Re: [Problem] Unable to do join on TumblingEventTimeWindows using SQL
Hi, Fabian, i use time-windowed join according to the docs you give but still have the problem. Here is my flink sql look like: SELECT a.account account, SUM(a.value) + SUM(b.value), UNIX_TIMESTAMP(TUMBLE_START(a.producer_timestamp, INTERVAL '3' MINUTE)) FROM (SELECT account, value, producer_timestamp FROM table1) a, (SELECT account, value, producer_timestamp FROM table2) b WHERE a.account = b.account AND a.producer_timestamp BETWEEN b.producer_timestamp - INTERVAL '3' MINUTE AND b.producer_timestamp) group by a.account, TUMBLE(a.producer_timestamp, INTERVAL '3' MINUTE) The exception is almost the same: Rowtime attributes must not be in the input rows of a regular join. As a workaround you can cast the time attributes of input tables to TIMESTAMP before. Please check the documentation for the set of currently supported SQL features. at org.apache.flink.table.api.TableEnvironment.runVolcanoPlanner(TableEnvironment.scala:450) at org.apache.flink.table.api.TableEnvironment.optimizePhysicalPlan(TableEnvironment.scala:369) at org.apache.flink.table.api.StreamTableEnvironment.optimize(StreamTableEnvironment.scala:814) at org.apache.flink.table.api.StreamTableEnvironment.translate(StreamTableEnvironment.scala:860) at org.apache.flink.table.api.StreamTableEnvironment.writeToSink(StreamTableEnvironment.scala:344) at org.apache.flink.table.api.TableEnvironment.insertInto(TableEnvironment.scala:1048) at org.apache.flink.table.api.TableEnvironment.sqlUpdate(TableEnvironment.scala:962) at org.apache.flink.table.api.TableEnvironment.sqlUpdate(TableEnvironment.scala:922) I think i use time-windowed join but flink told me its a regular join. Is there anything wrong i haven't notice? Jeremy -- Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
Re: [Problem] Unable to do join on TumblingEventTimeWindows using SQL
Hi,
the exception says: "Rowtime attributes must not be in the input rows of a
regular join. As a workaround you can cast the time attributes of input
tables to TIMESTAMP before.".
The problem is that your query first joins the two tables without a
temporal condition and then wants to do a windowed grouping.
Joins without temporal condition are not able to preserve the rowtime
attribute.
You should try to change the join into a time-windowed join [1] [2] by
adding a BETWEEN predicate on the rowtime attributes of both tables.
Best, Fabian
[1]
https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/streaming/joins.html#time-windowed-joins
[2]
https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/table/sql.html#joins
Am Mi., 23. Okt. 2019 um 09:18 Uhr schrieb Manoj Kumar :
>
> *Hi All,*
>
> *[Explanation]*
>
> Two tables say lineitem and orders:
>
> Table
> orderstbl=bsTableEnv.fromDataStream(orders,"a,b,c,d,e,f,g,h,i,orders.rowtime");
> Table
> lineitemtbl=bsTableEnv.fromDataStream(lineitem,"a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,lineitem.rowtime");
>
> bsTableEnv.registerTable("Orders",orderstbl);
> bsTableEnv.registerTable("Lineitem",lineitemtbl)
>
> *#Rgular tumble window works*
> Table sqlResult = bsTableEnv.sqlQuery("Select count(Orders.a) FROM Orders
> GROUP BY TUMBLE(orders, INTERVAL '5' SECOND)");
> Table sqlResult = bsTableEnv.sqlQuery("Select count(Lineitem.a) FROM
> Lineitem GROUP BY TUMBLE(lineitem, INTERVAL '5' SECOND)");
>
> *#Datastream TumblingEventTimeWindows joins also works fine*
>
> lineitem.join(orders).where(...).equalTo(...).window(TumblingEventTimeWindows.of(Time.seconds(5))).apply(...)
>
> *But when I try to join them over same window it gives me error, it might
> possible I am writing wrong SQL :(*
>
> Table sqlResult = bsTableEnv.sqlQuery("SELECTcount(Lineitem.a) FROM "
> + "Orders,Lineitem where Lineitem.a=Orders.a "
> + "GROUP BY TUMBLE(orders, INTERVAL '5' SECOND)");
>
> Exception in thread "main" org.apache.flink.table.api.TableException:
> Cannot generate a valid execution plan for the given query:
>
> FlinkLogicalSink(name=[sink], fields=[b])
> +- FlinkLogicalWindowAggregate(group=[{}], EXPR$0=[COUNT($1)],
> window=[TumblingGroupWindow], properties=[])
>+- FlinkLogicalCalc(select=[orders, a0])
> +- FlinkLogicalJoin(condition=[=($2, $0)], joinType=[inner])
> :- FlinkLogicalCalc(select=[a, orders])
> : +-
> FlinkLogicalDataStreamTableScan(table=[[Unregistered_DataStream_3]])
> +- FlinkLogicalCalc(select=[a])
> +-
> FlinkLogicalDataStreamTableScan(table=[[Unregistered_DataStream_6]])
>
> Rowtime attributes must not be in the input rows of a regular join. As a
> workaround you can cast the time attributes of input tables to TIMESTAMP
> before.
> Please check the documentation for the set of currently supported SQL
> features.
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:78)
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram$$anonfun$optimize$1.apply(FlinkChainedProgram.scala:62)
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram$$anonfun$optimize$1.apply(FlinkChainedProgram.scala:58)
> at
> scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
> at
> scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
> at scala.collection.Iterator$class.foreach(Iterator.scala:891)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
> at
> scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157)
> at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:104)
> at
> org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:57)
> at
> org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.optimizeTree(StreamCommonSubGraphBasedOptimizer.scala:166)
> at
> org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.doOptimize(StreamCommonSubGraphBasedOptimizer.scala:88)
> at
> org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:78)
> at
> org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:212)
> at
> org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:147)
> at
> org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:439)
> at
> org.apache.flink.table.api.internal.TableEnvironmentImpl.insertInto(TableEnvironmentImpl.java:327)
> at
> org.apache.flink.table.api.internal.TableImpl.insertInto(TableImpl.java:411)
> at bzflink.StreamingTable.main(StreamingTable.java:65)
> Caused by:
[Problem] Unable to do join on TumblingEventTimeWindows using SQL
*Hi All,*
*[Explanation]*
Two tables say lineitem and orders:
Table
orderstbl=bsTableEnv.fromDataStream(orders,"a,b,c,d,e,f,g,h,i,orders.rowtime");
Table
lineitemtbl=bsTableEnv.fromDataStream(lineitem,"a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,lineitem.rowtime");
bsTableEnv.registerTable("Orders",orderstbl);
bsTableEnv.registerTable("Lineitem",lineitemtbl)
*#Rgular tumble window works*
Table sqlResult = bsTableEnv.sqlQuery("Select count(Orders.a) FROM Orders
GROUP BY TUMBLE(orders, INTERVAL '5' SECOND)");
Table sqlResult = bsTableEnv.sqlQuery("Select count(Lineitem.a) FROM
Lineitem GROUP BY TUMBLE(lineitem, INTERVAL '5' SECOND)");
*#Datastream TumblingEventTimeWindows joins also works fine*
lineitem.join(orders).where(...).equalTo(...).window(TumblingEventTimeWindows.of(Time.seconds(5))).apply(...)
*But when I try to join them over same window it gives me error, it might
possible I am writing wrong SQL :(*
Table sqlResult = bsTableEnv.sqlQuery("SELECTcount(Lineitem.a) FROM "
+ "Orders,Lineitem where Lineitem.a=Orders.a "
+ "GROUP BY TUMBLE(orders, INTERVAL '5' SECOND)");
Exception in thread "main" org.apache.flink.table.api.TableException:
Cannot generate a valid execution plan for the given query:
FlinkLogicalSink(name=[sink], fields=[b])
+- FlinkLogicalWindowAggregate(group=[{}], EXPR$0=[COUNT($1)],
window=[TumblingGroupWindow], properties=[])
+- FlinkLogicalCalc(select=[orders, a0])
+- FlinkLogicalJoin(condition=[=($2, $0)], joinType=[inner])
:- FlinkLogicalCalc(select=[a, orders])
: +-
FlinkLogicalDataStreamTableScan(table=[[Unregistered_DataStream_3]])
+- FlinkLogicalCalc(select=[a])
+-
FlinkLogicalDataStreamTableScan(table=[[Unregistered_DataStream_6]])
Rowtime attributes must not be in the input rows of a regular join. As a
workaround you can cast the time attributes of input tables to TIMESTAMP
before.
Please check the documentation for the set of currently supported SQL
features.
at
org.apache.flink.table.planner.plan.optimize.program.FlinkVolcanoProgram.optimize(FlinkVolcanoProgram.scala:78)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram$$anonfun$optimize$1.apply(FlinkChainedProgram.scala:62)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram$$anonfun$optimize$1.apply(FlinkChainedProgram.scala:58)
at
scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
at
scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at
scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157)
at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:104)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:57)
at
org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.optimizeTree(StreamCommonSubGraphBasedOptimizer.scala:166)
at
org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.doOptimize(StreamCommonSubGraphBasedOptimizer.scala:88)
at
org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:78)
at
org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:212)
at
org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:147)
at
org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:439)
at
org.apache.flink.table.api.internal.TableEnvironmentImpl.insertInto(TableEnvironmentImpl.java:327)
at
org.apache.flink.table.api.internal.TableImpl.insertInto(TableImpl.java:411)
at bzflink.StreamingTable.main(StreamingTable.java:65)
Caused by: org.apache.flink.table.api.TableException: Rowtime attributes
must not be in the input rows of a regular join. As a workaround you can
cast the time attributes of input tables to TIMESTAMP before.
at
org.apache.flink.table.planner.plan.rules.physical.stream.StreamExecJoinRule.matches(StreamExecJoinRule.scala:88)
at
org.apache.calcite.plan.volcano.VolcanoRuleCall.matchRecurse(VolcanoRuleCall.java:263)
at
org.apache.calcite.plan.volcano.VolcanoRuleCall.matchRecurse(VolcanoRuleCall.java:367)
at
org.apache.calcite.plan.volcano.VolcanoRuleCall.matchRecurse(VolcanoRuleCall.java:367)
at
org.apache.calcite.plan.volcano.VolcanoRuleCall.match(VolcanoRuleCall.java:247)
at
org.apache.calcite.plan.volcano.VolcanoPlanner.fireRules(VolcanoPlanner.java:1522)
at
org.apache.calcite.plan.volcano.VolcanoPlanner.registerImpl(VolcanoPlanner.java:1795)
at
org.apache.calcite.plan.volcano.VolcanoPlanner.register(VolcanoPlanner.java:846)
at
