Github user zhzhan commented on the issue:
https://github.com/apache/spark/pull/15218
@mridulm You are right. This patch is mainly for the job that has multiple
stages, which is very common in production pipeline. As you mentioned, if there
is shuffle involved, getLocationsWithLargestOutputs in MapOutputTracker
typically return None for the ShuffledRowRDD and ShuffledRDD because of the
threshold REDUCER_PREF_LOCS_FRACTION (20%).
The ShuffledRowRDD/ShuffleRDD can be easily more than 10 partitions (even
hundreds) in real production pipeline, thus the patch does help a lot in CPU
reservation time.
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