StanZhai created SPARK-22084:
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Summary: Performance regression in aggregation strategy
Key: SPARK-22084
URL: https://issues.apache.org/jira/browse/SPARK-22084
Project: Spark
Issue Type: Improvement
Components: SQL
Affects Versions: 2.2.0, 2.1.1, 2.1.0, 2.0.2, 2.0.1, 2.0.0
Reporter: StanZhai
{code:sql}
SELECT a, SUM(b) AS b0, SUM(b) AS b1
FROM VALUES(1, 1), (2, 2) AS (a, b)
GROUP BY a
{code}
Two exactly the same SUM(b) expressions in the SQL, and the following is the
physical plan in Spark 2.x.
== Physical Plan ==
*HashAggregate(keys=[a#11], functions=[sum(cast(b#12 as bigint)), sum(cast(b#12
as bigint))])
+- Exchange hashpartitioning(a#11, 200)
+- *HashAggregate(keys=[a#11], functions=[partial_sum(cast(b#12 as bigint)),
partial_sum(cast(b#12 as bigint))])
+- LocalTableScan [a#11, b#12]
functions in Aggregate should be: functions=[partial_sum(cast(b#12 as bigint))]
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