LinkedIn Gradle Plugin for Apache Hadoop
The LinkedIn Gradle Plugin for Apache Hadoop (which we shall refer to as simply the "Hadoop Plugin" for brevity) will help you more effectively build, test and deploy Hadoop applications.
In particular, the Plugin will help you easily work with Hadoop applications like Apache Pig and build workflows for Hadoop workflow schedulers such as Azkaban and Apache Oozie.
The Plugin includes the LinkedIn Gradle DSL for Apache Hadoop (which we shall refer to as simply the "Hadoop DSL" for brevity), a language for specifying jobs and workflows for Azkaban.
Hadoop Plugin User Guide
The Hadoop Plugin User Guide is available at User Guide.
Hadoop DSL Language Reference
The Hadoop DSL Language Reference is available at Hadoop DSL Language Reference.
Getting the Hadoop Plugin
The Hadoop Plugin is now published at plugins.gradle.org.
Click on the link for a short snippet to add to your
build.gradle file to start using the Hadoop
Can I Benefit from the Hadoop Plugin and Hadoop DSL?
You must use Gradle as your build system to use the Hadoop Plugin. If you are using Azkaban, you should start using the Hadoop Plugin immediately and you should use the Hadoop DSL to develop all of your Azkaban workflows.
If you are using Apache Pig, the Plugin includes features that will statically validate your Pig scripts, saving you time by finding errors at build time instead of when you run your Pig script.
If you run Apache Pig or Apache Spark on a Hadoop cluster through a gateway node, the Plugin includes tasks that will automate the process of launching your Pig or Spark jobs on the gateway without you having to manually download your code and dependencies there first.
If you are using Gradle and you feel that you might benefit from any of the above features, consider using the Hadoop Plugin and the Hadoop DSL.
We have added an Example Project that uses the Hadoop Plugin and DSL to build an example Azkaban workflow consisting of Apache Pig, Apache Hive and Java Map-Reduce jobs.
Apache Oozie Status
The Hadoop Plugin includes Gradle tasks for Apache Oozie, including the ability to upload versioned directories to HDFS, as well as Gradle tasks for issuing Oozie commands. If you are using Gradle as your build system and Apache Oozie as your Hadoop workflow scheduler, you might find the Hadoop Plugin useful. However, we would like to mention the fact that since we are no longer actively using Oozie at LinkedIn, it is possible that the Oozie tasks may fall into a non-working state.
Although we started on a Hadoop DSL compiler for Oozie, we did not complete it, and it is currently not in a usable form. We are not currently working on it and it is unlikely to be completed.
May 2017We have added an Example Project that uses the Hadoop Plugin and DSL
April 2016We have made a refresh of the User Guide and Hadoop DSL Language Reference Wiki pages
January 2016The Hadoop Plugin is now published on plugins.gradle.org
November 2015Gradle version bumped to 2.7 and the Gradle daemon enabled - tests run much, much faster
August 2015Initial pull requests for Oozie versioned deployments and the Oozie Hadoop DSL compiler have been merged
August 2015The Hadoop Plugin and Hadoop DSL were released on Github! See the LinkedIn Engineering Blog post for the announcement!
July 2015See our talk at the Gradle Summit
The project structure is setup as follows:
azkaban-client: Code to work with Azkaban via the Azkaban REST API
example-project: Example project that uses the Hadoop Plugin and DSL to build an example Azkaban workflow
hadoop-jobs: Code for re-usable Hadoop jobs and implementations of Hadoop DSL job types
hadoop-plugin: Code for the various plugins that comprise the Hadoop Plugin
hadoop-plugin-test: Test cases for the Hadoop Plugin
li-hadoop-plugin: LinkedIn-specific extensions to the Hadoop Plugin
li-hadoop-plugin-test: Test cases for the LinkedIn-specific extensions to the Hadoop Plugin
li-hadoop-plugin code is generally specific to LinkedIn, it is included in the
project to show you how to use subclassing to extend the core functionality of the Hadoop Plugin for your
organization (and to make sure our open-source contributions don't break the LinkedIn customizations).
Building and Running Test Cases
To build the Plugin and run the test cases, run
./gradlew build from the top-level project directory.
To see all the test tasks, run
./gradlew tasks from the top-level project directory. You can run
an individual test with
./gradlew test_testName. You can also run multiple tests by running
./gradlew test_testName1 ... test_testNameN.