version>
+  <version>22.10.0-SNAPSHOT</version>
 
   <properties>
     <maven.compiler.source>1.8</maven.compiler.source>
     <maven.compiler.target>1.8</maven.compiler.target>
     <java.major.version>8</java.major.version>
-    <rapids.version>22.08.0</rapids.version>
+    <rapids.version>22.10.0</rapids.version>
     <scala.binary.version>2.12</scala.binary.version>
     <spark.version>3.2.0</spark.version>
     <udf.native.build.path>${project.build.directory}/cpp-build</udf.native.build.path>

examples/UDF-Examples/Spark-cuSpatial/src/main/native/CMakeLists.txt

@@ -16,7 +16,7 @@
 
 cmake_minimum_required(VERSION 3.20.1 FATAL_ERROR)
 
-project(SPATIALUDJNI VERSION 22.08.0 LANGUAGES C CXX CUDA)
+project(SPATIALUDJNI VERSION 22.10.0 LANGUAGES C CXX CUDA)
 
 ###################################################################################################
 # - build type ------------------------------------------------------------------------------------

examples/XGBoost-Examples/README.md

@@ -12,6 +12,10 @@ In the public cloud, better performance can lead to significantly lower costs as
 
 ![mortgage-speedup](/docs/img/guides/mortgage-perf.png)
 
+Note that the test result is based on 21 years [Fannie Mea Single-Family Loan Performance Data](https://capitalmarkets.fanniemae.com/credit-risk-transfer/single-family-credit-risk-transfer/fannie-mae-single-family-loan-performance-data) 
+with a 4 A100 GPU and 512 CPU vcores cluster, the performance is affected by many aspects, 
+including data size and type of GPU. 
+
 In this folder, there are three blue prints for users to learn about using 
 Spark XGBoost and RAPIDS Accelerator on GPUs :
 

examples/XGBoost-Examples/agaricus/scala/src/com/nvidia/spark/examples/agaricus/Main.scala

@@ -63,9 +63,6 @@ object Main {
     val xgbClassificationModel = if (xgboostArgs.isToTrain) {
       // build XGBoost classifier
       val paramMap = xgboostArgs.xgboostParams(Map(
-        "eta" -> 0.1,
-        "missing" -> 0.0,
-        "max_depth" -> 2,
         "objective" -> "binary:logistic",
         "eval_sets" -> datasets(1).map(ds => Map("eval" -> ds)).getOrElse(Map.empty)
       ))