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Posted to issues@drill.apache.org by "Khurram Faraaz (JIRA)" <ji...@apache.org> on 2015/04/04 06:54:33 UTC
[jira] [Commented] (DRILL-2639) Planner bug -
RelOptPlanner.CannotPlanException
[ https://issues.apache.org/jira/browse/DRILL-2639?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14395541#comment-14395541 ]
Khurram Faraaz commented on DRILL-2639:
---------------------------------------
You may want to look at the fix for DRILL-600, which was used to report a similar Exception for a Union All query, it is now in Resolved state.
> Planner bug - RelOptPlanner.CannotPlanException
> -----------------------------------------------
>
> Key: DRILL-2639
> URL: https://issues.apache.org/jira/browse/DRILL-2639
> Project: Apache Drill
> Issue Type: Bug
> Components: Query Planning & Optimization
> Affects Versions: 0.9.0
> Environment: | 9d92b8e319f2d46e8659d903d355450e15946533 | DRILL-2580: Exit early from HashJoinBatch if build side is empty | 26.03.2015 @ 16:13:53 EDT | Unknown | 26.03.2015 @ 16:53:21 EDT |
> Reporter: Khurram Faraaz
> Assignee: Sean Hsuan-Yi Chu
> Priority: Critical
> Fix For: 0.9.0
>
>
> Reporting this as a separate JIRA as this issue related to a bug in the planner. Performing aggregate on the output returned by Union All results in CannotPlanException. Note that the two inputs to Union All are casted to integer and hence the inputs from both legs are of the same datatype.
> {code}
> 0: jdbc:drill:> select count(c1) from (select cast(columns[0] as int) c1 from `testWindow.csv`) union all (select cast(columns[0] as int) c2 from `testWindow.csv`);
> Query failed: RelOptPlanner.CannotPlanException: Node [rel#59393:Subset#4.LOGICAL.ANY([]).[]] could not be implemented; planner state:
> Root: rel#59393:Subset#4.LOGICAL.ANY([]).[]
> Original rel:
> AbstractConverter(subset=[rel#59393:Subset#4.LOGICAL.ANY([]).[]], convention=[LOGICAL], DrillDistributionTraitDef=[ANY([])], sort=[[]]): rowcount = 1.7976931348623157E308, cumulative cost = {inf}, id = 59394
> UnionRel(subset=[rel#59392:Subset#4.NONE.ANY([]).[]], all=[true]): rowcount = 1.7976931348623157E308, cumulative cost = {1.7976931348623157E308 rows, 1.7976931348623157E308 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 59391
> AggregateRel(subset=[rel#59388:Subset#2.NONE.ANY([]).[]], group=[{}], EXPR$0=[COUNT($0)]): rowcount = 1.7976931348623158E307, cumulative cost = {1.7976931348623158E307 rows, 0.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 59387
> ProjectRel(subset=[rel#59386:Subset#1.NONE.ANY([]).[]], c1=[CAST(ITEM($1, 0)):INTEGER]): rowcount = 100.0, cumulative cost = {100.0 rows, 100.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 59385
> EnumerableTableAccessRel(subset=[rel#59384:Subset#0.ENUMERABLE.ANY([]).[]], table=[[dfs, tmp, testWindow.csv]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 59368
> ProjectRel(subset=[rel#59390:Subset#3.NONE.ANY([]).[]], c2=[CAST(ITEM($1, 0)):INTEGER]): rowcount = 100.0, cumulative cost = {100.0 rows, 100.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 59389
> EnumerableTableAccessRel(subset=[rel#59384:Subset#0.ENUMERABLE.ANY([]).[]], table=[[dfs, tmp, testWindow.csv]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 59368
> Sets:
> Set#0, type: (DrillRecordRow[*, columns])
> rel#59384:Subset#0.ENUMERABLE.ANY([]).[], best=rel#59368, importance=0.6561
> rel#59368:EnumerableTableAccessRel.ENUMERABLE.ANY([]).[](table=[dfs, tmp, testWindow.csv]), rowcount=100.0, cumulative cost={100.0 rows, 101.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> rel#59408:AbstractConverter.ENUMERABLE.ANY([]).[](child=rel#59407:Subset#0.LOGICAL.ANY([]).[],convention=ENUMERABLE,DrillDistributionTraitDef=ANY([]),sort=[]), rowcount=1.0, cumulative cost={inf}
> rel#59407:Subset#0.LOGICAL.ANY([]).[], best=rel#59415, importance=0.5904900000000001
> rel#59409:AbstractConverter.LOGICAL.ANY([]).[](child=rel#59384:Subset#0.ENUMERABLE.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]), rowcount=100.0, cumulative cost={inf}
> rel#59415:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, tmp, testWindow.csv],groupscan=EasyGroupScan [selectionRoot=/tmp/testWindow.csv, numFiles=1, columns=[`*`], files=[maprfs:/tmp/testWindow.csv]]), rowcount=1.0, cumulative cost={1.0 rows, 10000.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> Set#1, type: RecordType(INTEGER c1)
> rel#59386:Subset#1.NONE.ANY([]).[], best=null, importance=0.7290000000000001
> rel#59385:ProjectRel.NONE.ANY([]).[](child=rel#59384:Subset#0.ENUMERABLE.ANY([]).[],c1=CAST(ITEM($1, 0)):INTEGER), rowcount=100.0, cumulative cost={inf}
> rel#59404:Subset#1.LOGICAL.ANY([]).[], best=rel#59413, importance=0.36450000000000005
> rel#59405:AbstractConverter.LOGICAL.ANY([]).[](child=rel#59386:Subset#1.NONE.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]), rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#59413:DrillProjectRel.LOGICAL.ANY([]).[](child=rel#59402:Subset#5.LOGICAL.ANY([]).[],c1=CAST(ITEM($0, 0)):INTEGER), rowcount=1.0, cumulative cost={2.0 rows, 5.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> rel#59414:DrillProjectRel.LOGICAL.ANY([]).[](child=rel#59407:Subset#0.LOGICAL.ANY([]).[],c1=CAST(ITEM($1, 0)):INTEGER), rowcount=1.0, cumulative cost={2.0 rows, 10004.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> Set#2, type: RecordType(BIGINT EXPR$0)
> rel#59388:Subset#2.NONE.ANY([]).[], best=null, importance=0.81
> rel#59387:AggregateRel.NONE.ANY([]).[](child=rel#59386:Subset#1.NONE.ANY([]).[],group={},EXPR$0=COUNT($0)), rowcount=1.7976931348623158E307, cumulative cost={inf}
> rel#59395:Subset#2.LOGICAL.ANY([]).[], best=rel#59406, importance=0.405
> rel#59396:AbstractConverter.LOGICAL.ANY([]).[](child=rel#59388:Subset#2.NONE.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]), rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#59406:DrillAggregateRel.LOGICAL.ANY([]).[](child=rel#59404:Subset#1.LOGICAL.ANY([]).[],group={},EXPR$0=COUNT($0)), rowcount=1.0, cumulative cost={3.0 rows, 6.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> Set#3, type: RecordType(INTEGER c2)
> rel#59390:Subset#3.NONE.ANY([]).[], best=null, importance=0.81
> rel#59389:ProjectRel.NONE.ANY([]).[](child=rel#59384:Subset#0.ENUMERABLE.ANY([]).[],c2=CAST(ITEM($1, 0)):INTEGER), rowcount=100.0, cumulative cost={inf}
> rel#59397:Subset#3.LOGICAL.ANY([]).[], best=rel#59403, importance=0.405
> rel#59398:AbstractConverter.LOGICAL.ANY([]).[](child=rel#59390:Subset#3.NONE.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]), rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#59403:DrillProjectRel.LOGICAL.ANY([]).[](child=rel#59402:Subset#5.LOGICAL.ANY([]).[],c2=CAST(ITEM($0, 0)):INTEGER), rowcount=1.0, cumulative cost={2.0 rows, 5.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> rel#59410:DrillProjectRel.LOGICAL.ANY([]).[](child=rel#59407:Subset#0.LOGICAL.ANY([]).[],c2=CAST(ITEM($1, 0)):INTEGER), rowcount=1.0, cumulative cost={2.0 rows, 10004.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> Set#4, type: RecordType(BIGINT EXPR$0)
> rel#59392:Subset#4.NONE.ANY([]).[], best=null, importance=0.9
> rel#59391:UnionRel.NONE.ANY([]).[](input#0=rel#59388:Subset#2.NONE.ANY([]).[],input#1=rel#59390:Subset#3.NONE.ANY([]).[],all=true), rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#59393:Subset#4.LOGICAL.ANY([]).[], best=null, importance=1.0
> rel#59394:AbstractConverter.LOGICAL.ANY([]).[](child=rel#59392:Subset#4.NONE.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]), rowcount=1.7976931348623157E308, cumulative cost={inf}
> Set#5, type: RecordType(ANY columns)
> rel#59402:Subset#5.LOGICAL.ANY([]).[], best=rel#59400, importance=0.12728571428571428
> rel#59400:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, tmp, testWindow.csv],groupscan=EasyGroupScan [selectionRoot=/tmp/testWindow.csv, numFiles=1, columns=[`columns`[0]], files=[maprfs:/tmp/testWindow.csv]]), rowcount=1.0, cumulative cost={1.0 rows, 1.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> Error: exception while executing query: Failure while executing query. (state=,code=0)
> {code}
> Stack trace from drillbit.log
> {code}
> Set#5, type: RecordType(ANY columns)
> rel#59402:Subset#5.LOGICAL.ANY([]).[], best=rel#59400, importance=0.12728571428571428
> rel#59400:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, tmp, testWindow.csv],groupscan=EasyGroupScan [selectionRoot=/tmp/testWindow.csv, numFiles=1, columns=[`columns`[0]], files=[maprfs:/tmp/testWindow.csv]]), rowcount=1.0, cumulative cost={1.0 rows, 1.0 cpu, 0.0 io, 0.0 network, 0.0 memory}
> at org.eigenbase.relopt.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:445) ~[optiq-core-0.9-drill-r20.jar:na]
> at org.eigenbase.relopt.volcano.RelSubset.buildCheapestPlan(RelSubset.java:287) ~[optiq-core-0.9-drill-r20.jar:na]
> at org.eigenbase.relopt.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:677) ~[optiq-core-0.9-drill-r20.jar:na]
> at net.hydromatic.optiq.tools.Programs$RuleSetProgram.run(Programs.java:165) ~[optiq-core-0.9-drill-r20.jar:na]
> at net.hydromatic.optiq.prepare.PlannerImpl.transform(PlannerImpl.java:275) ~[optiq-core-0.9-drill-r20.jar:na]
> at org.apache.drill.exec.planner.sql.handlers.DefaultSqlHandler.convertToDrel(DefaultSqlHandler.java:206) ~[drill-java-exec-0.9.0-SNAPSHOT-rebuffed.jar:0.9.0-SNAPSHOT]
> at org.apache.drill.exec.planner.sql.handlers.DefaultSqlHandler.getPlan(DefaultSqlHandler.java:138) ~[drill-java-exec-0.9.0-SNAPSHOT-rebuffed.jar:0.9.0-SNAPSHOT]
> at org.apache.drill.exec.planner.sql.DrillSqlWorker.getPlan(DrillSqlWorker.java:145) ~[drill-java-exec-0.9.0-SNAPSHOT-rebuffed.jar:0.9.0-SNAPSHOT]
> at org.apache.drill.exec.work.foreman.Foreman.runSQL(Foreman.java:773) [drill-java-exec-0.9.0-SNAPSHOT-rebuffed.jar:0.9.0-SNAPSHOT]
> at org.apache.drill.exec.work.foreman.Foreman.run(Foreman.java:204) [drill-java-exec-0.9.0-SNAPSHOT-rebuffed.jar:0.9.0-SNAPSHOT]
> ... 3 common frames omitted
> {code}
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