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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
, for example:SPARK-123: Add some feature to Spark
[STREAMING] SPARK-123: Add some feature to Spark streaming
[MLLIB] [WIP] SPARK-123: Some potentially useful feature for MLLib
.
- Follow the Spark Code Style Guide.
- Make sure that your code passes the unit tests. You can run the tests with
sbt/sbt assembly
and thensbt/sbt test
in the root directory of Spark. It's important to runassembly
first 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
docs
folder) if you add a new feature or configuration parameter.
If you’d like to report a bug but don’t have time to fix it, you can still post it to our issue tracker, or email the mailing list.
Tip | ||
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SPARK-123: Add some feature to Spark [STREAMING] SPARK-123: Add some feature to Spark streaming [MLLIB] [WIP] SPARK-123: Some potentially useful feature for MLLib |
Starter Tasks
If you are new to Spark and want to contribute, you can browse through the list of starter tasks on our JIRA. These tasks are typically small and simple, and are excellent problems to get you ramped up.
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