Khurram Faraaz created DRILL-2639:
-------------------------------------
Summary: Panner 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: Jinfeng Ni
Priority: Critical
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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