Building Spark with Maven

Building Spark using Maven Requires Maven 3 (the build process is tested with Maven 3.0.4) and Java 1.6 or newer.

Setting up Maven’s Memory Usage

You’ll need to configure Maven to use more memory than usual by setting MAVEN_OPTS. We recommend the following settings:

export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m"

If you don’t run this, you may see errors like the following:

[INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-2.9.3/classes...
[ERROR] PermGen space -> [Help 1]

[INFO] Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-2.9.3/classes...
[ERROR] Java heap space -> [Help 1]

You can fix this by setting the MAVEN_OPTS variable as discussed before.

Specifying the Hadoop version

Because HDFS is not protocol-compatible across versions, if you want to read from HDFS, you’ll need to build Spark against the specific HDFS version in your environment. You can do this through the “hadoop.version” property. If unset, Spark will build against Hadoop 1.0.4 by default.

For Apache Hadoop versions 1.x, Cloudera CDH MRv1, and other Hadoop versions without YARN, use:

# Apache Hadoop 1.2.1
$ mvn -Dhadoop.version=1.2.1 -DskipTests clean package

# Cloudera CDH 4.2.0 with MapReduce v1
$ mvn -Dhadoop.version=2.0.0-mr1-cdh4.2.0 -DskipTests clean package

For Apache Hadoop 2.x, 0.23.x, Cloudera CDH MRv2, and other Hadoop versions with YARN, you should enable the “hadoop2-yarn” profile and set the “yarn.version” property:

# Apache Hadoop 2.0.5-alpha
$ mvn -Phadoop2-yarn -Dhadoop.version=2.0.5-alpha -Dyarn.version=2.0.5-alpha -DskipTests clean package

# Cloudera CDH 4.2.0 with MapReduce v2
$ mvn -Phadoop2-yarn -Dhadoop.version=2.0.0-cdh4.2.0 -Dyarn.version=2.0.0-chd4.2.0 -DskipTests clean package

Hadoop versions 2.2.x and newer can be built by setting the new-yarn and the yarn.version as follows:

# Apache Hadoop 2.2.X and newer
$ mvn -Pnew-yarn -Dhadoop.version=2.2.0 -Dyarn.version=2.2.0 -DskipTests clean package

The build process handles Hadoop 2.2.x as a special case that uses the directory new-yarn, which supports the new YARN API. Furthermore, for this version, the build depends on artifacts published by the spark-project to enable Akka 2.0.5 to work with protobuf 2.5.

Spark Tests in Maven

Tests are run by default via the ScalaTest Maven plugin. Some of the require Spark to be packaged first, so always run mvn package with -DskipTests the first time. You can then run the tests with mvn -Dhadoop.version=... test.

The ScalaTest plugin also supports running only a specific test suite as follows:

$ mvn -Dhadoop.version=... -Dsuites=spark.repl.ReplSuite test

Continuous Compilation

We use the scala-maven-plugin which supports incremental and continuous compilation. E.g.

$ mvn scala:cc

should run continuous compilation (i.e. wait for changes). However, this has not been tested extensively.

Using With IntelliJ IDEA

This setup works fine in IntelliJ IDEA 11.1.4. After opening the project via the pom.xml file in the project root folder, you only need to activate either the hadoop1 or hadoop2 profile in the “Maven Properties” popout. We have not tried Eclipse/Scala IDE with this.

Building Spark Debian Packages

It includes support for building a Debian package containing a ‘fat-jar’ which includes the repl, the examples and bagel. This can be created by specifying the following profiles:

$ mvn -Prepl-bin -Pdeb clean package

The debian package can then be found under repl/target. We added the short commit hash to the file name so that we can distinguish individual packages build for SNAPSHOT versions.