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  1. IMPALA
  2. IMPALA-4268

Rework coordinator buffering to buffer more data

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      PlanRootSink executes the producer thread (the coordinator fragment execution thread) in a separate thread to the consumer (i.e. the thread handling the fetch RPC), which calls GetNext() to retrieve the rows. The implementation was simplified by handing off a single batch at a time from the producers to consumer.

      This decision causes some problems:

      • Many context switches for the sender. Adding buffering would allow the sender to append to the buffer and continue progress without a context switch.
      • Query execution can't release resources until the client has fetched the final batch, because the coordinator fragment thread is still running and potentially producing backpressure all the way down the plan tree.
      • The consumer can't fulfil fetch requests greater than Impala's internal BATCH_SIZE, because it is only given one batch at a time.

      The tricky part is managing the mismatch between the size of the row batches processed in Send() and the size of the fetch result asked for by the client without impacting performance too badly. The sender materializes output rows in a QueryResultSet that is owned by the coordinator. That is not, currently, a splittable object - instead it contains the actual RPC response struct that will hit the wire when the RPC completes. As asynchronous sender does not know the batch size, because it can in theory change on every fetch call (although most reasonable clients will not randomly change the fetch size).

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        1. rows-produced-histogram.png
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          Tim Armstrong

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              Unassigned Unassigned
              henryr Henry Robinson
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