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https://issues.apache.org/jira/browse/FLINK-15867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17323104#comment-17323104
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Flink Jira Bot commented on FLINK-15867:
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This issue is assigned but has not received an update in 7 days so it has been
labeled "stale-assigned". If you are still working on the issue, please give an
update and remove the label. If you are no longer working on the issue, please
unassign so someone else may work on it. In 7 days the issue will be
automatically unassigned.
> LAST_VALUE and FIRST_VALUE aggregate function does not support time-related
> types
> ---------------------------------------------------------------------------------
>
> Key: FLINK-15867
> URL: https://issues.apache.org/jira/browse/FLINK-15867
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / Planner
> Affects Versions: 1.9.2, 1.10.0
> Reporter: Benoît Paris
> Assignee: Jannik Schmeier
> Priority: Major
> Labels: pull-request-available, stale-assigned
> Attachments: flink-test-lastvalue-timestamp.zip
>
>
> The following fails:
> {code:java}
> LAST_VALUE(TIMESTAMP '2020-02-03 16:17:20')
> LAST_VALUE(DATE '2020-02-03')
> LAST_VALUE(TIME '16:17:20')
> LAST_VALUE(NOW()){code}
> But this works:
>
> {code:java}
> LAST_VALUE(UNIX_TIMESTAMP())
> {code}
> Leading me to say it might be more a type/format issue, rather than an actual
> time processing issue.
> Attached is java + pom + full stacktrace, for reproduction. Stacktrace part
> is below.
>
> The ByteLastValueAggFunction, etc types seem trivial to implement, but the in
> the createLastValueAggFunction only basic types seem to be dealt with. Is
> there a reason more complicated LogicalTypeRoots might not be implemented ?
> (old vs new types?)
>
>
> Caused by: org.apache.flink.table.api.TableException: LAST_VALUE aggregate
> function does not support type: ''TIMESTAMP_WITHOUT_TIME_ZONE''.Caused by:
> org.apache.flink.table.api.TableException: LAST_VALUE aggregate function does
> not support type: ''TIMESTAMP_WITHOUT_TIME_ZONE''.Please re-check the data
> type. at
> org.apache.flink.table.planner.plan.utils.AggFunctionFactory.createLastValueAggFunction(AggFunctionFactory.scala:617)
> at
> org.apache.flink.table.planner.plan.utils.AggFunctionFactory.createAggFunction(AggFunctionFactory.scala:113)
> at
> org.apache.flink.table.planner.plan.utils.AggregateUtil$$anonfun$9.apply(AggregateUtil.scala:285)
> at
> org.apache.flink.table.planner.plan.utils.AggregateUtil$$anonfun$9.apply(AggregateUtil.scala:279)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:234) at
> scala.collection.AbstractTraversable.map(Traversable.scala:104) at
> org.apache.flink.table.planner.plan.utils.AggregateUtil$.transformToAggregateInfoList(AggregateUtil.scala:279)
> at
> org.apache.flink.table.planner.plan.utils.AggregateUtil$.transformToStreamAggregateInfoList(AggregateUtil.scala:228)
> at
> org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecGroupAggregate.<init>(StreamExecGroupAggregate.scala:72)
> at
> org.apache.flink.table.planner.plan.rules.physical.stream.StreamExecGroupAggregateRule.convert(StreamExecGroupAggregateRule.scala:68)
> at
> org.apache.calcite.rel.convert.ConverterRule.onMatch(ConverterRule.java:139)
> at
> org.apache.calcite.plan.volcano.VolcanoRuleCall.onMatch(VolcanoRuleCall.java:208)
> at
> org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:631)
> at org.apache.calcite.tools.Programs$RuleSetProgram.run(Programs.java:328)
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:64)
> ----
>
>
>
>
>
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