[jira] [Created] (FLINK-20487) FLINK SQL GROUP BY TUMBLE AND OVER FUNCTION

["jiayue.yu (Jira)" <ji...@apache.org>]

jiayue.yu created FLINK-20487:
---------------------------------

             Summary: FLINK SQL GROUP BY TUMBLE AND OVER FUNCTION
                 Key: FLINK-20487
                 URL: https://issues.apache.org/jira/browse/FLINK-20487
             Project: Flink
          Issue Type: Bug
          Components: Table SQL / Planner
            Reporter: jiayue.yu


EXCEPTION: org.apache.flink.table.api.TableException: Group Window Aggregate: Retraction on windowed GroupBy Aggregate is not supported yet. org.apache.flink.table.api.TableException: Group Window Aggregate: Retraction on windowed GroupBy Aggregate is not supported yet. please re-check sql grammar. Note: Windowed GroupBy Aggregate should not follow anon-windowed GroupBy aggregation. at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecGroupWindowAggregateBase.translateToPlanInternal(StreamExecGroupWindowAggregateBase.scala:138) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecGroupWindowAggregateBase.translateToPlanInternal(StreamExecGroupWindowAggregateBase.scala:54) at org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan(ExecNode.scala:58) at org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan$(ExecNode.scala:56) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecGroupWindowAggregateBase.translateToPlan(StreamExecGroupWindowAggregateBase.scala:54) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:54) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalc.translateToPlanInternal(StreamExecCalc.scala:39) at org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan(ExecNode.scala:58) at org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan$(ExecNode.scala:56) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalcBase.translateToPlan(StreamExecCalcBase.scala:38) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToTransformation(StreamExecSink.scala:184) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:91) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:48) at org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan(ExecNode.scala:58) at org.apache.flink.table.planner.plan.nodes.exec.ExecNode.translateToPlan$(ExecNode.scala:56) at org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlan(StreamExecSink.scala:48) at org.apache.flink.table.planner.delegation.StreamPlanner.$anonfun$translateToPlan$1(StreamPlanner.scala:60) at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233) at scala.collection.Iterator.foreach(Iterator.scala:937) at scala.collection.Iterator.foreach$(Iterator.scala:937) at scala.collection.AbstractIterator.foreach(Iterator.scala:1425) at scala.collection.IterableLike.foreach(IterableLike.scala:70) at scala.collection.IterableLike.foreach$(IterableLike.scala:69) at scala.collection.AbstractIterable.foreach(Iterable.scala:54) at scala.collection.TraversableLike.map(TraversableLike.scala:233) at scala.collection.TraversableLike.map$(TraversableLike.scala:226) at scala.collection.AbstractTraversable.map(Traversable.scala:104) at org.apache.flink.table.planner.delegation.StreamPlanner.translateToPlan(StreamPlanner.scala:59) at org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:153) at org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:682) at org.apache.flink.table.api.internal.TableEnvironmentImpl.insertIntoInternal(TableEnvironmentImpl.java:355) at org.apache.flink.table.api.internal.TableEnvironmentImpl.insertInto(TableEnvironmentImpl.java:334)

 

CASE:

SELECT
 DATE_FORMAT(tumble_end(ROWTIME ,interval '1' hour),'yyyy-MM-dd HH') as stat_time,
 count(crypto_customer_number) first_phone_num
FROM (
 SELECT 
 ROWTIME,
 crypto_customer_number,
 row_number() over(partition by crypto_customer_number order by ROWTIME ) as rn
 FROM source_kafka_biz_shuidi_sdb_crm_call_record 
) cal 
where rn =1
group by tumble(ROWTIME,interval '1' hour);



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