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Posted to issues@flink.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/11/01 13:00:00 UTC

[jira] [Updated] (FLINK-8897) Rowtime materialization causes "mismatched type" AssertionError

     [ https://issues.apache.org/jira/browse/FLINK-8897?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

ASF GitHub Bot updated FLINK-8897:
----------------------------------
    Labels: pull-request-available  (was: )

> 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 &amp; SQL
>            Reporter: Xingcan Cui
>            Assignee: Timo Walther
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 1.5.6
>
>
> 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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