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[SPARK-9821] [PYSPARK] pyspark-reduceByKey-should-take-a-custom-partitioner
from the issue: In Scala, I can supply a custom partitioner to reduceByKey (and other aggregation/repartitioning methods like aggregateByKey and combinedByKey), but as far as I can tell from the Pyspark API, there's no way to do the same in Python. Here's an example of my code in Scala: weblogs.map(s => (getFileType(s), 1)).reduceByKey(new FileTypePartitioner(),_+_) But I can't figure out how to do the same in Python. The closest I can get is to call repartition before reduceByKey like so: weblogs.map(lambda s: (getFileType(s), 1)).partitionBy(3,hash_filetype).reduceByKey(lambda v1,v2: v1+v2).collect() But that defeats the purpose, because I'm shuffling twice instead of once, so my performance is worse instead of better. Author: Holden Karau <holden@pigscanfly.ca> Closes #8569 from holdenk/SPARK-9821-pyspark-reduceByKey-should-take-a-custom-partitioner.
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