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https://issues.apache.org/jira/browse/FLINK-34529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17830900#comment-17830900
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yisha zhou commented on FLINK-34529:
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Hi [~libenchao] [~lincoln.86xy] , as your suggestions, I tried to introduce
`FlinkProjectWindowTransposeRule` which is based on
CoreRules.PROJECT_WINDOW_TRANSPOSE but keeps upsert keys of input not being
pruned. Then the regression mentioned before is gone. The PR is ready, please
feel free to review my code when you have some time.
> Projection cannot be pushed down through rank operator.
> -------------------------------------------------------
>
> Key: FLINK-34529
> URL: https://issues.apache.org/jira/browse/FLINK-34529
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / Planner
> Affects Versions: 1.19.0
> Reporter: yisha zhou
> Assignee: yisha zhou
> Priority: Major
> Labels: pull-request-available
>
> When there is a rank/deduplicate operator, the projection based on output of
> this operator cannot be pushed down to the input of it.
> The following code can help reproducing the issue:
> {code:java}
> val util = streamTestUtil()
> util.addTableSource[(String, Int, String)]("T1", 'a, 'b, 'c)
> util.addTableSource[(String, Int, String)]("T2", 'd, 'e, 'f)
> val sql =
> """
> |SELECT a FROM (
> | SELECT a, f,
> | ROW_NUMBER() OVER (PARTITION BY f ORDER BY c DESC) as rank_num
> | FROM T1, T2
> | WHERE T1.a = T2.d
> |)
> |WHERE rank_num = 1
> """.stripMargin
> util.verifyPlan(sql){code}
> The plan is expected to be:
> {code:java}
> Calc(select=[a])
> +- Rank(strategy=[AppendFastStrategy], rankType=[ROW_NUMBER],
> rankRange=[rankStart=1, rankEnd=1], partitionBy=[f], orderBy=[c DESC],
> select=[a, c, f])
> +- Exchange(distribution=[hash[f]])
> +- Calc(select=[a, c, f])
> +- Join(joinType=[InnerJoin], where=[=(a, d)], select=[a, c, d, f],
> leftInputSpec=[NoUniqueKey], rightInputSpec=[NoUniqueKey])
> :- Exchange(distribution=[hash[a]])
> : +- Calc(select=[a, c])
> : +- LegacyTableSourceScan(table=[[default_catalog,
> default_database, T1, source: [TestTableSource(a, b, c)]]], fields=[a, b, c])
> +- Exchange(distribution=[hash[d]])
> +- Calc(select=[d, f])
> +- LegacyTableSourceScan(table=[[default_catalog,
> default_database, T2, source: [TestTableSource(d, e, f)]]], fields=[d, e, f])
> {code}
> Notice that the 'select' of Join operator is [a, c, d, f]. However the actual
> plan is:
> {code:java}
> Calc(select=[a])
> +- Rank(strategy=[AppendFastStrategy], rankType=[ROW_NUMBER],
> rankRange=[rankStart=1, rankEnd=1], partitionBy=[f], orderBy=[c DESC],
> select=[a, c, f])
> +- Exchange(distribution=[hash[f]])
> +- Calc(select=[a, c, f])
> +- Join(joinType=[InnerJoin], where=[=(a, d)], select=[a, b, c, d,
> e, f], leftInputSpec=[NoUniqueKey], rightInputSpec=[NoUniqueKey])
> :- Exchange(distribution=[hash[a]])
> : +- LegacyTableSourceScan(table=[[default_catalog,
> default_database, T1, source: [TestTableSource(a, b, c)]]], fields=[a, b, c])
> +- Exchange(distribution=[hash[d]])
> +- LegacyTableSourceScan(table=[[default_catalog,
> default_database, T2, source: [TestTableSource(d, e, f)]]], fields=[d, e, f])
> {code}
> the 'select' of Join operator is [a, b, c, d, e, f], which means the
> projection in the final Calc is not passed through the Rank.
> And I think an easy way to fix this issue is to add
> org.apache.calcite.rel.rules.ProjectWindowTransposeRule into
> FlinkStreamRuleSets.LOGICAL_OPT_RULES.
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