THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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If you'd like to report a bug in Spark or ask for a new feature, open an issue on the Apache Spark JIRA. For general usage help, you should email the user mailing list.
Contributing Code
We prefer to receive contributions in the form of GitHub pull requests. Please send pull requests against the github.com/apache/spark repository. If you've previously forked Spark from its old location, you will need to fork apache/spark instead.
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- Break your work into small, single-purpose patches if possible. It’s much harder to merge in a large change with a lot of disjoint features.
- Create a JIRA for your patch on the Spark Project JIRA.
Submit the patch as a GitHub pull request. For a tutorial, see the GitHub guides on forking a repo and sending a pull request. Name your pull request with the JIRA name and include the Spark module or WIP if relevant.
- Follow the Spark Code Style Guide. Before sending in your pull request, run
sbt/sbt scalastyleto validate the style. - Make sure that your code passes the unit tests. You can run the tests with
sbt/sbt assemblyand thensbt/sbt testin the root directory of Spark. It's important to runassemblyfirst as some of the tests depend on compiled JARs. - Add new unit tests for your code. We use ScalaTest for testing. Just add a new Suite in
core/src/test, or methods to an existing Suite. - Update the documentation (in the
docsfolder) if you add a new feature or configuration parameter.
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- To have us add a link to an external tutorial you wrote, simply email the developer mailing list.
- To modify the built-in documentation, edit the MarkDown source files in Spark's
docsdirectory, and send a patch against the incubator-spark Spark GitHub repository. The README file indocssays how to build the documentation locally to test your changes.
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To keep up to date with the latest discussions, join the developer mailing list.
IDE Setup
While many of the Spark developers use SBT or Maven on the command line, the most common IDE we use is IntelliJ IDEA. You can get the community edition for free (Apache committers can get free IntelliJ Ultimate Edition licenses) and install the JetBrains Scala plugin from Preferences > Plugins. To generate an IDEA workspace for Spark, run
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