Get started with Sparkling Water in a few easy steps
1. Download Spark (if not already installed) from the Spark Downloads Page
2. Point SPARK_HOME to the existing installation of Spark and export variable MASTER.
export SPARK_HOME="/path/to/spark/installation"
# To launch a local Spark cluster with 3 worker nodes with 2 cores and 1g per node.
export MASTER="local-cluster[3,2,1024]"
3. From your terminal, run:
cd ~/Downloads
unzip sparkling-water-1.6.3.zip
cd sparkling-water-1.6.3
bin/sparkling-shell --conf "spark.executor.memory=1g"
4. Create an H2O cloud inside the Spark cluster:
import org.apache.spark.h2o._
val h2oContext = H2OContext.getOrCreate(sc)
import h2oContext._
5. Follow this demo, which imports airlines and weather data and runs predictions on delays.
Launch Sparkling Water on Hadoop using Yarn.
1. Download Spark (if not already installed) from the Spark Downloads Page.
2. Point SPARK_HOME to an existing installation of Spark:
export SPARK_HOME='/path/to/spark/installation'
3. Set the HADOOP_CONF_DIR and Spark MASTER environmental variables.
export HADOOP_CONF_DIR=/etc/hadoop/conf
export MASTER="yarn-client"
4. Download Spark and Use spark-submit to launch Sparkling Shell on YARN.
wget /sparkling-water-1.6.3.zip
unzip sparkling-water-1.6.3.zip
cd sparkling-water-1.6.3/
bin/sparkling-shell --num-executors 3 --executor-memory 2g --master yarn-client
5. Create an H2O cloud inside the Spark cluster:
import org.apache.spark.h2o._
val h2oContext = H2OContext.getOrCreate(sc)
import h2oContext._
Launch H2O on a Standalone Spark Cluster
1. Download Spark (if not already installed) from the Spark Downloads Page.
2. Point SPARK_HOME to an existing installation of Spark:
export SPARK_HOME='/path/to/spark/installation'
3. From your terminal, run:
cd ~/Downloads
unzip sparkling-water-1.6.3.zip
cd sparkling-water-1.6.3
bin/launch-spark-cloud.sh
export MASTER="spark://localhost:7077"
bin/sparkling-shell
4. Create an H2O cloud inside the Spark cluster:
import org.apache.spark.h2o._
val h2oContext = H2OContext.getOrCreate(sc)
import h2oContext._
Documentation
Integration info
- H2O version: 3.8.2.3 turchin (documentation)
- Spark version: 1.6.1 (documentation)