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
Date: 2016-10-07T04:59:37Z
Decrease the batch size for repartition.
commit be6d1537e9bbd2cc2484e4d8da9d901b16725c97
Author: Liang-Chi Hsieh
Date: 2016-10-12T03:08:38Z
Merge remote-tracking branch 'upstream/master' into repartition-batch-size
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