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  1. Hive
  2. HIVE-7292 Hive on Spark
  3. HIVE-10550

Dynamic RDD caching optimization for HoS.[Spark Branch]


    • Type: Sub-task
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: None
    • Fix Version/s: 1.3.0, 2.0.0
    • Component/s: Spark
    • Labels:


      A Hive query may try to scan the same table multi times, like self-join, self-union, or even share the same subquery, TPC-DS Q39 is an example. As you may know that, Spark support cache RDD data, which mean Spark would put the calculated RDD data in memory and get the data from memory directly for next time, this avoid the calculation cost of this RDD(and all the cost of its dependencies) at the cost of more memory usage. Through analyze the query context, we should be able to understand which part of query could be shared, so that we can reuse the cached RDD in the generated Spark job.


        1. HIVE-10550.1.patch
          52 kB
          Chengxiang Li
        2. HIVE-10550.1-spark.patch
          52 kB
          Xuefu Zhang
        3. HIVE-10550.2-spark.patch
          61 kB
          Chengxiang Li
        4. HIVE-10550.3-spark.patch
          42 kB
          Chengxiang Li
        5. HIVE-10550.4-spark.patch
          18 kB
          Chengxiang Li
        6. HIVE-10550.5-spark.patch
          18 kB
          Chengxiang Li
        7. HIVE-10550.6-spark.patch
          10 kB
          Chengxiang Li

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              • Assignee:
                chengxiang li Chengxiang Li
                chengxiang li Chengxiang Li
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