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Small patches are almost never rejected, so it's a good strategy to start with small patches for new contributors. Keep in mind that Spark committers act as volunteers , so anything you can do to make review time more efficient is useful- patches with major correctness issues might be rejected rather than revived. If this happens consider finding smaller patches or simpler features to contribute, then building up your confidence and abilities over time.

Contributing New Algorithms to MLLib

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