The changing of the column order in the SELECT should not materially affect
the planning, so this does look like a bug.   I was able to repro it with a
simpler example (without the group-by):
           select row_number() over (order by department_id desc) r,
department_id
            from (select department_id
                        from  cp.`employee.json`
                        order by department_id desc) ;

Error: SYSTEM ERROR: CannotPlanException: Node
[rel#3170:Subset#4.LOGICAL.ANY([]).[1 DESC]] could not be implemented;
planner state:

I believe the 2 ORDER BYs are causing an issue with the plan generation but
more analysis is needed by looking at the Calcite trace.  However, that
brings up the question of why you need 2 ORDER BYs ?   If the ROW_NUMBER()
is already doing an ORDER BY DESC on the exact same column, *the  subquery
ORDER BY is redundant.*  If you remove it, the query runs OK...

apache drill> *select* row_number() *over* (*order* *by* cnt *desc*) r, cnt

. .semicolon> *from* (*select* *count*(1) *as* cnt

. . . . . .)>   *from*  cp.`employee.json`

. . . . . .)>   *group* *by* department_id);

*+----+-----+*

*| **r ** | **cnt** |*

*+----+-----+*

*| *1 * | *268* |*

*| *2 * | *264* |*

*| *3 * | *226* |*

*| *4 * | *222* |*

*| *5 * | *100* |*

*| *6 * | *32 * |*

*| *7 * | *16 * |*

*| *8 * | *9  * |*

*| *9 * | *7  * |*

*| *10* | *5  * |*

*| *11* | *4  * |*

*| *12* | *2  * |*

*+----+-----+*

12 rows selected

In any case if you can file a JIRA for the original problem that would be
good.

Thanks.

On Fri, May 24, 2019 at 2:57 PM Ted Dunning <ted.dunn...@gmail.com> wrote:

> I have a bunch of data that I want to group up and look at the counts. In
> order to get a row number for plotting, I tried a window function.
>
> The data consists of about 7,2 million rows accessed via a view[1]. The
> columns are pretty much all untyped[2].
>
> This query works great:
>
>
> *with *
> *t0 as (*
> *  select count(1) cnt*
> *  from  dfs.flt.`flights-2018-01.csv` *
> *  group by columns[5]*
> *  order by cnt desc)*
> *select cnt, row_number() over (order by cnt desc) r*
> *from t0*
>
>
> But if I change the order of the columns like this:
>
> *with *
> *t0 as (*
> *  select count(1) cnt*
> *  from  dfs.flt.`flights-2018-01.csv` *
> *  group by columns[5]*
> *  order by cnt desc)*
> *select row_number() over (order by cnt desc) r, cnt*
> *from t0*
>
>
> I get the error below in query planning. That seems so very wrong.
>
> Any ideas? I know I can just avoid the issue, but I was hoping for some
> insight.
>
> For extra oddness points, if I use a common table expression and invert the
> field order, I get what I want with no error:
>
>
> *with *
> *t0 as (*
> *  select count(1) cnt*
> *  from  dfs.flt.`flights-2018-01.csv` *
> *  group by columns[5]*
> *  order by cnt desc),*
> *t1 as (*
> *  select cnt, row_number() over (order by cnt desc) r *
> *  from t0)*
> *select r, cnt*
> *from t1*
>
>
> This means that the planner is not rewriting this to eliminate the common
> table before planning.
>
>
> java.sql.SQLException: [MapR][DrillJDBCDriver](500165) Query execution
> error. Details: SYSTEM ERROR: CannotPlanException: Node
> [rel#18615:Subset#8.LOGICAL.ANY([]).[1 DESC]] could not be implemented;
> planner state: Root: rel#18615:Subset#8.LOGICAL.ANY([]).[1 DESC] Original
> rel: LogicalProject(subset=[rel#18615:Subset#8.LOGICAL.ANY([]).[1 DESC]],
> r=[$1], cnt=[$0]): rowcount = 10.0, cumulative cost = {10.0 rows, 20.0 cpu,
> 0.0 io, 0.0 network, 0.0 memory}, id = 18613
> LogicalWindow(subset=[rel#18612:Subset#7.NONE.ANY([]).[1 DESC]],
> window#0=[window(partition {} order by [0 DESC] rows between UNBOUNDED
> PRECEDING and CURRENT ROW aggs [ROW_NUMBER()])]): rowcount = 10.0,
> cumulative cost = {10.0 rows, 20.0 cpu, 0.0 io, 0.0 network, 0.0 memory},
> id = 18611 LogicalSort(subset=[rel#18610:Subset#6.NONE.ANY([]).[0 DESC]],
> sort0=[$0], dir0=[DESC]): rowcount = 10.0, cumulative cost = {10.0 rows,
> 92.10340371976184 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18609
> LogicalProject(subset=[rel#18608:Subset#5.NONE.ANY([]).[]], cnt=[$1]):
> rowcount = 10.0, cumulative cost = {10.0 rows, 10.0 cpu, 0.0 io, 0.0
> network, 0.0 memory}, id = 18607
> LogicalAggregate(subset=[rel#18606:Subset#4.NONE.ANY([]).[]], group=[{0}],
> cnt=[COUNT($1)]): rowcount = 10.0, cumulative cost = {11.25 rows, 0.0 cpu,
> 0.0 io, 0.0 network, 0.0 memory}, id = 18605
> LogicalProject(subset=[rel#18604:Subset#3.NONE.ANY([]).[]],
> dest_airport_id=[$5], $f1=[1]): rowcount = 100.0, cumulative cost = {100.0
> rows, 200.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18603
> LogicalProject(subset=[rel#18602:Subset#2.NONE.ANY([]).[]], fl_date=[$0],
> op_unique_carrier=[$1], tail_num=[$2], op_carrier_fl_num=[$3],
> origin_airport_id=[$4], dest_airport_id=[$5], crs_dep_time=[$6],
> dep_time=[$7], dep_delay=[$8], taxi_out=[$9], wheels_off=[$10],
> wheels_on=[$11], taxi_in=[$12], arr_time=[$13], arr_delay=[$14],
> air_time=[$15], distance=[$16]): rowcount = 100.0, cumulative cost = {100.0
> rows, 1700.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18601
> LogicalProject(subset=[rel#18600:Subset#1.NONE.ANY([]).[]],
> EXPR$0=[ITEM($1, 0)], EXPR$1=[ITEM($1, 1)], EXPR$2=[ITEM($1, 2)],
> EXPR$3=[ITEM($1, 3)], EXPR$4=[ITEM($1, 4)], EXPR$5=[ITEM($1, 5)],
> EXPR$6=[ITEM($1, 6)], EXPR$7=[ITEM($1, 7)], EXPR$8=[ITEM($1, 8)],
> EXPR$9=[ITEM($1, 9)], EXPR$10=[ITEM($1, 10)], EXPR$11=[ITEM($1, 11)],
> EXPR$12=[ITEM($1, 12)], EXPR$13=[ITEM($1, 13)], EXPR$14=[ITEM($1, 14)],
> EXPR$15=[ITEM($1, 15)], EXPR$16=[ITEM($1, 16)]): rowcount = 100.0,
> cumulative cost = {100.0 rows, 1700.0 cpu, 0.0 io, 0.0 network, 0.0
> memory}, id = 18599
> EnumerableTableScan(subset=[rel#18598:Subset#0.ENUMERABLE.ANY([]).[]],
> table=[[dfs, flt, flights-2018-*.csv]]): rowcount = 100.0, cumulative cost
> = {100.0 rows, 101.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18507
> Sets: Set#0, type: RecordType(DYNAMIC_STAR **, ANY columns)
> rel#18598:Subset#0.ENUMERABLE.ANY([]).[], best=rel#18507,
> importance=0.4304672100000001
> rel#18507:EnumerableTableScan.ENUMERABLE.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv]), rowcount=100.0, cumulative cost={100.0 rows, 101.0
> cpu, 0.0 io, 0.0 network, 0.0 memory}
> rel#18644:Subset#0.LOGICAL.ANY([]).[], best=rel#18653,
> importance=0.28936962450000003
> rel#18653:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv],groupscan=EasyGroupScan
> [selectionRoot=maprfs:/mapr/61-demo/flights, numFiles=12, columns=[`**`,
> `columns`], files=[maprfs:/mapr/61-demo/flights/flights-2018-01.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-02.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-03.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-04.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-05.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-06.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-07.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-08.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-09.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-10.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-11.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-12.csv]]), rowcount=8370632.0,
> cumulative cost={8370632.0 rows, 8.370632E10 cpu, 0.0 io, 0.0 network, 0.0
> memory} Set#1, type: RecordType(ANY EXPR$0, ANY EXPR$1, ANY EXPR$2, ANY
> EXPR$3, ANY EXPR$4, ANY EXPR$5, ANY EXPR$6, ANY EXPR$7, ANY EXPR$8, ANY
> EXPR$9, ANY EXPR$10, ANY EXPR$11, ANY EXPR$12, ANY EXPR$13, ANY EXPR$14,
> ANY EXPR$15, ANY EXPR$16) rel#18600:Subset#1.NONE.ANY([]).[], best=null,
> importance=0.4782969000000001
>
> rel#18599:LogicalProject.NONE.ANY([]).[](input=rel#18598:Subset#0.ENUMERABLE.ANY([]).[],EXPR$0=ITEM($1,
> 0),EXPR$1=ITEM($1, 1),EXPR$2=ITEM($1, 2),EXPR$3=ITEM($1, 3),EXPR$4=ITEM($1,
> 4),EXPR$5=ITEM($1, 5),EXPR$6=ITEM($1, 6),EXPR$7=ITEM($1, 7),EXPR$8=ITEM($1,
> 8),EXPR$9=ITEM($1, 9),EXPR$10=ITEM($1, 10),EXPR$11=ITEM($1,
> 11),EXPR$12=ITEM($1, 12),EXPR$13=ITEM($1, 13),EXPR$14=ITEM($1,
> 14),EXPR$15=ITEM($1, 15),EXPR$16=ITEM($1, 16)), rowcount=100.0, cumulative
> cost={inf}
>
> rel#18601:LogicalProject.NONE.ANY([]).[](input=rel#18600:Subset#1.NONE.ANY([]).[],fl_date=$0,op_unique_carrier=$1,tail_num=$2,op_carrier_fl_num=$3,origin_airport_id=$4,dest_airport_id=$5,crs_dep_time=$6,dep_time=$7,dep_delay=$8,taxi_out=$9,wheels_off=$10,wheels_on=$11,taxi_in=$12,arr_time=$13,arr_delay=$14,air_time=$15,distance=$16),
> rowcount=100.0, cumulative cost={inf}
> rel#18636:Subset#1.LOGICAL.ANY([]).[], best=rel#18649,
> importance=0.28936962450000003
>
> rel#18649:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18648:Subset#10.LOGICAL.ANY([]).[],EXPR$0=ITEM($0,
> 0),EXPR$1=ITEM($0, 1),EXPR$2=ITEM($0, 2),EXPR$3=ITEM($0, 3),EXPR$4=ITEM($0,
> 4),EXPR$5=ITEM($0, 5),EXPR$6=ITEM($0, 6),EXPR$7=ITEM($0, 7),EXPR$8=ITEM($0,
> 8),EXPR$9=ITEM($0, 9),EXPR$10=ITEM($0, 10),EXPR$11=ITEM($0,
> 11),EXPR$12=ITEM($0, 12),EXPR$13=ITEM($0, 13),EXPR$14=ITEM($0,
> 14),EXPR$15=ITEM($0, 15),EXPR$16=ITEM($0, 16)), rowcount=8370632.0,
> cumulative cost={1.6741264E7 rows, 5.77573608E8 cpu, 0.0 io, 0.0 network,
> 0.0 memory}
>
> rel#18650:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18644:Subset#0.LOGICAL.ANY([]).[],EXPR$0=ITEM($1,
> 0),EXPR$1=ITEM($1, 1),EXPR$2=ITEM($1, 2),EXPR$3=ITEM($1, 3),EXPR$4=ITEM($1,
> 4),EXPR$5=ITEM($1, 5),EXPR$6=ITEM($1, 6),EXPR$7=ITEM($1, 7),EXPR$8=ITEM($1,
> 8),EXPR$9=ITEM($1, 9),EXPR$10=ITEM($1, 10),EXPR$11=ITEM($1,
> 11),EXPR$12=ITEM($1, 12),EXPR$13=ITEM($1, 13),EXPR$14=ITEM($1,
> 14),EXPR$15=ITEM($1, 15),EXPR$16=ITEM($1, 16)), rowcount=8370632.0,
> cumulative cost={1.6741264E7 rows, 8.4275522976E10 cpu, 0.0 io, 0.0
> network, 0.0 memory}
>
> rel#18651:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18636:Subset#1.LOGICAL.ANY([]).[],fl_date=$0,op_unique_carrier=$1,tail_num=$2,op_carrier_fl_num=$3,origin_airport_id=$4,dest_airport_id=$5,crs_dep_time=$6,dep_time=$7,dep_delay=$8,taxi_out=$9,wheels_off=$10,wheels_on=$11,taxi_in=$12,arr_time=$13,arr_delay=$14,air_time=$15,distance=$16),
> rowcount=8370632.0, cumulative cost={2.5111896E7 rows, 7.19874352E8 cpu,
> 0.0 io, 0.0 network, 0.0 memory} Set#3, type: RecordType(ANY
> dest_airport_id, INTEGER $f1) rel#18604:Subset#3.NONE.ANY([]).[],
> best=null, importance=0.531441
>
> rel#18634:LogicalProject.NONE.ANY([]).[](input=rel#18600:Subset#1.NONE.ANY([]).[],dest_airport_id=$5,$f1=1),
> rowcount=100.0, cumulative cost={inf}
>
> rel#18638:LogicalProject.NONE.ANY([]).[](input=rel#18598:Subset#0.ENUMERABLE.ANY([]).[],dest_airport_id=ITEM($1,
> 5),$f1=1), rowcount=100.0, cumulative cost={inf}
> rel#18630:Subset#3.LOGICAL.ANY([]).[], best=rel#18643, importance=0.2657205
>
> rel#18637:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18636:Subset#1.LOGICAL.ANY([]).[],dest_airport_id=$5,$f1=1),
> rowcount=8370632.0, cumulative cost={2.5111896E7 rows, 6.19426768E8 cpu,
> 0.0 io, 0.0 network, 0.0 memory}
>
> rel#18643:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18642:Subset#9.LOGICAL.ANY([]).[],dest_airport_id=ITEM($0,
> 5),$f1=1), rowcount=8370632.0, cumulative cost={1.6741264E7 rows,
> 7.5335688E7 cpu, 0.0 io, 0.0 network, 0.0 memory}
>
> rel#18645:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18644:Subset#0.LOGICAL.ANY([]).[],dest_airport_id=ITEM($1,
> 5),$f1=1), rowcount=8370632.0, cumulative cost={1.6741264E7 rows,
> 8.3773285056E10 cpu, 0.0 io, 0.0 network, 0.0 memory} Set#4, type:
> RecordType(ANY dest_airport_id, BIGINT cnt)
> rel#18606:Subset#4.NONE.ANY([]).[], best=null,
> importance=0.5904900000000001
>
> rel#18605:LogicalAggregate.NONE.ANY([]).[](input=rel#18604:Subset#3.NONE.ANY([]).[],group={0},cnt=COUNT($1)),
> rowcount=10.0, cumulative cost={inf} rel#18628:Subset#4.LOGICAL.ANY([]).[],
> best=rel#18631, importance=0.29524500000000004
>
> rel#18631:DrillAggregateRel.LOGICAL.ANY([]).[](input=rel#18630:Subset#3.LOGICAL.ANY([]).[],group={0},cnt=COUNT($1)),
> rowcount=8370581.997901573, cumulative cost={2.5111896E7 rows, 2.42748328E8
> cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory} Set#5, type:
> RecordType(BIGINT cnt) rel#18608:Subset#5.NONE.ANY([]).[], best=null,
> importance=0.6561
>
> rel#18607:LogicalProject.NONE.ANY([]).[](input=rel#18606:Subset#4.NONE.ANY([]).[],cnt=$1),
> rowcount=10.0, cumulative cost={inf} rel#18609:LogicalSort.NONE.ANY([]).[0
> DESC](input=rel#18608:Subset#5.NONE.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=10.0, cumulative cost={inf} rel#18621:Subset#5.LOGICAL.ANY([]).[],
> best=rel#18629, importance=0.405 rel#18622:DrillSortRel.LOGICAL.ANY([]).[0
> DESC](input=rel#18621:Subset#5.LOGICAL.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=8370581.997901573, cumulative cost={4.185305999580315E7 rows,
> 7.848350521732183E8 cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory}
>
> rel#18629:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18628:Subset#4.LOGICAL.ANY([]).[],cnt=$1),
> rowcount=8370581.997901573, cumulative cost={3.3482477997901574E7 rows,
> 2.5111890999790156E8 cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory}
> rel#18624:Subset#5.NONE.ANY([]).[0 DESC], best=null,
> importance=0.7290000000000001 rel#18609:LogicalSort.NONE.ANY([]).[0
> DESC](input=rel#18608:Subset#5.NONE.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=10.0, cumulative cost={inf} rel#18625:Subset#5.LOGICAL.ANY([]).[1
> DESC], best=null, importance=0.81 rel#18626:Subset#5.LOGICAL.ANY([]).[0
> DESC], best=rel#18622, importance=0.405
> rel#18622:DrillSortRel.LOGICAL.ANY([]).[0
> DESC](input=rel#18621:Subset#5.LOGICAL.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=8370581.997901573, cumulative cost={4.185305999580315E7 rows,
> 7.848350521732183E8 cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory}
> Set#7, type: RecordType(BIGINT cnt, BIGINT w0$o0)
> rel#18612:Subset#7.NONE.ANY([]).[1 DESC], best=null, importance=0.81
> rel#18611:LogicalWindow.NONE.ANY([]).[[1
> DESC]](input=rel#18624:Subset#5.NONE.ANY([]).[0
> DESC],window#0=window(partition {} order by [0 DESC] rows between UNBOUNDED
> PRECEDING and CURRENT ROW aggs [ROW_NUMBER()])), rowcount=10.0, cumulative
> cost={inf} rel#18617:Subset#7.LOGICAL.ANY([]).[1 DESC], best=null,
> importance=0.9 rel#18620:DrillWindowRel.LOGICAL.ANY([]).[1
> DESC](input=rel#18625:Subset#5.LOGICAL.ANY([]).[1
> DESC],window#0=window(partition {} order by [0 DESC] rows between UNBOUNDED
> PRECEDING and CURRENT ROW aggs [ROW_NUMBER()])), rowcount=10.0, cumulative
> cost={inf} Set#8, type: RecordType(BIGINT r, BIGINT cnt)
> rel#18614:Subset#8.NONE.ANY([]).[1 DESC], best=null, importance=0.9
> rel#18613:LogicalProject.NONE.ANY([]).[[1
> DESC]](input=rel#18612:Subset#7.NONE.ANY([]).[1 DESC],r=$1,cnt=$0),
> rowcount=10.0, cumulative cost={inf} rel#18615:Subset#8.LOGICAL.ANY([]).[1
> DESC], best=null, importance=1.0
> rel#18616:AbstractConverter.LOGICAL.ANY([]).[1
> DESC](input=rel#18614:Subset#8.NONE.ANY([]).[1
> DESC],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[1 DESC]),
> rowcount=10.0, cumulative cost={inf}
> rel#18618:DrillProjectRel.LOGICAL.ANY([]).[[1
> DESC]](input=rel#18617:Subset#7.LOGICAL.ANY([]).[1 DESC],r=$1,cnt=$0),
> rowcount=10.0, cumulative cost={inf} Set#9, type: RecordType(ANY columns)
> rel#18642:Subset#9.LOGICAL.ANY([]).[], best=rel#18640,
> importance=0.05314410000000001
> rel#18640:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv],groupscan=EasyGroupScan
> [selectionRoot=maprfs:/mapr/61-demo/flights, numFiles=12,
> columns=[`columns`[5]],
> files=[maprfs:/mapr/61-demo/flights/flights-2018-01.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-02.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-03.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-04.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-05.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-06.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-07.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-08.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-09.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-10.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-11.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-12.csv]]), rowcount=8370632.0,
> cumulative cost={8370632.0 rows, 8370632.0 cpu, 0.0 io, 0.0 network, 0.0
> memory} Set#10, type: RecordType(ANY columns)
> rel#18648:Subset#10.LOGICAL.ANY([]).[], best=rel#18646,
> importance=0.007410233661971832
> rel#18646:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv],groupscan=EasyGroupScan
> [selectionRoot=maprfs:/mapr/61-demo/flights, numFiles=12,
> columns=[`columns`[0], `columns`[1], `columns`[2], `columns`[3],
> `columns`[4], `columns`[5], `columns`[6], `columns`[7], `columns`[8],
> `columns`[9], `columns`[10], `columns`[11], `columns`[12], `columns`[13],
> `columns`[14], `columns`[15], `columns`[16]],
> files=[maprfs:/mapr/61-demo/flights/flights-2018-01.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-02.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-03.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-04.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-05.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-06.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-07.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-08.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-09.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-10.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-11.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-12.csv]]), rowcount=8370632.0,
> cumulative cost={8370632.0 rows, 8370632.0 cpu, 0.0 io, 0.0 network, 0.0
> memory} [Error Id: e05bca25-7110-47aa-b872-60aa1b2fdc34 on
> mdn-1.mdn.tdunning-dsr-demo-z6io48.svc.cluster.local:31010]. at
>
> com.mapr.drill.drill.dataengine.DRQryResultListener.checkAndThrowException(Unknown
> Source) at
> com.mapr.drill.drill.dataengine.DRQryResultListener.getNextBatch(Unknown
> Source) at
>
> com.mapr.drill.drill.dataengine.DRJDBCResultSet.doLoadRecordBatchData(Unknown
> Source) at
> com.mapr.drill.drill.dataengine.DRJDBCResultSet.doMoveToNextRow(Unknown
> Source) at
> com.mapr.drill.drill.dataengine.DRJDBCQueryExecutor.execute(Unknown Source)
> at com.mapr.drill.jdbc.common.SStatement.executeNoParams(Unknown Source) at
> com.mapr.drill.jdbc.common.SStatement.execute(Unknown Source) at
>
> org.apache.commons.dbcp2.DelegatingStatement.execute(DelegatingStatement.java:291)
> at
>
> org.apache.commons.dbcp2.DelegatingStatement.execute(DelegatingStatement.java:291)
> at
>
> org.apache.zeppelin.jdbc.JDBCInterpreter.executeSql(JDBCInterpreter.java:718)
> at
>
> org.apache.zeppelin.jdbc.JDBCInterpreter.interpret(JDBCInterpreter.java:801)
> at
>
> org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:103)
> at
>
> org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:633)
> at org.apache.zeppelin.scheduler.Job.run(Job.java:188) at
>
> org.apache.zeppelin.scheduler.ParallelScheduler$JobRunner.run(ParallelScheduler.java:162)
> at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.run(FutureTask.java:266) at
>
> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
> at
>
> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
> at
>
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
>
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> Caused by: com.mapr.drill.support.exceptions.GeneralException:
> [MapR][DrillJDBCDriver](500165) Query execution error. Details: SYSTEM
> ERROR: CannotPlanException: Node [rel#18615:Subset#8.LOGICAL.ANY([]).[1
> DESC]] could not be implemented; planner state: Root:
> rel#18615:Subset#8.LOGICAL.ANY([]).[1 DESC] Original rel:
> LogicalProject(subset=[rel#18615:Subset#8.LOGICAL.ANY([]).[1 DESC]],
> r=[$1], cnt=[$0]): rowcount = 10.0, cumulative cost = {10.0 rows, 20.0 cpu,
> 0.0 io, 0.0 network, 0.0 memory}, id = 18613
> LogicalWindow(subset=[rel#18612:Subset#7.NONE.ANY([]).[1 DESC]],
> window#0=[window(partition {} order by [0 DESC] rows between UNBOUNDED
> PRECEDING and CURRENT ROW aggs [ROW_NUMBER()])]): rowcount = 10.0,
> cumulative cost = {10.0 rows, 20.0 cpu, 0.0 io, 0.0 network, 0.0 memory},
> id = 18611 LogicalSort(subset=[rel#18610:Subset#6.NONE.ANY([]).[0 DESC]],
> sort0=[$0], dir0=[DESC]): rowcount = 10.0, cumulative cost = {10.0 rows,
> 92.10340371976184 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18609
> LogicalProject(subset=[rel#18608:Subset#5.NONE.ANY([]).[]], cnt=[$1]):
> rowcount = 10.0, cumulative cost = {10.0 rows, 10.0 cpu, 0.0 io, 0.0
> network, 0.0 memory}, id = 18607
> LogicalAggregate(subset=[rel#18606:Subset#4.NONE.ANY([]).[]], group=[{0}],
> cnt=[COUNT($1)]): rowcount = 10.0, cumulative cost = {11.25 rows, 0.0 cpu,
> 0.0 io, 0.0 network, 0.0 memory}, id = 18605
> LogicalProject(subset=[rel#18604:Subset#3.NONE.ANY([]).[]],
> dest_airport_id=[$5], $f1=[1]): rowcount = 100.0, cumulative cost = {100.0
> rows, 200.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18603
> LogicalProject(subset=[rel#18602:Subset#2.NONE.ANY([]).[]], fl_date=[$0],
> op_unique_carrier=[$1], tail_num=[$2], op_carrier_fl_num=[$3],
> origin_airport_id=[$4], dest_airport_id=[$5], crs_dep_time=[$6],
> dep_time=[$7], dep_delay=[$8], taxi_out=[$9], wheels_off=[$10],
> wheels_on=[$11], taxi_in=[$12], arr_time=[$13], arr_delay=[$14],
> air_time=[$15], distance=[$16]): rowcount = 100.0, cumulative cost = {100.0
> rows, 1700.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18601
> LogicalProject(subset=[rel#18600:Subset#1.NONE.ANY([]).[]],
> EXPR$0=[ITEM($1, 0)], EXPR$1=[ITEM($1, 1)], EXPR$2=[ITEM($1, 2)],
> EXPR$3=[ITEM($1, 3)], EXPR$4=[ITEM($1, 4)], EXPR$5=[ITEM($1, 5)],
> EXPR$6=[ITEM($1, 6)], EXPR$7=[ITEM($1, 7)], EXPR$8=[ITEM($1, 8)],
> EXPR$9=[ITEM($1, 9)], EXPR$10=[ITEM($1, 10)], EXPR$11=[ITEM($1, 11)],
> EXPR$12=[ITEM($1, 12)], EXPR$13=[ITEM($1, 13)], EXPR$14=[ITEM($1, 14)],
> EXPR$15=[ITEM($1, 15)], EXPR$16=[ITEM($1, 16)]): rowcount = 100.0,
> cumulative cost = {100.0 rows, 1700.0 cpu, 0.0 io, 0.0 network, 0.0
> memory}, id = 18599
> EnumerableTableScan(subset=[rel#18598:Subset#0.ENUMERABLE.ANY([]).[]],
> table=[[dfs, flt, flights-2018-*.csv]]): rowcount = 100.0, cumulative cost
> = {100.0 rows, 101.0 cpu, 0.0 io, 0.0 network, 0.0 memory}, id = 18507
> Sets: Set#0, type: RecordType(DYNAMIC_STAR **, ANY columns)
> rel#18598:Subset#0.ENUMERABLE.ANY([]).[], best=rel#18507,
> importance=0.4304672100000001
> rel#18507:EnumerableTableScan.ENUMERABLE.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv]), rowcount=100.0, cumulative cost={100.0 rows, 101.0
> cpu, 0.0 io, 0.0 network, 0.0 memory}
> rel#18644:Subset#0.LOGICAL.ANY([]).[], best=rel#18653,
> importance=0.28936962450000003
> rel#18653:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv],groupscan=EasyGroupScan
> [selectionRoot=maprfs:/mapr/61-demo/flights, numFiles=12, columns=[`**`,
> `columns`], files=[maprfs:/mapr/61-demo/flights/flights-2018-01.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-02.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-03.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-04.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-05.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-06.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-07.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-08.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-09.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-10.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-11.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-12.csv]]), rowcount=8370632.0,
> cumulative cost={8370632.0 rows, 8.370632E10 cpu, 0.0 io, 0.0 network, 0.0
> memory} Set#1, type: RecordType(ANY EXPR$0, ANY EXPR$1, ANY EXPR$2, ANY
> EXPR$3, ANY EXPR$4, ANY EXPR$5, ANY EXPR$6, ANY EXPR$7, ANY EXPR$8, ANY
> EXPR$9, ANY EXPR$10, ANY EXPR$11, ANY EXPR$12, ANY EXPR$13, ANY EXPR$14,
> ANY EXPR$15, ANY EXPR$16) rel#18600:Subset#1.NONE.ANY([]).[], best=null,
> importance=0.4782969000000001
>
> rel#18599:LogicalProject.NONE.ANY([]).[](input=rel#18598:Subset#0.ENUMERABLE.ANY([]).[],EXPR$0=ITEM($1,
> 0),EXPR$1=ITEM($1, 1),EXPR$2=ITEM($1, 2),EXPR$3=ITEM($1, 3),EXPR$4=ITEM($1,
> 4),EXPR$5=ITEM($1, 5),EXPR$6=ITEM($1, 6),EXPR$7=ITEM($1, 7),EXPR$8=ITEM($1,
> 8),EXPR$9=ITEM($1, 9),EXPR$10=ITEM($1, 10),EXPR$11=ITEM($1,
> 11),EXPR$12=ITEM($1, 12),EXPR$13=ITEM($1, 13),EXPR$14=ITEM($1,
> 14),EXPR$15=ITEM($1, 15),EXPR$16=ITEM($1, 16)), rowcount=100.0, cumulative
> cost={inf}
>
> rel#18601:LogicalProject.NONE.ANY([]).[](input=rel#18600:Subset#1.NONE.ANY([]).[],fl_date=$0,op_unique_carrier=$1,tail_num=$2,op_carrier_fl_num=$3,origin_airport_id=$4,dest_airport_id=$5,crs_dep_time=$6,dep_time=$7,dep_delay=$8,taxi_out=$9,wheels_off=$10,wheels_on=$11,taxi_in=$12,arr_time=$13,arr_delay=$14,air_time=$15,distance=$16),
> rowcount=100.0, cumulative cost={inf}
> rel#18636:Subset#1.LOGICAL.ANY([]).[], best=rel#18649,
> importance=0.28936962450000003
>
> rel#18649:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18648:Subset#10.LOGICAL.ANY([]).[],EXPR$0=ITEM($0,
> 0),EXPR$1=ITEM($0, 1),EXPR$2=ITEM($0, 2),EXPR$3=ITEM($0, 3),EXPR$4=ITEM($0,
> 4),EXPR$5=ITEM($0, 5),EXPR$6=ITEM($0, 6),EXPR$7=ITEM($0, 7),EXPR$8=ITEM($0,
> 8),EXPR$9=ITEM($0, 9),EXPR$10=ITEM($0, 10),EXPR$11=ITEM($0,
> 11),EXPR$12=ITEM($0, 12),EXPR$13=ITEM($0, 13),EXPR$14=ITEM($0,
> 14),EXPR$15=ITEM($0, 15),EXPR$16=ITEM($0, 16)), rowcount=8370632.0,
> cumulative cost={1.6741264E7 rows, 5.77573608E8 cpu, 0.0 io, 0.0 network,
> 0.0 memory}
>
> rel#18650:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18644:Subset#0.LOGICAL.ANY([]).[],EXPR$0=ITEM($1,
> 0),EXPR$1=ITEM($1, 1),EXPR$2=ITEM($1, 2),EXPR$3=ITEM($1, 3),EXPR$4=ITEM($1,
> 4),EXPR$5=ITEM($1, 5),EXPR$6=ITEM($1, 6),EXPR$7=ITEM($1, 7),EXPR$8=ITEM($1,
> 8),EXPR$9=ITEM($1, 9),EXPR$10=ITEM($1, 10),EXPR$11=ITEM($1,
> 11),EXPR$12=ITEM($1, 12),EXPR$13=ITEM($1, 13),EXPR$14=ITEM($1,
> 14),EXPR$15=ITEM($1, 15),EXPR$16=ITEM($1, 16)), rowcount=8370632.0,
> cumulative cost={1.6741264E7 rows, 8.4275522976E10 cpu, 0.0 io, 0.0
> network, 0.0 memory}
>
> rel#18651:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18636:Subset#1.LOGICAL.ANY([]).[],fl_date=$0,op_unique_carrier=$1,tail_num=$2,op_carrier_fl_num=$3,origin_airport_id=$4,dest_airport_id=$5,crs_dep_time=$6,dep_time=$7,dep_delay=$8,taxi_out=$9,wheels_off=$10,wheels_on=$11,taxi_in=$12,arr_time=$13,arr_delay=$14,air_time=$15,distance=$16),
> rowcount=8370632.0, cumulative cost={2.5111896E7 rows, 7.19874352E8 cpu,
> 0.0 io, 0.0 network, 0.0 memory} Set#3, type: RecordType(ANY
> dest_airport_id, INTEGER $f1) rel#18604:Subset#3.NONE.ANY([]).[],
> best=null, importance=0.531441
>
> rel#18634:LogicalProject.NONE.ANY([]).[](input=rel#18600:Subset#1.NONE.ANY([]).[],dest_airport_id=$5,$f1=1),
> rowcount=100.0, cumulative cost={inf}
>
> rel#18638:LogicalProject.NONE.ANY([]).[](input=rel#18598:Subset#0.ENUMERABLE.ANY([]).[],dest_airport_id=ITEM($1,
> 5),$f1=1), rowcount=100.0, cumulative cost={inf}
> rel#18630:Subset#3.LOGICAL.ANY([]).[], best=rel#18643, importance=0.2657205
>
> rel#18637:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18636:Subset#1.LOGICAL.ANY([]).[],dest_airport_id=$5,$f1=1),
> rowcount=8370632.0, cumulative cost={2.5111896E7 rows, 6.19426768E8 cpu,
> 0.0 io, 0.0 network, 0.0 memory}
>
> rel#18643:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18642:Subset#9.LOGICAL.ANY([]).[],dest_airport_id=ITEM($0,
> 5),$f1=1), rowcount=8370632.0, cumulative cost={1.6741264E7 rows,
> 7.5335688E7 cpu, 0.0 io, 0.0 network, 0.0 memory}
>
> rel#18645:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18644:Subset#0.LOGICAL.ANY([]).[],dest_airport_id=ITEM($1,
> 5),$f1=1), rowcount=8370632.0, cumulative cost={1.6741264E7 rows,
> 8.3773285056E10 cpu, 0.0 io, 0.0 network, 0.0 memory} Set#4, type:
> RecordType(ANY dest_airport_id, BIGINT cnt)
> rel#18606:Subset#4.NONE.ANY([]).[], best=null,
> importance=0.5904900000000001
>
> rel#18605:LogicalAggregate.NONE.ANY([]).[](input=rel#18604:Subset#3.NONE.ANY([]).[],group={0},cnt=COUNT($1)),
> rowcount=10.0, cumulative cost={inf} rel#18628:Subset#4.LOGICAL.ANY([]).[],
> best=rel#18631, importance=0.29524500000000004
>
> rel#18631:DrillAggregateRel.LOGICAL.ANY([]).[](input=rel#18630:Subset#3.LOGICAL.ANY([]).[],group={0},cnt=COUNT($1)),
> rowcount=8370581.997901573, cumulative cost={2.5111896E7 rows, 2.42748328E8
> cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory} Set#5, type:
> RecordType(BIGINT cnt) rel#18608:Subset#5.NONE.ANY([]).[], best=null,
> importance=0.6561
>
> rel#18607:LogicalProject.NONE.ANY([]).[](input=rel#18606:Subset#4.NONE.ANY([]).[],cnt=$1),
> rowcount=10.0, cumulative cost={inf} rel#18609:LogicalSort.NONE.ANY([]).[0
> DESC](input=rel#18608:Subset#5.NONE.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=10.0, cumulative cost={inf} rel#18621:Subset#5.LOGICAL.ANY([]).[],
> best=rel#18629, importance=0.405 rel#18622:DrillSortRel.LOGICAL.ANY([]).[0
> DESC](input=rel#18621:Subset#5.LOGICAL.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=8370581.997901573, cumulative cost={4.185305999580315E7 rows,
> 7.848350521732183E8 cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory}
>
> rel#18629:DrillProjectRel.LOGICAL.ANY([]).[](input=rel#18628:Subset#4.LOGICAL.ANY([]).[],cnt=$1),
> rowcount=8370581.997901573, cumulative cost={3.3482477997901574E7 rows,
> 2.5111890999790156E8 cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory}
> rel#18624:Subset#5.NONE.ANY([]).[0 DESC], best=null,
> importance=0.7290000000000001 rel#18609:LogicalSort.NONE.ANY([]).[0
> DESC](input=rel#18608:Subset#5.NONE.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=10.0, cumulative cost={inf} rel#18625:Subset#5.LOGICAL.ANY([]).[1
> DESC], best=null, importance=0.81 rel#18626:Subset#5.LOGICAL.ANY([]).[0
> DESC], best=rel#18622, importance=0.405
> rel#18622:DrillSortRel.LOGICAL.ANY([]).[0
> DESC](input=rel#18621:Subset#5.LOGICAL.ANY([]).[],sort0=$0,dir0=DESC),
> rowcount=8370581.997901573, cumulative cost={4.185305999580315E7 rows,
> 7.848350521732183E8 cpu, 0.0 io, 0.0 network, 1.4732312320000002E8 memory}
> Set#7, type: RecordType(BIGINT cnt, BIGINT w0$o0)
> rel#18612:Subset#7.NONE.ANY([]).[1 DESC], best=null, importance=0.81
> rel#18611:LogicalWindow.NONE.ANY([]).[[1
> DESC]](input=rel#18624:Subset#5.NONE.ANY([]).[0
> DESC],window#0=window(partition {} order by [0 DESC] rows between UNBOUNDED
> PRECEDING and CURRENT ROW aggs [ROW_NUMBER()])), rowcount=10.0, cumulative
> cost={inf} rel#18617:Subset#7.LOGICAL.ANY([]).[1 DESC], best=null,
> importance=0.9 rel#18620:DrillWindowRel.LOGICAL.ANY([]).[1
> DESC](input=rel#18625:Subset#5.LOGICAL.ANY([]).[1
> DESC],window#0=window(partition {} order by [0 DESC] rows between UNBOUNDED
> PRECEDING and CURRENT ROW aggs [ROW_NUMBER()])), rowcount=10.0, cumulative
> cost={inf} Set#8, type: RecordType(BIGINT r, BIGINT cnt)
> rel#18614:Subset#8.NONE.ANY([]).[1 DESC], best=null, importance=0.9
> rel#18613:LogicalProject.NONE.ANY([]).[[1
> DESC]](input=rel#18612:Subset#7.NONE.ANY([]).[1 DESC],r=$1,cnt=$0),
> rowcount=10.0, cumulative cost={inf} rel#18615:Subset#8.LOGICAL.ANY([]).[1
> DESC], best=null, importance=1.0
> rel#18616:AbstractConverter.LOGICAL.ANY([]).[1
> DESC](input=rel#18614:Subset#8.NONE.ANY([]).[1
> DESC],convention=LOGICAL,DrillDistributionTraitDef=ANY([]),sort=[1 DESC]),
> rowcount=10.0, cumulative cost={inf}
> rel#18618:DrillProjectRel.LOGICAL.ANY([]).[[1
> DESC]](input=rel#18617:Subset#7.LOGICAL.ANY([]).[1 DESC],r=$1,cnt=$0),
> rowcount=10.0, cumulative cost={inf} Set#9, type: RecordType(ANY columns)
> rel#18642:Subset#9.LOGICAL.ANY([]).[], best=rel#18640,
> importance=0.05314410000000001
> rel#18640:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv],groupscan=EasyGroupScan
> [selectionRoot=maprfs:/mapr/61-demo/flights, numFiles=12,
> columns=[`columns`[5]],
> files=[maprfs:/mapr/61-demo/flights/flights-2018-01.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-02.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-03.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-04.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-05.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-06.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-07.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-08.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-09.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-10.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-11.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-12.csv]]), rowcount=8370632.0,
> cumulative cost={8370632.0 rows, 8370632.0 cpu, 0.0 io, 0.0 network, 0.0
> memory} Set#10, type: RecordType(ANY columns)
> rel#18648:Subset#10.LOGICAL.ANY([]).[], best=rel#18646,
> importance=0.007410233661971832
> rel#18646:DrillScanRel.LOGICAL.ANY([]).[](table=[dfs, flt,
> flights-2018-*.csv],groupscan=EasyGroupScan
> [selectionRoot=maprfs:/mapr/61-demo/flights, numFiles=12,
> columns=[`columns`[0], `columns`[1], `columns`[2], `columns`[3],
> `columns`[4], `columns`[5], `columns`[6], `columns`[7], `columns`[8],
> `columns`[9], `columns`[10], `columns`[11], `columns`[12], `columns`[13],
> `columns`[14], `columns`[15], `columns`[16]],
> files=[maprfs:/mapr/61-demo/flights/flights-2018-01.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-02.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-03.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-04.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-05.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-06.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-07.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-08.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-09.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-10.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-11.csv,
> maprfs:/mapr/61-demo/flights/flights-2018-12.csv]]), rowcount=8370632.0,
> cumulative cost={8370632.0 rows, 8370632.0 cpu, 0.0 io, 0.0 network, 0.0
> memory} [Error Id: e05bca25-7110-47aa-b872-60aa1b2fdc34 on
> mdn-1.mdn.tdunning-dsr-demo-z6io48.svc.cluster.local:31010]. ... 21 more
>

Reply via email to