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From "Khurram Faraaz (JIRA)" <j...@apache.org>
Subject [jira] [Created] (DRILL-3173) Invalid inputs are NOT handled properly by Window functions
Date Fri, 22 May 2015 22:13:17 GMT
Khurram Faraaz created DRILL-3173:
-------------------------------------

             Summary: Invalid inputs are NOT handled properly by Window functions
                 Key: DRILL-3173
                 URL: https://issues.apache.org/jira/browse/DRILL-3173
             Project: Apache Drill
          Issue Type: Bug
          Components: Query Planning & Optimization
    Affects Versions: 1.0.0
         Environment: faec150598840c40827e6493992d81209aa936da
            Reporter: Khurram Faraaz
            Assignee: Jinfeng Ni


Invalid input must be properly handled by window functions. 

{code}
0: jdbc:drill:schema=dfs.tmp> select count(*) over ( partition by -1 order by -1 ) from
`airports.csv`;
Error: SYSTEM ERROR: org.apache.calcite.plan.RelOptPlanner$CannotPlanException: Node [rel#1674:Subset#7.PHYSICAL.SINGLETON([]).[]]
could not be implemented; planner state:

Root: rel#1674:Subset#7.PHYSICAL.SINGLETON([]).[]
Original rel:
AbstractConverter(subset=[rel#1674:Subset#7.PHYSICAL.SINGLETON([]).[]], convention=[PHYSICAL],
DrillDistributionTraitDef=[SINGLETON([])], sort=[[]]): rowcount = 69890.0, cumulative cost
= {inf}, id = 1676
  DrillScreenRel(subset=[rel#1673:Subset#7.LOGICAL.ANY([]).[]]): rowcount = 69890.0, cumulative
cost = {6989.0 rows, 6989.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 1672
    DrillProjectRel(subset=[rel#1671:Subset#6.LOGICAL.ANY([]).[]], EXPR$0=[$0]): rowcount
= 69890.0, cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 1670
      DrillWindowRel(subset=[rel#1669:Subset#5.LOGICAL.ANY([]).[]], window#0=[window(partition
{} order by [] range between UNBOUNDED PRECEDING and CURRENT ROW aggs [COUNT()])]): rowcount
= 69890.0, cumulative cost = {69890.0 rows, 139780.0 cpu, 0.0 io, 0.0 network, 0.0 memory},
id = 1668
        DrillScanRel(subset=[rel#1667:Subset#4.LOGICAL.ANY([]).[]], table=[[dfs, tmp, airports.csv]],
groupscan=[EasyGroupScan [selectionRoot=/tmp/airports.csv, numFiles=1, columns=[`*`], files=[maprfs:///tmp/airports.csv]]]):
rowcount = 69890.0, cumulative cost = {69890.0 rows, 0.0 cpu, 0.0 io, 0.0 network, 0.0 memory},
id = 1651

Sets:
Set#4, type: RecordType()
	rel#1667:Subset#4.LOGICAL.ANY([]).[], best=rel#1651, importance=0.6561
		rel#1651:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, tmp, airports.csv],groupscan=EasyGroupScan
[selectionRoot=/tmp/airports.csv, numFiles=1, columns=[`*`], files=[maprfs:///tmp/airports.csv]]),
rowcount=69890.0, cumulative cost={tiny}
		rel#1695:AbstractConverter.LOGICAL.ANY([]).[](input=rel#1694:Subset#4.PHYSICAL.HASH_DISTRIBUTED([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
rowcount=69890.0, cumulative cost={inf}
		rel#1713:AbstractConverter.LOGICAL.ANY([]).[](input=rel#1712:Subset#4.PHYSICAL.SINGLETON([]).[],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[]),
rowcount=69890.0, cumulative cost={inf}
	rel#1694:Subset#4.PHYSICAL.HASH_DISTRIBUTED([]).[], best=null, importance=0.5904900000000001
		rel#1696:AbstractConverter.PHYSICAL.HASH_DISTRIBUTED([]).[](input=rel#1667:Subset#4.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=HASH_DISTRIBUTED([]),sort=[]),
rowcount=69890.0, cumulative cost={inf}
		rel#1714:AbstractConverter.PHYSICAL.HASH_DISTRIBUTED([]).[](input=rel#1712:Subset#4.PHYSICAL.SINGLETON([]).[],convention=PHYSICAL,DrillDistributionTraitDef=HASH_DISTRIBUTED([]),sort=[]),
rowcount=69890.0, cumulative cost={inf}
		rel#1717:HashToRandomExchangePrel.PHYSICAL.HASH_DISTRIBUTED([]).[](input=rel#1712:Subset#4.PHYSICAL.SINGLETON([]).[]),
rowcount=69890.0, cumulative cost={69891.0 rows, Infinity cpu, 0.0 io, 0.0 network, 0.0 memory}
	rel#1712:Subset#4.PHYSICAL.SINGLETON([]).[], best=rel#1711, importance=0.531441
		rel#1715:AbstractConverter.PHYSICAL.SINGLETON([]).[](input=rel#1667:Subset#4.LOGICAL.ANY([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
rowcount=69890.0, cumulative cost={inf}
		rel#1716:AbstractConverter.PHYSICAL.SINGLETON([]).[](input=rel#1694:Subset#4.PHYSICAL.HASH_DISTRIBUTED([]).[],convention=PHYSICAL,DrillDistributionTraitDef=SINGLETON([]),sort=[]),
rowcount=69890.0, cumulative cost={inf}
		rel#1711:ScanPrel.PHYSICAL.SINGLETON([]).[](groupscan=EasyGroupScan [selectionRoot=/tmp/airports.csv,
numFiles=1, columns=[`*`], files=[maprfs:///tmp/airports.csv]]), rowcount=69890.0, cumulative
cost={tiny}
		rel#1719:UnionExchangePrel.PHYSICAL.SINGLETON([]).[](input=rel#1694:Subset#4.PHYSICAL.HASH_DISTRIBUTED([]).[]),
rowcount=69890.0, cumulative cost={inf}
...
at org.apache.calcite.plan.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:473)
~[calcite-core-1.1.0-drill-r7.jar:1.1.0-drill-r7]
        at org.apache.calcite.plan.volcano.RelSubset.buildCheapestPlan(RelSubset.java:317)
~[calcite-core-1.1.0-drill-r7.jar:1.1.0-drill-r7]
        at org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:811)
~[calcite-core-1.1.0-drill-r7.jar:1.1.0-drill-r7]
        at org.apache.calcite.tools.Programs$RuleSetProgram.run(Programs.java:303) ~[calcite-core-1.1.0-drill-r7.jar:1.1.0-drill-r7]
        at org.apache.calcite.prepare.PlannerImpl.transform(PlannerImpl.java:316) ~[calcite-core-1.1.0-drill-r7.jar:1.1.0-drill-r7]
        at org.apache.drill.exec.planner.sql.handlers.DefaultSqlHandler.convertToPrel(DefaultSqlHandler.java:315)
~[drill-java-exec-1.0.0-mapr-r1-rebuffed.jar:1.0.0-mapr-r1]
        at org.apache.drill.exec.planner.sql.handlers.DefaultSqlHandler.getPlan(DefaultSqlHandler.java:190)
~[drill-java-exec-1.0.0-mapr-r1-rebuffed.jar:1.0.0-mapr-r1]
        at org.apache.drill.exec.planner.sql.DrillSqlWorker.getPlan(DrillSqlWorker.java:177)
~[drill-java-exec-1.0.0-mapr-r1-rebuffed.jar:1.0.0-mapr-r1]
        at org.apache.drill.exec.work.foreman.Foreman.runSQL(Foreman.java:902) [drill-java-exec-1.0.0-mapr-r1-rebuffed.jar:1.0.0-mapr-r1]
        at org.apache.drill.exec.work.foreman.Foreman.run(Foreman.java:240) [drill-java-exec-1.0.0-mapr-r1-rebuffed.jar:1.0.0-mapr-r1]
        ... 3 common frames omitted

{code}



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