Uploaded image for project: 'Spark'
  1. Spark
  2. SPARK-23249

Improve partition bin-filling algorithm to have less skew and fewer partitions



    • Type: Improvement
    • Status: Resolved
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 2.2.1
    • Fix Version/s: 2.3.0
    • Component/s: SQL
    • Labels:


      Change DataSourceScanExec so that when grouping blocks together into partitions, also checks the end of the sorted list of splits to more efficiently fill out partitions.



      The current bin-packing method of next-fit descending for blocks into partitions is sub-optimal in a lot of cases and will result in extra partitions, un-even distribution of block-counts across partitions, and un-even distribution of partition sizes.

      As an example, 128 files ranging from 1MB, 2MB,...127MB,128MB. will result in 82 partitions with the current algorithm, but only 64 using this algorithm. Also in this example, the max # of blocks per partition in NFD is 13, while in this algorithm is is 2.

      More generally, running a simulation of 1000 runs using 128MB blocksize, between 1-1000 normally distributed file sizes between 1-500Mb, you can see an improvement of approx 5% reduction of partition counts, and a large reduction in standard deviation of blocks per partition.

      This algorithm also runs in O time as NFD does, and in every case is strictly better results than NFD.

      Overall, the more even distribution of blocks across partitions and therefore reduced partition counts should result in a small but significant performance increase across the board




            • Assignee:
              gtakahashi@palantir.com Glen Takahashi
              gtakahashi@palantir.com Glen Takahashi
            • Votes:
              0 Vote for this issue
              7 Start watching this issue


              • Created: