Benoît Paris created FLINK-15867:
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Summary: 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
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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