[jira] [Created] (FLINK-12263) Remove SINGLE_VALUE aggregate function from physical plan

["Jark Wu (JIRA)" <ji...@apache.org>]

Jark Wu created FLINK-12263:
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             Summary: Remove SINGLE_VALUE aggregate function from physical plan
                 Key: FLINK-12263
                 URL: https://issues.apache.org/jira/browse/FLINK-12263
             Project: Flink
          Issue Type: New Feature
          Components: Table SQL / Planner
            Reporter: Jark Wu


 SINGLE_VALUE is an aggregate function which only accepts one row, and throws exception when received more than one row.

 

For example: 
{code:sql}
SELECT a2, SUM(a1) FROM A GROUP BY a2 HAVING SUM(a1) > (SELECT SUM(a1) * 0.1 FROM A)
{code}
will get a physical plan contains SINGLE_VALUE:
{code:sql}
+- NestedLoopJoin(joinType=[InnerJoin], where=[>(EXPR$1, $f0)], select=[a2, EXPR$1, $f0], build=[right], singleRowJoin=[true])
   :- HashAggregate(isMerge=[true], groupBy=[a2], select=[a2, Final_SUM(sum$0) AS EXPR$1])
   :  +- Exchange(distribution=[hash[a2]])
   :     +- LocalHashAggregate(groupBy=[a2], select=[a2, Partial_SUM(a1) AS sum$0])
   :        +- TableSourceScan(table=[[A, source: [TestTableSource(a1, a2)]]], fields=[a1, a2])
   +- Exchange(distribution=[broadcast])
      +- HashAggregate(isMerge=[true], select=[Final_SINGLE_VALUE(value$0, count$1) AS $f0])
         +- Exchange(distribution=[single])
            +- LocalHashAggregate(select=[Partial_SINGLE_VALUE(EXPR$0) AS (value$0, count$1)])
               +- Calc(select=[*($f0, 0.1) AS EXPR$0])
                  +- HashAggregate(isMerge=[true], select=[Final_SUM(sum$0) AS $f0])
                     +- Exchange(distribution=[single])
                        +- LocalHashAggregate(select=[Partial_SUM(a1) AS sum$0])
                           +- Calc(select=[a1])
                              +- TableSourceScan(table=[[A, source: [TestTableSource(a1, a2)]]], fields=[a1, a2])
{code}
But SINGLE_VALUE is a bit wired in physical plan because the logical plan can make sure there is only one input row. Moreover it it also introduces additional overhead.



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