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https://issues.apache.org/jira/browse/FLINK-8897?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Timo Walther updated FLINK-8897:
--------------------------------
Priority: Major (was: Blocker)
> Rowtime materialization causes "mismatched type" AssertionError
> ---------------------------------------------------------------
>
> Key: FLINK-8897
> URL: https://issues.apache.org/jira/browse/FLINK-8897
> Project: Flink
> Issue Type: Bug
> Components: Table API & SQL
> Reporter: Xingcan Cui
> Assignee: Timo Walther
> Priority: Major
> Fix For: 1.5.0
>
>
> As raised in [this
> thread|https://lists.apache.org/thread.html/e2ea38aa7ae224d7481145334955d84243690e9aad10d58310bdb8e7@%3Cuser.flink.apache.org%3E],
> the query created by the following code will throw a calcite "mismatch type"
> ({{Timestamp(3)}} and {{TimeIndicator}}) exception.
> {code:java}
> String sql1 = "select id, eventTs as t1, count(*) over (partition by id order
> by eventTs rows between 100 preceding and current row) as cnt1 from myTable1";
> String sql2 = "select distinct id as r_id, eventTs as t2, count(*) over
> (partition by id order by eventTs rows between 50 preceding and current row)
> as cnt2 from myTable2";
> Table left = tableEnv.sqlQuery(sql1);
> Table right = tableEnv.sqlQuery(sql2);
> left.join(right).where("id === r_id && t1 === t2").select("id,
> t1").writeToSink(...)
> {code}
> The logical plan is as follows.
> {code}
> LogicalProject(id=[$0], t1=[$1])
> LogicalFilter(condition=[AND(=($0, $3), =($1, $4))])
> LogicalJoin(condition=[true], joinType=[inner])
> LogicalAggregate(group=[{0, 1, 2}])
> LogicalWindow(window#0=[window(partition {0} order by [1] rows
> between $2 PRECEDING and CURRENT ROW aggs [COUNT()])])
> LogicalProject(id=[$0], eventTs=[$3])
> LogicalTableScan(table=[[_DataStreamTable_0]])
> LogicalAggregate(group=[{0, 1, 2}])
> LogicalWindow(window#0=[window(partition {0} order by [1] rows
> between $2 PRECEDING and CURRENT ROW aggs [COUNT()])])
> LogicalProject(id=[$0], eventTs=[$3])
> LogicalTableScan(table=[[_DataStreamTable_0]])
> {code}
> That is because the the rowtime field after an aggregation will be
> materialized while the {{RexInputRef}} type for the filter's operands ({{t1
> === t2}}) is still {{TimeIndicator}}. We should make them unified.
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