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https://issues.apache.org/jira/browse/DRILL-786?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16681876#comment-16681876
 ] 

ASF GitHub Bot commented on DRILL-786:
--------------------------------------

amansinha100 commented on issue #1488: DRILL-786: Allow CROSS JOIN syntax
URL: https://github.com/apache/drill/pull/1488#issuecomment-437470894
 
 
   @ihuzenko sorry I missed responding to your earlier comment.  Based on your 
latest comment, I suppose we can merge this PR but explain the limitation of 
the Cross Join in the documentation until 
[DRILL-6839](https://issues.apache.org/jira/browse/DRILL-6839) is fixed.  
   
   Regarding the underlying issue with the 2 phase StreamingAgg, I did not 
quite understand the comment 
   > Currently for simple cross join query with aggregate function, physical 
rules are applied in order, which is wrong and results into PlanningException:
   
   This is not correct, since rules in Volcano planner are applied iteratively. 
 So there could be an initial state where a physical rule did not match but 
subsequently after other transformations, it could match and be triggered.  I 
would suggest enabling Calcite tracing to get a better idea of what's going on 
with the distribution traits of the NestedLoopJoin that is causing the 
downstream StreamingAgg to not get planned with multi-phase aggregation.  

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> Implement CROSS JOIN
> --------------------
>
>                 Key: DRILL-786
>                 URL: https://issues.apache.org/jira/browse/DRILL-786
>             Project: Apache Drill
>          Issue Type: New Feature
>          Components: Query Planning & Optimization
>    Affects Versions: 1.14.0
>            Reporter: Krystal
>            Assignee: Igor Guzenko
>            Priority: Major
>              Labels: doc-impacting
>             Fix For: 1.15.0
>
>
> git.commit.id.abbrev=5d7e3d3
> 0: jdbc:drill:schema=dfs> select student.name, student.age, 
> student.studentnum from student cross join voter where student.age = 20 and 
> voter.age = 20;
> Query failed: org.apache.drill.exec.rpc.RpcException: Remote failure while 
> running query.[error_id: "af90e65a-c4d7-4635-a436-bbc1444c8db2"
> Root: rel#318:Subset#28.PHYSICAL.SINGLETON([]).[]
> Original rel:
> AbstractConverter(subset=[rel#318:Subset#28.PHYSICAL.SINGLETON([]).[]], 
> convention=[PHYSICAL], DrillDistributionTraitDef=[SINGLETON([])], sort=[[]]): 
> rowcount = 22500.0, cumulative cost = {inf}, id = 320
>   DrillScreenRel(subset=[rel#317:Subset#28.LOGICAL.ANY([]).[]]): rowcount = 
> 22500.0, cumulative cost = {2250.0 rows, 2250.0 cpu, 0.0 io, 0.0 network}, id 
> = 316
>     DrillProjectRel(subset=[rel#315:Subset#27.LOGICAL.ANY([]).[]], name=[$2], 
> age=[$1], studentnum=[$3]): rowcount = 22500.0, cumulative cost = {22500.0 
> rows, 12.0 cpu, 0.0 io, 0.0 network}, id = 314
>       DrillJoinRel(subset=[rel#313:Subset#26.LOGICAL.ANY([]).[]], 
> condition=[true], joinType=[inner]): rowcount = 22500.0, cumulative cost = 
> {22500.0 rows, 0.0 cpu, 0.0 io, 0.0 network}, id = 312
>         DrillFilterRel(subset=[rel#308:Subset#23.LOGICAL.ANY([]).[]], 
> condition=[=(CAST($1):INTEGER, 20)]): rowcount = 150.0, cumulative cost = 
> {1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 network}, id = 307
>           DrillScanRel(subset=[rel#306:Subset#22.LOGICAL.ANY([]).[]], 
> table=[[dfs, student]]): rowcount = 1000.0, cumulative cost = {1000.0 rows, 
> 4000.0 cpu, 0.0 io, 0.0 network}, id = 129
>         DrillFilterRel(subset=[rel#311:Subset#25.LOGICAL.ANY([]).[]], 
> condition=[=(CAST($1):INTEGER, 20)]): rowcount = 150.0, cumulative cost = 
> {1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 network}, id = 310
>           DrillScanRel(subset=[rel#309:Subset#24.LOGICAL.ANY([]).[]], 
> table=[[dfs, voter]]): rowcount = 1000.0, cumulative cost = {1000.0 rows, 
> 2000.0 cpu, 0.0 io, 0.0 network}, id = 140
> Stack trace:
> org.eigenbase.relopt.RelOptPlanner$CannotPlanException: Node 
> [rel#318:Subset#28.PHYSICAL.SINGLETON([]).[]] could not be implemented; 
> planner state:
> Root: rel#318:Subset#28.PHYSICAL.SINGLETON([]).[]
> Original rel:
> AbstractConverter(subset=[rel#318:Subset#28.PHYSICAL.SINGLETON([]).[]], 
> convention=[PHYSICAL], DrillDistributionTraitDef=[SINGLETON([])], sort=[[]]): 
> rowcount = 22500.0, cumulative cost = {inf}, id = 320
>   DrillScreenRel(subset=[rel#317:Subset#28.LOGICAL.ANY([]).[]]): rowcount = 
> 22500.0, cumulative cost = {2250.0 rows, 2250.0 cpu, 0.0 io, 0.0 network}, id 
> = 316
>     DrillProjectRel(subset=[rel#315:Subset#27.LOGICAL.ANY([]).[]], name=[$2], 
> age=[$1], studentnum=[$3]): rowcount = 22500.0, cumulative cost = {22500.0 
> rows, 12.0 cpu, 0.0 io, 0.0 network}, id = 314
>       DrillJoinRel(subset=[rel#313:Subset#26.LOGICAL.ANY([]).[]], 
> condition=[true], joinType=[inner]): rowcount = 22500.0, cumulative cost = 
> {22500.0 rows, 0.0 cpu, 0.0 io, 0.0 network}, id = 312
>         DrillFilterRel(subset=[rel#308:Subset#23.LOGICAL.ANY([]).[]], 
> condition=[=(CAST($1):INTEGER, 20)]): rowcount = 150.0, cumulative cost = 
> {1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 network}, id = 307
>           DrillScanRel(subset=[rel#306:Subset#22.LOGICAL.ANY([]).[]], 
> table=[[dfs, student]]): rowcount = 1000.0, cumulative cost = {1000.0 rows, 
> 4000.0 cpu, 0.0 io, 0.0 network}, id = 129
>         DrillFilterRel(subset=[rel#311:Subset#25.LOGICAL.ANY([]).[]], 
> condition=[=(CAST($1):INTEGER, 20)]): rowcount = 150.0, cumulative cost = 
> {1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 network}, id = 310
>           DrillScanRel(subset=[rel#309:Subset#24.LOGICAL.ANY([]).[]], 
> table=[[dfs, voter]]): rowcount = 1000.0, cumulative cost = {1000.0 rows, 
> 2000.0 cpu, 0.0 io, 0.0 network}, id = 140
> Sets:
> Set#22, type: (DrillRecordRow[*, age, name, studentnum])
> rel#306:Subset#22.LOGICAL.ANY([]).[], best=rel#129, 
> importance=0.5904900000000001
> rel#129:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, student]), 
> rowcount=1000.0, cumulative cost={1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 
> network}
> rel#333:AbstractConverter.LOGICAL.ANY([]).[](child=rel#332:Subset#22.PHYSICAL.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#337:AbstractConverter.LOGICAL.ANY([]).[](child=rel#336:Subset#22.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#332:Subset#22.PHYSICAL.ANY([]).[], best=rel#335, importance=0.531441
> rel#334:AbstractConverter.PHYSICAL.ANY([]).[](child=rel#306:Subset#22.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#338:AbstractConverter.PHYSICAL.ANY([]).[](child=rel#336:Subset#22.PHYSICAL.SINGLETON([]).[],convention=PHYSICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#339:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#306:Subset#22.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#340:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#332:Subset#22.PHYSICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#335:ScanPrel.PHYSICAL.SINGLETON([]).[](groupscan=ParquetGroupScan 
> [entries=[ReadEntryWithPath [path=maprfs:/drill/testdata/p1tests/student]], 
> selectionRoot=/drill/testdata/p1tests/student, columns=[SchemaPath [`age`], 
> SchemaPath [`name`], SchemaPath [`studentnum`]]]), rowcount=1000.0, 
> cumulative cost={1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 network}
> rel#336:Subset#22.PHYSICAL.SINGLETON([]).[], best=rel#335, 
> importance=0.4782969000000001
> rel#339:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#306:Subset#22.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#340:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#332:Subset#22.PHYSICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#335:ScanPrel.PHYSICAL.SINGLETON([]).[](groupscan=ParquetGroupScan 
> [entries=[ReadEntryWithPath [path=maprfs:/drill/testdata/p1tests/student]], 
> selectionRoot=/drill/testdata/p1tests/student, columns=[SchemaPath [`age`], 
> SchemaPath [`name`], SchemaPath [`studentnum`]]]), rowcount=1000.0, 
> cumulative cost={1000.0 rows, 4000.0 cpu, 0.0 io, 0.0 network}
> Set#23, type: (DrillRecordRow[*, age, name, studentnum])
> rel#308:Subset#23.LOGICAL.ANY([]).[], best=rel#307, importance=0.6561
> rel#307:DrillFilterRel.LOGICAL.ANY([]).[](child=rel#306:Subset#22.LOGICAL.ANY([]).[],condition==(CAST($1):INTEGER,
>  20)), rowcount=150.0, cumulative cost={2000.0 rows, 8000.0 cpu, 0.0 io, 0.0 
> network}
> rel#343:AbstractConverter.LOGICAL.ANY([]).[](child=rel#342:Subset#23.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=150.0, cumulative cost={inf}
> rel#342:Subset#23.PHYSICAL.SINGLETON([]).[], best=rel#341, 
> importance=0.5904900000000001
> rel#344:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#308:Subset#23.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=150.0, cumulative cost={inf}
> rel#341:FilterPrel.PHYSICAL.SINGLETON([]).[](child=rel#332:Subset#22.PHYSICAL.ANY([]).[],condition==(CAST($1):INTEGER,
>  20)), rowcount=150.0, cumulative cost={2000.0 rows, 8000.0 cpu, 0.0 io, 0.0 
> network}
> Set#24, type: (DrillRecordRow[*, age])
> rel#309:Subset#24.LOGICAL.ANY([]).[], best=rel#140, 
> importance=0.5904900000000001
> rel#140:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, voter]), rowcount=1000.0, 
> cumulative cost={1000.0 rows, 2000.0 cpu, 0.0 io, 0.0 network}
> rel#330:AbstractConverter.LOGICAL.ANY([]).[](child=rel#329:Subset#24.PHYSICAL.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#349:AbstractConverter.LOGICAL.ANY([]).[](child=rel#348:Subset#24.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#329:Subset#24.PHYSICAL.ANY([]).[], best=rel#347, importance=0.531441
> rel#331:AbstractConverter.PHYSICAL.ANY([]).[](child=rel#309:Subset#24.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#350:AbstractConverter.PHYSICAL.ANY([]).[](child=rel#348:Subset#24.PHYSICAL.SINGLETON([]).[],convention=PHYSICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#351:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#309:Subset#24.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#352:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#329:Subset#24.PHYSICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#347:ScanPrel.PHYSICAL.SINGLETON([]).[](groupscan=ParquetGroupScan 
> [entries=[ReadEntryWithPath [path=maprfs:/drill/testdata/p1tests/voter]], 
> selectionRoot=/drill/testdata/p1tests/voter, columns=[SchemaPath [`age`]]]), 
> rowcount=1000.0, cumulative cost={1000.0 rows, 2000.0 cpu, 0.0 io, 0.0 
> network}
> rel#348:Subset#24.PHYSICAL.SINGLETON([]).[], best=rel#347, 
> importance=0.4782969000000001
> rel#351:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#309:Subset#24.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#352:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#329:Subset#24.PHYSICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=1000.0, cumulative cost={inf}
> rel#347:ScanPrel.PHYSICAL.SINGLETON([]).[](groupscan=ParquetGroupScan 
> [entries=[ReadEntryWithPath [path=maprfs:/drill/testdata/p1tests/voter]], 
> selectionRoot=/drill/testdata/p1tests/voter, columns=[SchemaPath [`age`]]]), 
> rowcount=1000.0, cumulative cost={1000.0 rows, 2000.0 cpu, 0.0 io, 0.0 
> network}
> Set#25, type: (DrillRecordRow[*, age])
> rel#311:Subset#25.LOGICAL.ANY([]).[], best=rel#310, importance=0.6561
> rel#310:DrillFilterRel.LOGICAL.ANY([]).[](child=rel#309:Subset#24.LOGICAL.ANY([]).[],condition==(CAST($1):INTEGER,
>  20)), rowcount=150.0, cumulative cost={2000.0 rows, 6000.0 cpu, 0.0 io, 0.0 
> network}
> rel#355:AbstractConverter.LOGICAL.ANY([]).[](child=rel#354:Subset#25.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=150.0, cumulative cost={inf}
> rel#354:Subset#25.PHYSICAL.SINGLETON([]).[], best=rel#353, 
> importance=0.5904900000000001
> rel#356:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#311:Subset#25.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=150.0, cumulative cost={inf}
> rel#353:FilterPrel.PHYSICAL.SINGLETON([]).[](child=rel#329:Subset#24.PHYSICAL.ANY([]).[],condition==(CAST($1):INTEGER,
>  20)), rowcount=150.0, cumulative cost={2000.0 rows, 6000.0 cpu, 0.0 io, 0.0 
> network}
> Set#26, type: RecordType(ANY *, ANY age, ANY name, ANY studentnum, ANY *0, 
> ANY age0)
> rel#313:Subset#26.LOGICAL.ANY([]).[], best=rel#312, 
> importance=0.7290000000000001
> rel#312:DrillJoinRel.LOGICAL.ANY([]).[](left=rel#308:Subset#23.LOGICAL.ANY([]).[],right=rel#311:Subset#25.LOGICAL.ANY([]).[],condition=true,joinType=inner),
>  rowcount=22500.0, cumulative cost={4001.0 rows, 14001.0 cpu, 0.0 io, 0.0 
> network}
> rel#327:AbstractConverter.LOGICAL.ANY([]).[](child=rel#326:Subset#26.PHYSICAL.ANY([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#326:Subset#26.PHYSICAL.ANY([]).[], best=null, importance=0.6561
> rel#328:AbstractConverter.PHYSICAL.ANY([]).[](child=rel#313:Subset#26.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=22500.0, cumulative cost={inf}
> Set#27, type: RecordType(ANY name, ANY age, ANY studentnum)
> rel#315:Subset#27.LOGICAL.ANY([]).[], best=rel#314, importance=0.81
> rel#314:DrillProjectRel.LOGICAL.ANY([]).[](child=rel#313:Subset#26.LOGICAL.ANY([]).[],name=$2,age=$1,studentnum=$3),
>  rowcount=22500.0, cumulative cost={26501.0 rows, 14013.0 cpu, 0.0 io, 0.0 
> network}
> rel#322:AbstractConverter.LOGICAL.ANY([]).[](child=rel#321:Subset#27.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#321:Subset#27.PHYSICAL.SINGLETON([]).[], best=null, 
> importance=0.7290000000000001
> rel#323:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#315:Subset#27.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=22500.0, cumulative cost={inf}
> Set#28, type: RecordType(ANY name, ANY age, ANY studentnum)
> rel#317:Subset#28.LOGICAL.ANY([]).[], best=rel#316, importance=0.9
> rel#316:DrillScreenRel.LOGICAL.ANY([]).[](child=rel#315:Subset#27.LOGICAL.ANY([]).[]),
>  rowcount=22500.0, cumulative cost={28751.0 rows, 16263.0 cpu, 0.0 io, 0.0 
> network}
> rel#319:AbstractConverter.LOGICAL.ANY([]).[](child=rel#318:Subset#28.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
>  rowcount=1.7976931348623157E308, cumulative cost={inf}
> rel#318:Subset#28.PHYSICAL.SINGLETON([]).[], best=null, importance=1.0
> rel#320:AbstractConverter.PHYSICAL.SINGLETON([]).[](child=rel#317:Subset#28.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
>  rowcount=22500.0, cumulative cost={inf}
> rel#324:ScreenPrel.PHYSICAL.SINGLETON([]).[](child=rel#321:Subset#27.PHYSICAL.SINGLETON([]).[]),
>  rowcount=1.7976931348623157E308, cumulative cost={inf}
> org.eigenbase.relopt.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:445)
>  ~[optiq-core-0.7-20140513.013236-5.jar:na]
> org.eigenbase.relopt.volcano.RelSubset.buildCheapestPlan(RelSubset.java:287) 
> ~[optiq-core-0.7-20140513.013236-5.jar:na]
> org.eigenbase.relopt.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:669)
>  ~[optiq-core-0.7-20140513.013236-5.jar:na]
> net.hydromatic.optiq.prepare.PlannerImpl.transform(PlannerImpl.java:271) 
> ~[optiq-core-0.7-20140513.013236-5.jar:na]
> org.apache.drill.exec.planner.sql.handlers.DefaultSqlHandler.convertToPrel(DefaultSqlHandler.java:119)
>  
> ~[drill-java-exec-1.0.0-m2-incubating-SNAPSHOT-rebuffed.jar:1.0.0-m2-incubating-SNAPSHOT]
> org.apache.drill.exec.planner.sql.handlers.DefaultSqlHandler.getPlan(DefaultSqlHandler.java:89)
>  
> ~[drill-java-exec-1.0.0-m2-incubating-SNAPSHOT-rebuffed.jar:1.0.0-m2-incubating-SNAPSHOT]
> org.apache.drill.exec.planner.sql.DrillSqlWorker.getPlan(DrillSqlWorker.java:134)
>  
> ~[drill-java-exec-1.0.0-m2-incubating-SNAPSHOT-rebuffed.jar:1.0.0-m2-incubating-SNAPSHOT]
> org.apache.drill.exec.work.foreman.Foreman.runSQL(Foreman.java:338) 
> [drill-java-exec-1.0.0-m2-incubating-SNAPSHOT-rebuffed.jar:1.0.0-m2-incubating-SNAPSHOT]
> org.apache.drill.exec.work.foreman.Foreman.run(Foreman.java:186) 
> [drill-java-exec-1.0.0-m2-incubating-SNAPSHOT-rebuffed.jar:1.0.0-m2-incubating-SNAPSHOT]
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>  [na:1.7.0_45]
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>  [na:1.7.0_45]
> java.lang.Thread.run(Thread.java:744) [na:1.7.0_45]



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