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Instead of materializing empty rows when computing count star, we use the data stored in the Parquet RowGroup.num_rows field. The Parquet scanner tuple is modified to have one slot into which we will write the num rows statistic. The aggregate function is changed from count to a special sum function that gets initialized to 0. We also add a rewrite rule so that count(<literal>) is rewritten to count(*) in order to make sure that this optimization is applied in all cases. Testing: - Added functional and planner tests Change-Id: I536b85c014821296aed68a0c68faadae96005e62 Reviewed-on: http://gerrit.cloudera.org:8080/6812 Reviewed-by: Taras Bobrovytsky <tbobrovytsky@cloudera.com> Tested-by: Impala Public Jenkins
This directory contains Impala test workloads. The directory layout for the workloads should follow: workloads/ <data set name>/<data set name>_dimensions.csv <- The test dimension file <data set name>/<data set name>_core.csv <- A test vector file <data set name>/<data set name>_pairwise.csv <data set name>/<data set name>_exhaustive.csv <data set name>/queries/<query test>.test <- The queries for this workload