Installation

Shared Deployment

Shared deployment implies that GridGain nodes are running independently from Apache Spark applications and store state even after Apache Spark jobs die. Similarly to Apache Spark, there are three ways to deploy GridGain to the cluster.

Standalone Deployment

In the Standalone deployment mode, GridGain nodes should be deployed together with Spark Worker nodes. After you install GridGain on all worker nodes, start a node on each Spark worker with your config using ignite.sh script.

Adding GridGain libraries to Spark classpath by default

Spark application deployment model allows dynamic jar distribution during application start. This model, however, has some drawbacks:

Spark dynamic class loader does not implement getResource methods, so you will not be able to access resources located in jar files.
Java logger uses application class loader (not the context class loader) to load log handlers which results in ClassNotFoundException when using Java logging in Ignite.

There is a way to alter the default Spark classpath for each launched application (this should be done on each machine of the Spark cluster, including master, worker and driver nodes).

Locate the $SPARK_HOME/conf/spark-env.sh file. If this file does not exist, create it from template using $SPARK_HOME/conf/spark-env.sh.template
Add the following lines to the end of the spark-env.sh file (uncomment the line setting IGNITE_HOME in case if you do not have it globally set):

# Optionally set IGNITE_HOME here.
# IGNITE_HOME=/path/to/ignite

IGNITE_LIBS="${IGNITE_HOME}/libs/*"

for file in ${IGNITE_HOME}/libs/*
do
    if [ -d ${file} ] && [ "${file}" != "${IGNITE_HOME}"/libs/optional ]; then
        IGNITE_LIBS=${IGNITE_LIBS}:${file}/*
    fi
done

export SPARK_CLASSPATH=$IGNITE_LIBS

Copy any folders required from the $IGNITE_HOME/libs/optional folder, such as ignite-log4j, to the $IGNITE_HOME/libs folder.

You can verify that the Spark classpath is changed by running bin/spark-shell and typing a simple import statement:

scala> import org.apache.ignite.configuration._
import org.apache.ignite.configuration._

Embedded Deployment

Embedded deployment means that GridGain nodes are started inside the Apache Spark job processes and are stopped when the job dies. There is no need for additional deployment steps in this case. GridGain code will be distributed to worker machines using the Apache Spark deployment mechanism and nodes will be started on all workers as part of the IgniteContext initialization.

Maven

Ignite’s Spark artifact is hosted in Maven Central. Depending on a Scala version you use, include the artifact using one of the dependencies shown below.

Scala 2.11+

<dependency>
  <groupId>org.apache.ignite</groupId>
  <artifactId>ignite-spark-ext</artifactId>
  <version>2.0.0</version>
</dependency>

SBT

If SBT is used as a build tool for a Scala application, then Ignite’s Spark artifact can be added into build.sbt with one of the commands below:

Scala 2.11

libraryDependencies += "org.apache.ignite" % "ignite-spark-ext" % "2.0.0"

Classpath Configuration

When IgniteRDD or Ignite Data Frames APIs are used, make sure that Spark executors and drivers have all the required Ignite jars available in their classpath. Spark provides several ways to modify the classpath of both the driver or the executor process.

Parameter Configuration

Ignite jars can be added to Spark using configuration parameters such as spark.driver.extraClassPath and spark.executor.extraClassPath. Refer to the Spark official documentation for all available options.

The following shows how to fill in spark.driver.extraClassPath parameters:

spark.executor.extraClassPath /opt/ignite/libs/*:/opt/ignite/libs/optional/ignite-spark-ext/*:/opt/ignite/libs/optional/ignite-log4j2/*:/opt/ignite/libs/optional/ignite-yarn-ext/*:/opt/ignite/libs/ignite-spring/*

Source Code Configuration

Spark provides APIs to set up extra libraries from the application code. You can provide Ignite jars in the following way:

private val MAVEN_HOME = "/home/user/.m2/repository"

val spark = SparkSession.builder()
       .appName("Spark Ignite data sources example")
       .master("spark://172.17.0.2:7077")
       .getOrCreate()

spark.sparkContext.addJar(MAVEN_HOME + "/org/apache/ignite/ignite-core/2.4.0/ignite-core-2.4.0.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/apache/ignite/ignite-spring/2.4.0/ignite-spring-2.4.0.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/apache/ignite/ignite-log4j/2.4.0/ignite-log4j-2.4.0.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/apache/ignite/ignite-spark/2.4.0/ignite-spark-2.4.0.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/apache/ignite/ignite-indexing/2.4.0/ignite-indexing-2.4.0.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/springframework/spring-beans/4.3.7.RELEASE/spring-beans-4.3.7.RELEASE.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/springframework/spring-core/4.3.7.RELEASE/spring-core-4.3.7.RELEASE.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/springframework/spring-context/4.3.7.RELEASE/spring-context-4.3.7.RELEASE.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/org/springframework/spring-expression/4.3.7.RELEASE/spring-expression-4.3.7.RELEASE.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/javax/cache/cache-api/1.0.0/cache-api-1.0.0.jar")
spark.sparkContext.addJar(MAVEN_HOME + "/com/h2database/h2/1.4.195/h2-1.4.195.jar")

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Last updated on Oct 09, 2024