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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