Thus, the full flow for running continuous-compilation of the core submodule may look more like: $. Specific submodules to work this is because submodules that depend on other submodules do so via You’ll typically need to run mvn install from the project root for compilation within It only scans the paths src/main and src/test (seeįrom within certain submodules that have that structure. However, this has not been testedĮxtensively. We use the scala-maven-plugin which supports incremental and continuous compilation. Where spark-streaming_2.11 is the artifactId as defined in streaming/pom.xml file. build/mvn -pl :spark-streaming_2.11 clean install It’s possible to build Spark submodules using the mvn -pl option.įor instance, you can build the Spark Streaming module using. Note: Flume support is deprecated as of Spark 2.3.0./build/mvn -Pflume -DskipTests clean package Building with Flume supportĪpache Flume support must be explicitly enabled with the flume profile. Kafka 0.10 support is still automatically built. Note: Kafka 0.8 support is deprecated as of Spark 2.3.0./build/mvn -Pkafka-0-8 -DskipTests clean package Kafka 0.8 support must be explicitly enabled with the kafka-0-8 profile. build/mvn -Pkubernetes -DskipTests clean package build/mvn -Pmesos -DskipTests clean packageīuilding with Kubernetes support. The hadoop-provided profile builds the assembly without including Hadoop-ecosystem projects, The Spark assembly and the version on each node, included with. On YARN deployments, thisĬauses multiple versions of these to appear on executor classpaths: the version packaged in The assembly directory produced by mvn package will, by default, include all of Spark’sĭependencies, including Hadoop and some of its ecosystem projects. Packaging without Hadoop Dependencies for YARN build/mvn -Pyarn -Phive -Phive-thriftserver -DskipTests clean package To enable Hive integration for Spark SQL along with its JDBC server and CLI,Īdd the -Phive and Phive-thriftserver profiles to your existing build options.īy default Spark will build with Hive 1.2.1 bindings. build/mvn -Pyarn -Phadoop-2.7 -Dhadoop.version=2.7.3 -DskipTests clean package build/mvn -Pyarn -DskipTests clean package You can enable the yarn profile and optionally set the yarn.version property if it is different If unset, Spark will build against Hadoop 2.6.X by default. You can specify the exact version of Hadoop to compile against through the hadoop.version property. dev/make-distribution.sh -help Specifying the Hadoop Version and Enabling YARN This will build Spark distribution along with Python pip and R packages. dev/make-distribution.sh -name custom-spark -pip -r -tgz -Psparkr -Phadoop-2.7 -Phive -Phive-thriftserver -Pmesos -Pyarn -Pkubernetes With Maven profile settings and so on like the direct Maven build. dev/make-distribution.sh in the project root directory. Spark Downloads page, and that is laid out so as
To create a Spark distribution like those distributed by the As an example, one can build a version of Spark as follows. build/mvn execution acts as a pass through to the mvn call allowing easy transition from previous build methods. It honors any mvn binary if present already, however, will pull down its own copy of Scala and Zinc regardless to ensure proper version requirements are met.
Pip install apache spark download#
This script will automatically download and setup all necessary build requirements ( Maven, Scala, and Zinc) locally within the build/ directory itself. Spark now comes packaged with a self-contained Maven installation to ease building and deployment of Spark from source located under the build/ directory. The test phase of the Spark build will automatically add these options to MAVEN_OPTS, even when not using build/mvn.If using build/mvn with no MAVEN_OPTS set, the script will automatically add the above options to the MAVEN_OPTS environment variable.You can fix these problems by setting the MAVEN_OPTS variable as discussed before. If you don’t add these parameters to MAVEN_OPTS, you may see errors and warnings like the following: Compiling 203 Scala sources and 9 Java sources to /Users/me/Development/spark/core/target/scala-2.12/classes. (The ReservedCodeCacheSize setting is optional but recommended.) You’ll need to configure Maven to use more memory than usual by setting MAVEN_OPTS: export MAVEN_OPTS="-Xmx2g -XX:ReservedCodeCacheSize=1g"
Note that support for Java 7 was removed as of Spark 2.2.0.
The Maven-based build is the build of reference for Apache Spark.īuilding Spark using Maven requires Maven 3.5.4 and Java 8.
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