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https://issues.apache.org/jira/browse/FLINK-15867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17231314#comment-17231314
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Jannik Schmeier edited comment on FLINK-15867 at 11/13/20, 9:30 AM:
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Since we need this functionality for our use cases, I would like to provide a
pull request for this it. Can you please assign the issue to me?
was (Author: shmyer):
Since we need this functionality for our use cases, I would like to provide a
pull request for this it. Can you assign the issue to me?
> LAST_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
> Priority: Major
> 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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