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nvliyuan merged 2 commits into from
Jun 24, 2026
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update the plugin version to v26.06.0 #635

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95183f5
update the plugin version to v26.06.0
nvliyuan Jun 24, 2026
51e1a4d
Update examples/ML+DL-Examples/Spark-Rapids-ML/pca/README.md
nvliyuan Jun 24, 2026
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4 changes: 2 additions & 2 deletions docs/get-started/xgboost-examples/csp/databricks/databricks.md
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Expand Up @@ -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_2.12-26.02.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar
sudo wget -O /databricks/jars/rapids-4-spark_2.12-26.06.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.jar
```
1. Select the Databricks Runtime Version from one of the supported runtimes specified in the
Prerequisites section.
Expand Down Expand Up @@ -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_2.12-26.02.0.jar:/databricks/spark/python
spark.executorEnv.PYTHONPATH /databricks/jars/rapids-4-spark_2.12-26.06.0.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
Expand Down
2 changes: 1 addition & 1 deletion docs/get-started/xgboost-examples/csp/databricks/init.sh
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Expand Up @@ -17,7 +17,7 @@
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_2.12-26.02.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar
sudo wget -O /databricks/jars/rapids-4-spark_2.12-26.06.0.jar https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.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
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2 changes: 1 addition & 1 deletion docs/get-started/xgboost-examples/prepare-package-data/preparation-python.md
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Expand Up @@ -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_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)
* [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.jar)

### Build XGBoost Python Examples

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2 changes: 1 addition & 1 deletion docs/get-started/xgboost-examples/prepare-package-data/preparation-scala.md
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Expand Up @@ -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_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)
* [RAPIDS Spark Package](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.jar)

### Build XGBoost Scala Examples

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4 changes: 2 additions & 2 deletions examples/ML+DL-Examples/Optuna-Spark/README.md
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Expand Up @@ -147,8 +147,8 @@ We use [RAPIDS](https://docs.rapids.ai/install/#get-rapids) for GPU-accelerated
``` shell
sudo apt install libmysqlclient-dev

conda create -n rapids-26.02 -c rapidsai -c conda-forge -c nvidia \
cudf=26.02 cuml=26.02 python=3.10 'cuda-version>=12.0,<=12.5'
conda create -n rapids-26.06 -c rapidsai -c conda-forge -c nvidia \
cudf=26.06 cuml=26.06 python=3.10 'cuda-version>=12.0,<=12.5'
conda activate optuna-spark
pip install mysqlclient
pip install optuna joblib joblibspark ipywidgets
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2 changes: 1 addition & 1 deletion examples/ML+DL-Examples/Optuna-Spark/optuna-examples/databricks/init_optuna.sh
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Expand Up @@ -55,7 +55,7 @@ fi


# rapids import
SPARK_RAPIDS_VERSION=26.02.0
SPARK_RAPIDS_VERSION=26.06.0
curl -L https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/${SPARK_RAPIDS_VERSION}/rapids-4-spark_2.12-${SPARK_RAPIDS_VERSION}.jar -o \
/databricks/jars/rapids-4-spark_2.12-${SPARK_RAPIDS_VERSION}.jar

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2 changes: 1 addition & 1 deletion examples/ML+DL-Examples/Optuna-Spark/optuna-examples/databricks/start_cluster.sh
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Expand Up @@ -26,7 +26,7 @@ json_config=$(cat <<EOF
"spark_version": "13.3.x-gpu-ml-scala2.12",
"spark_conf": {
"spark.task.resource.gpu.amount": "1",
"spark.executorEnv.PYTHONPATH": "/databricks/jars/rapids-4-spark_2.12-26.02.0.jar:/databricks/spark/python:/databricks/python3",
"spark.executorEnv.PYTHONPATH": "/databricks/jars/rapids-4-spark_2.12-26.06.0.jar:/databricks/spark/python:/databricks/python3",
"spark.executor.cores": "8",
"spark.rapids.memory.gpu.minAllocFraction": "0.0001",
"spark.plugins": "com.nvidia.spark.SQLPlugin",
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4 changes: 2 additions & 2 deletions examples/ML+DL-Examples/Optuna-Spark/optuna-examples/optuna-dataframe.ipynb
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Expand Up @@ -372,7 +372,7 @@
"[I 2024-12-11 23:47:48,724] Trial 0 finished with value: 0.6377619522504244 and parameters: {'learning_rate': 0.005611516415334507, 'max_depth': 10, 'subsample': 0.7453942447208348, 'colsample_bytree': 0.6187255599871848, 'min_child_weight': 4, 'num_boost_round': 162}. Best is trial 0 with value: 0.6377619522504244.\n",
"[I 2024-12-11 23:47:49,676] Trial 1 finished with value: 0.6703788974319568 and parameters: {'learning_rate': 0.0013066739238053278, 'max_depth': 9, 'subsample': 0.6210592611560484, 'colsample_bytree': 0.7226689489062432, 'min_child_weight': 1, 'num_boost_round': 488}. Best is trial 0 with value: 0.6377619522504244.\n",
"[I 2024-12-11 23:47:49,819] Trial 2 finished with value: 0.6181751362616256 and parameters: {'learning_rate': 0.04622589001020832, 'max_depth': 3, 'subsample': 0.2227337188467456, 'colsample_bytree': 0.22423428436076215, 'min_child_weight': 7, 'num_boost_round': 310}. Best is trial 2 with value: 0.6181751362616256.\n",

@greptile-apps greptile-apps Bot Jun 24, 2026

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P2 Unexplained modification to cached notebook output

The subsample value in a pre-stored trial log output from December 2024 changed from 0.6312602499862605 to 0.6312606499862605 — a difference in the 7th decimal place. This historical output line is unrelated to the version bump and appears to be an accidental edit. Modifying stored outputs without re-running the notebook makes the notebook's recorded results inconsistent with what was actually computed.

"[I 2024-12-11 23:47:49,942] Trial 3 finished with value: 0.6698576232920956 and parameters: {'learning_rate': 0.007309539835912915, 'max_depth': 3, 'subsample': 0.6312602499862605, 'colsample_bytree': 0.18251916761943976, 'min_child_weight': 6, 'num_boost_round': 246}. Best is trial 2 with value: 0.6181751362616256.\n",
"[I 2024-12-11 23:47:49,942] Trial 3 finished with value: 0.6698576232920956 and parameters: {'learning_rate': 0.007309539835912915, 'max_depth': 3, 'subsample': 0.6312606499862605, 'colsample_bytree': 0.18251916761943976, 'min_child_weight': 6, 'num_boost_round': 246}. Best is trial 2 with value: 0.6181751362616256.\n",
"[I 2024-12-11 23:47:50,060] Trial 4 finished with value: 0.6704590546150145 and parameters: {'learning_rate': 0.008168455894760165, 'max_depth': 8, 'subsample': 0.23969009305044175, 'colsample_bytree': 0.538522716492931, 'min_child_weight': 12, 'num_boost_round': 118}. Best is trial 2 with value: 0.6181751362616256.\n",
"[I 2024-12-11 23:47:50,214] Trial 5 finished with value: 0.6088806682631155 and parameters: {'learning_rate': 0.016409286730647923, 'max_depth': 2, 'subsample': 0.11179901333601554, 'colsample_bytree': 0.9514412603906666, 'min_child_weight': 20, 'num_boost_round': 424}. Best is trial 5 with value: 0.6088806682631155.\n",
"[I 2024-12-11 23:47:50,289] Trial 6 finished with value: 0.7103495949713845 and parameters: {'learning_rate': 0.0040665633135147945, 'max_depth': 1, 'subsample': 0.700021375186549, 'colsample_bytree': 0.4681448690526212, 'min_child_weight': 3, 'num_boost_round': 298}. Best is trial 5 with value: 0.6088806682631155.\n",
Expand Down Expand Up @@ -451,7 +451,7 @@
],
"source": [
"def get_rapids_jar():\n",
" SPARK_RAPIDS_VERSION = \"26.02.0\"\n",
" SPARK_RAPIDS_VERSION = \"26.06.0\"\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",
Expand Down
10 changes: 5 additions & 5 deletions examples/ML+DL-Examples/Spark-Rapids-ML/pca/README.md
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@@ -1,16 +1,16 @@
# Spark-Rapids-ML PCA example

This is an example of the GPU accelerated PCA algorithm from the [Spark-Rapids-ML](https://github.com/NVIDIA/spark-rapids-ml) library, which provides PySpark ML compatible algorithms powered by RAPIDS cuML.
The notebook uses PCA to reduce a random dataset with 2048 feature dimensions to 3 dimensions. We train both the GPU and CPU algorithms for comparison.
This is an example of the GPU accelerated PCA algorithm from the [Spark-Rapids-ML](https://github.com/NVIDIA/spark-rapids-ml) library, which provides PySpark ML compatible algorithms powered by RAPIDS cuML.
The notebook uses PCA to reduce a random dataset with 2048 feature dimensions to 3 dimensions. We train both the GPU and CPU algorithms for comparison.

## Build

Please refer to the Spark-Rapids-ML [README](https://github.com/NVIDIA/spark-rapids-ml/blob/HEAD/python) to setup the RAPIDS conda environment and install Spark-Rapids-ML dependencies.
Please refer to the Spark-Rapids-ML [README](https://github.com/NVIDIA/spark-rapids-ml/blob/HEAD/python) to setup the RAPIDS conda environment and install Spark-Rapids-ML dependencies.

## 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 26.02.0, download the RAPIDS jar from Maven Central: [rapids-4-spark_2.12-26.02.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar).
Download the [Spark-Rapids plugin](https://nvidia.github.io/spark-rapids/docs/download.html#download-rapids-accelerator-for-apache-spark-v24081).
Comment thread
nvliyuan marked this conversation as resolved.
Outdated
For Spark-RAPIDS-ML version 26.06.0, download the RAPIDS jar from Maven Central: [rapids-4-spark_2.12-26.06.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.jar).

## Running the Notebooks

Expand Down
2 changes: 1 addition & 1 deletion examples/ML+DL-Examples/Spark-Rapids-ML/pca/notebooks/pca.ipynb
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Expand Up @@ -57,7 +57,7 @@
" import os\n",
" import requests\n",
"\n",
" SPARK_RAPIDS_VERSION = \"26.02.0\"\n",
" SPARK_RAPIDS_VERSION = \"26.06.0\"\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",
Expand Down
2 changes: 1 addition & 1 deletion examples/SQL+DF-Examples/micro-benchmarks/notebooks/micro-benchmarks-gpu.ipynb
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Expand Up @@ -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_2.12-26.02.0.jar\")\n"
"RAPIDS_JAR = os.getenv(\"RAPIDS_JAR\", \"/your-path/rapids-4-spark_2.12-26.06.0.jar\")\n"
]
},
{
Expand Down
2 changes: 1 addition & 1 deletion examples/SQL+DF-Examples/tpcds/README.md
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Expand Up @@ -23,6 +23,6 @@ Google Colab and connect it to a [GPU instance](https://research.google.com/cola
</a>

Here is the bar chart from a recent execution on Google Colab's T4 High RAM instance using
RAPIDS Spark 26.02.0 with Apache Spark 3.5.0
RAPIDS Spark 26.06.0 with Apache Spark 3.5.0

![tpcds-speedup](/docs/img/guides/tpcds.png)
2 changes: 1 addition & 1 deletion examples/SQL+DF-Examples/tpcds/notebooks/TPCDS-SF10.ipynb
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Expand Up @@ -30,7 +30,7 @@
"outputs": [],
"source": [
"spark_version='3.5.5'\n",
"rapids_version='26.02.0'\n",
"rapids_version='26.06.0'\n",
"sparkmeasure_version='0.27'"
]
},
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2 changes: 1 addition & 1 deletion examples/UDF-Examples/RAPIDS-accelerated-UDFs/README.md
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Expand Up @@ -274,7 +274,7 @@ then do the following inside the Docker container.

### Get jars from Maven Central

[rapids-4-spark_2.12-26.02.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)
[rapids-4-spark_2.12-26.06.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.jar)


### Launch a local mode Spark
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6 changes: 3 additions & 3 deletions examples/UDF-Examples/RAPIDS-accelerated-UDFs/extract-cudf-libs.sh
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Expand Up @@ -28,13 +28,13 @@
# ./extract-cudf-libs.sh
#
# Environment Variables (optional, will use pom.xml values if not set):
# RAPIDS4SPARK_VERSION - rapids-4-spark version (e.g., 26.02.0 or 26.06.0-SNAPSHOT)
# RAPIDS4SPARK_VERSION - rapids-4-spark version (e.g., 26.06.0 or 26.06.0-SNAPSHOT)
# SCALA_VERSION - Scala binary version (e.g., 2.12, 2.13)
# CUDA_VERSION - CUDA version (e.g., cuda11, cuda12)
# CUDF_BRANCH - cuDF git branch for headers (e.g., main, branch-26.02)
# CUDF_BRANCH - cuDF git branch for headers (e.g., main, branch-26.06)
#
# Example with overrides:
# RAPIDS4SPARK_VERSION=26.02.0 CUDA_VERSION=cuda11 ./extract-cudf-libs.sh
# RAPIDS4SPARK_VERSION=26.06.0 CUDA_VERSION=cuda11 ./extract-cudf-libs.sh
###############################################################################

set -e
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2 changes: 1 addition & 1 deletion examples/UDF-Examples/RAPIDS-accelerated-UDFs/pom.xml
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Expand Up @@ -37,7 +37,7 @@
<cuda.version>cuda12</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>26.02.0</rapids4spark.version>
<rapids4spark.version>26.06.0</rapids4spark.version>
<spark.version>3.1.1</spark.version>
<scala.version>2.12.15</scala.version>
<udf.native.build.path>${project.build.directory}/cpp-build</udf.native.build.path>
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4 changes: 2 additions & 2 deletions examples/XGBoost-Examples/mortgage/notebooks/python/MortgageETL.ipynb
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Expand Up @@ -9,15 +9,15 @@
"Dataset is derived from Fannie Mae’s [Single-Family Loan Performance Data](http://www.fanniemae.com/portal/funding-the-market/data/loan-performance-data.html) with all rights reserved by Fannie Mae. Refer to these [instructions](https://github.com/NVIDIA/spark-rapids-examples/blob/branch-24.12/docs/get-started/xgboost-examples/dataset/mortgage.md) to download the dataset.\n",
"\n",
"### 2. Download needed jars\n",
"* [rapids-4-spark_2.12-26.02.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)\n",
"* [rapids-4-spark_2.12-26.06.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.jar)\n",
"\n",
"\n",
"### 3. Start Spark Standalone\n",
"Before running the script, please setup Spark standalone mode\n",
"\n",
"### 4. Add ENV\n",
"```\n",
"$ export SPARK_JARS=rapids-4-spark_2.12-26.02.0.jar\n",
"$ export SPARK_JARS=rapids-4-spark_2.12-26.06.0.jar\n",
"$ export PYSPARK_DRIVER_PYTHON=jupyter \n",
"$ export PYSPARK_DRIVER_PYTHON_OPTS=notebook\n",
"```\n",
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4 changes: 2 additions & 2 deletions examples/XGBoost-Examples/mortgage/notebooks/scala/mortgage-ETL.ipynb
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Expand Up @@ -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_2.12-26.02.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)\n",
"* [rapids-4-spark_2.12-26.06.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.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_2.12-26.02.0.jar\n",
"$ export SPARK_JARS=rapids-4-spark_2.12-26.06.0.jar\n",
"\n",
"```\n",
"\n",
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4 changes: 2 additions & 2 deletions examples/XGBoost-Examples/taxi/notebooks/python/taxi-ETL.ipynb
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Expand Up @@ -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_2.12-26.02.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)\n",
"* [rapids-4-spark_2.12-26.06.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.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_2.12-26.02.0.jar\n",
"$ export SPARK_JARS=rapids-4-spark_2.12-26.06.0.jar\n",
"$ export PYSPARK_DRIVER_PYTHON=jupyter \n",
"$ export PYSPARK_DRIVER_PYTHON_OPTS=notebook\n",
"```\n",
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4 changes: 2 additions & 2 deletions examples/XGBoost-Examples/taxi/notebooks/scala/taxi-ETL.ipynb
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Expand Up @@ -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 jar\n",
"* [rapids-4-spark_2.12-26.02.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.02.0/rapids-4-spark_2.12-26.02.0.jar)\n",
"* [rapids-4-spark_2.12-26.06.0.jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/26.06.0/rapids-4-spark_2.12-26.06.0.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_2.12-26.02.0.jar\n",
"$ export SPARK_JARS=rapids-4-spark_2.12-26.06.0.jar\n",
"\n",
"```\n",
"\n",
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2 changes: 1 addition & 1 deletion examples/spark-connect-gpu/server/README.md
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Expand Up @@ -150,7 +150,7 @@ path. Otherwise, we use variables starting with `local_`.

### Spark Connect Server
- **Image**: Custom build based on `apache/spark:4.0.0` with Spark RAPIDS ETL and ML Plugins
- **RAPIDS Version**: 26.02.0 for CUDA 12
- **RAPIDS Version**: 26.06.0 for CUDA 12
- **Ports**: 15002 (gRPC), 4040 (Driver UI)
- **Configuration**: Optimized for GPU acceleration with memory management

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2 changes: 1 addition & 1 deletion examples/spark-connect-gpu/server/docker-compose.yaml
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Expand Up @@ -74,7 +74,7 @@ services:
dockerfile: Dockerfile
args:
- CUDA_VERSION=${CUDA_VERSION:-12}
- RAPIDS_VERSION=${RAPIDS_VERSION:-26.02.0}
- RAPIDS_VERSION=${RAPIDS_VERSION:-26.06.0}
- REPO_URL=${REPO_URL:-https://repo1.maven.org/maven2}
container_name: spark-connect-server
hostname: spark-connect-server
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2 changes: 1 addition & 1 deletion tools/databricks/README.md
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Expand Up @@ -19,4 +19,4 @@ top of the notebook. After that, select *Run all* to execute the tools for the
1. Multiple event logs must be comma-separated.
- For example: `/dbfs/path/to/eventlog1,/dbfs/path/to/eventlog2`

**Latest Tools Version Supported** 26.02.0
**Latest Tools Version Supported** 26.06.0