[jira] [Created] (HIVE-10550) Dynamic RDD caching optimization for HoS.[Spark Branch]

["Chengxiang Li (JIRA)" <ji...@apache.org>]

Chengxiang Li created HIVE-10550:
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             Summary: Dynamic RDD caching optimization for HoS.[Spark Branch]
                 Key: HIVE-10550
                 URL: https://issues.apache.org/jira/browse/HIVE-10550
             Project: Hive
          Issue Type: Sub-task
          Components: Spark
            Reporter: Chengxiang Li


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|https://github.com/hortonworks/hive-testbench/blob/hive14/sample-queries-tpcds/query39.sql] 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.



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