GitHub user viirya opened a pull request: https://github.com/apache/spark/pull/15445
[SPARK-17817][PySpark][FOLLOWUP] PySpark RDD Repartitioning Results in Highly Skewed Partition Sizes ## What changes were proposed in this pull request? This change is a followup for #15389 which calls `_to_java_object_rdd()` to solve this issue. Due to the concern of the possible expensive cost of the call, we can choose to decrease the batch size to solve this issue too. ## How was this patch tested? Jenkins tests. You can merge this pull request into a Git repository by running: $ git pull https://github.com/viirya/spark-1 repartition-batch-size Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15445.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #15445 ---- commit 60e2abd9616016dce8e5dc2faf5c75be8e07335f Author: Liang-Chi Hsieh <vii...@gmail.com> Date: 2016-10-07T04:59:37Z Decrease the batch size for repartition. commit be6d1537e9bbd2cc2484e4d8da9d901b16725c97 Author: Liang-Chi Hsieh <vii...@gmail.com> Date: 2016-10-12T03:08:38Z Merge remote-tracking branch 'upstream/master' into repartition-batch-size ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org