[jira] [Created] (SPARK-9872) Allow passing of 'numPartitions' to DataFrame joins

["Al M (JIRA)" <ji...@apache.org>]

Al M created SPARK-9872:
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             Summary: Allow passing of 'numPartitions' to DataFrame joins
                 Key: SPARK-9872
                 URL: https://issues.apache.org/jira/browse/SPARK-9872
             Project: Spark
          Issue Type: Improvement
    Affects Versions: 1.4.1
            Reporter: Al M
            Priority: Minor


When I join two normal RDDs, I can set the number of shuffle partitions in the 'numPartitions' argument.  When I join two DataFrames I do not have this option.

My spark job loads in 2 large files and 2 small files.  When I perform a join, this will use the "spark.sql.shuffle.partitions" to determine the number of partitions.  This means that the join with my small files will use exactliy the same number of partitions as the join with my large files.

I can either use a low number of partitions and run out of memory on my large join, or use a high number of partitions and my small join will take far too long.

If we were able to specify the number of shuffle partitions in a DataFrame join like in an RDD join, this would not be an issue.

My long term ideal solution would be dynamic partition determination as described in SPARK-4630.  However I appreciate that it is not particularly easy to do.



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