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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