[
https://issues.apache.org/jira/browse/CALCITE-2592?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Vladimir Sitnikov updated CALCITE-2592:
---------------------------------------
Description:
I have added a test case
{{org.apache.calcite.plan.volcano.VolcanoPlannerTest#testMergeJoin}}
The test fails as follows:
{noformat}org.apache.calcite.plan.RelOptPlanner$CannotPlanException: There are
not enough rules to produce a node with desired properties:
convention=ENUMERABLE, sort=[].
Missing conversion is LogicalValues[convention: NONE -> ENUMERABLE, sort: [1]
-> [0]]
There is 1 empty subset: rel#9:Subset#0.ENUMERABLE.[0], the relevant part of
the original plan is as follows
0:LogicalValues(tuples=[[{ '2', 'a' }, { '1', 'b' }]])
Root: rel#7:Subset#2.ENUMERABLE.[]
Original rel:
LogicalJoin(subset=[rel#7:Subset#2.ENUMERABLE.[]], condition=[=($0, $2)],
joinType=[inner]): rowcount = 1.0, cumulative cost = {1.0 rows, 0.0 cpu, 0.0
io}, id = 5
LogicalValues(subset=[rel#3:Subset#0.NONE.[1]], tuples=[[{ '2', 'a' }, { '1',
'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, id = 0
LogicalValues(subset=[rel#4:Subset#1.NONE.[]], tuples=[[{ '1', 'x' }, { '2',
'y' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, id = 1
Sets:
Set#0, type: RecordType(CHAR(1) id, CHAR(1) name)
rel#3:Subset#0.NONE.[1], best=null, importance=0.81
rel#0:LogicalValues.NONE.[1](type=RecordType(CHAR(1) id,
CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }]), rowcount=2.0, cumulative
cost={inf}
rel#9:Subset#0.ENUMERABLE.[0], best=null, importance=0.9
rel#24:Subset#0.ENUMERABLE.[1], best=rel#23, importance=0.45
rel#23:EnumerableValues.ENUMERABLE.[1](type=RecordType(CHAR(1)
id, CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }]), rowcount=2.0,
cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
Set#1, type: RecordType(CHAR(1) id, CHAR(1) name)
rel#4:Subset#1.NONE.[], best=null, importance=0.81
rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(CHAR(1)
id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }]), rowcount=2.0,
cumulative cost={inf}
rel#10:Subset#1.ENUMERABLE.[0], best=rel#21, importance=0.9
rel#21:EnumerableValues.ENUMERABLE.[[0, 1],
[1]](type=RecordType(CHAR(1) id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y'
}]), rowcount=2.0, cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
rel#22:Subset#1.ENUMERABLE.[], best=rel#21, importance=0.45
rel#21:EnumerableValues.ENUMERABLE.[[0, 1],
[1]](type=RecordType(CHAR(1) id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y'
}]), rowcount=2.0, cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
Set#2, type: RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0, CHAR(1) name0)
rel#6:Subset#2.NONE.[], best=null, importance=0.9
rel#5:LogicalJoin.NONE.[](left=RelSubset#3,right=RelSubset#4,condition==($0,
$2),joinType=inner), rowcount=1.0, cumulative cost={inf}
rel#15:LogicalProject.NONE.[](input=RelSubset#14,id=$2,name=$3,id0=$0,name0=$1),
rowcount=1.0, cumulative cost={inf}
rel#7:Subset#2.ENUMERABLE.[], best=null, importance=1.0
rel#8:AbstractConverter.ENUMERABLE.[](input=RelSubset#6,convention=ENUMERABLE,sort=[]),
rowcount=1.0, cumulative cost={inf}
rel#11:EnumerableMergeJoin.ENUMERABLE.[[0],
[2]](left=RelSubset#9,right=RelSubset#10,condition==($0, $2),joinType=inner),
rowcount=1.0, cumulative cost={inf}
Set#3, type: RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0, CHAR(1) name0)
rel#14:Subset#3.NONE.[], best=null, importance=0.81
rel#12:LogicalJoin.NONE.[](left=RelSubset#4,right=RelSubset#3,condition==($2,
$0),joinType=inner), rowcount=1.0, cumulative cost={inf}
rel#18:LogicalProject.NONE.[](input=RelSubset#6,id=$2,name=$3,id0=$0,name0=$1),
rowcount=1.0, cumulative cost={inf}
rel#20:Subset#3.ENUMERABLE.[], best=null, importance=0.405
rel#19:EnumerableMergeJoin.ENUMERABLE.[[0],
[2]](left=RelSubset#10,right=RelSubset#9,condition==($0, $2),joinType=inner),
rowcount=1.0, cumulative cost={inf}
Graphviz:
digraph G {
root [style=filled,label="Root"];
subgraph cluster0{
label="Set 0 RecordType(CHAR(1) id, CHAR(1) name)";
rel0 [label="rel#0:LogicalValues(type=RecordType(CHAR(1) id,
CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }])\nrows=2.0,
cost={inf}",shape=box]
rel23 [label="rel#23:EnumerableValues(type=RecordType(CHAR(1)
id, CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }])\nrows=2.0, cost={2.0
rows, 1.0 cpu, 0.0 io}",color=blue,shape=box]
subset3 [label="rel#3:Subset#0.NONE.[1]"]
subset9 [label="rel#9:Subset#0.ENUMERABLE.[0]",color=red]
subset24 [label="rel#24:Subset#0.ENUMERABLE.[1]"]
}
subgraph cluster1{
label="Set 1 RecordType(CHAR(1) id, CHAR(1) name)";
rel1 [label="rel#1:LogicalValues(type=RecordType(CHAR(1) id,
CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }])\nrows=2.0,
cost={inf}",shape=box]
rel21 [label="rel#21:EnumerableValues(type=RecordType(CHAR(1)
id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }])\nrows=2.0, cost={2.0
rows, 1.0 cpu, 0.0 io}",color=blue,shape=box]
subset4 [label="rel#4:Subset#1.NONE.[]"]
subset10 [label="rel#10:Subset#1.ENUMERABLE.[0]"]
subset22 [label="rel#22:Subset#1.ENUMERABLE.[]"]
subset22 -> subset10; }
subgraph cluster2{
label="Set 2 RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0,
CHAR(1) name0)";
rel5
[label="rel#5:LogicalJoin(left=RelSubset#3,right=RelSubset#4,condition==($0,
$2),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
rel8
[label="rel#8:AbstractConverter(input=RelSubset#6,convention=ENUMERABLE,sort=[])\nrows=1.0,
cost={inf}",shape=box]
rel11
[label="rel#11:EnumerableMergeJoin(left=RelSubset#9,right=RelSubset#10,condition==($0,
$2),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
rel15
[label="rel#15:LogicalProject(input=RelSubset#14,id=$2,name=$3,id0=$0,name0=$1)\nrows=1.0,
cost={inf}",shape=box]
subset6 [label="rel#6:Subset#2.NONE.[]"]
subset7 [label="rel#7:Subset#2.ENUMERABLE.[]"]
}
subgraph cluster3{
label="Set 3 RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0,
CHAR(1) name0)";
rel12
[label="rel#12:LogicalJoin(left=RelSubset#4,right=RelSubset#3,condition==($2,
$0),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
rel18
[label="rel#18:LogicalProject(input=RelSubset#6,id=$2,name=$3,id0=$0,name0=$1)\nrows=1.0,
cost={inf}",shape=box]
rel19
[label="rel#19:EnumerableMergeJoin(left=RelSubset#10,right=RelSubset#9,condition==($0,
$2),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
subset14 [label="rel#14:Subset#3.NONE.[]"]
subset20 [label="rel#20:Subset#3.ENUMERABLE.[]"]
}
root -> subset7;
subset3 -> rel0;
subset24 -> rel23[color=blue];
subset4 -> rel1;
subset22 -> rel21[color=blue];
subset6 -> rel5; rel5 -> subset3[label="0"]; rel5 -> subset4[label="1"];
subset7 -> rel8; rel8 -> subset6;
subset7 -> rel11; rel11 -> subset9[label="0"]; rel11 ->
subset10[label="1"];
subset6 -> rel15; rel15 -> subset14;
subset14 -> rel12; rel12 -> subset4[label="0"]; rel12 ->
subset3[label="1"];
subset14 -> rel18; rel18 -> subset6;
subset20 -> rel19; rel19 -> subset10[label="0"]; rel19 ->
subset9[label="1"];
}
at
org.apache.calcite.plan.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:587)
at
org.apache.calcite.plan.volcano.RelSubset.buildCheapestPlan(RelSubset.java:304)
at
org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:655){noformat}
was:
I have added a test case in
https://git-wip-us.apache.org/repos/asf?p=calcite.git;a=commit;h=87c4b735b983883d806799e18b21471f9f5ce7be
The test fails as follows:
{noformat}org.apache.calcite.plan.RelOptPlanner$CannotPlanException: Node
[rel#7:Subset#2.ENUMERABLE.[]] could not be implemented; planner state:
Root: rel#7:Subset#2.ENUMERABLE.[]
Original rel:
LogicalJoin(subset=[rel#7:Subset#2.ENUMERABLE.[]], condition=[=($0, $2)],
joinType=[inner]): rowcount = 1.0, cumulative cost = {1.0 rows, 0.0 cpu, 0.0
io}, id = 5
LogicalValues(subset=[rel#3:Subset#0.NONE.[1]], tuples=[[{ '2', 'a' }, { '1',
'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, id = 0
LogicalValues(subset=[rel#4:Subset#1.NONE.[]], tuples=[[{ '1', 'x' }, { '2',
'y' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io}, id = 1
Sets:
Set#0, type: RecordType(CHAR(1) id, CHAR(1) name)
rel#3:Subset#0.NONE.[1], best=null, importance=0.81
rel#0:LogicalValues.NONE.[[1]](type=RecordType(CHAR(1) id,
CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }]), rowcount=2.0, cumulative
cost={inf}
rel#9:Subset#0.ENUMERABLE.[0], best=null, importance=0.9
rel#30:Subset#0.ENUMERABLE.[1], best=rel#29, importance=0.45
rel#29:EnumerableValues.ENUMERABLE.[[1]](type=RecordType(CHAR(1) id, CHAR(1)
name),tuples=[{ '2', 'a' }, { '1', 'b' }]), rowcount=2.0, cumulative cost={2.0
rows, 1.0 cpu, 0.0 io}
Set#1, type: RecordType(CHAR(1) id, CHAR(1) name)
rel#4:Subset#1.NONE.[], best=null, importance=0.81
rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(CHAR(1)
id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }]), rowcount=2.0,
cumulative cost={inf}
rel#10:Subset#1.ENUMERABLE.[0], best=rel#27, importance=0.9
rel#27:EnumerableValues.ENUMERABLE.[[0, 1],
[1]](type=RecordType(CHAR(1) id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y'
}]), rowcount=2.0, cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
rel#28:Subset#1.ENUMERABLE.[], best=rel#27, importance=0.45
rel#27:EnumerableValues.ENUMERABLE.[[0, 1],
[1]](type=RecordType(CHAR(1) id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y'
}]), rowcount=2.0, cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
Set#2, type: RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0, CHAR(1) name0)
rel#6:Subset#2.NONE.[], best=null, importance=0.9
rel#5:LogicalJoin.NONE.[](left=rel#3:Subset#0.NONE.[1],right=rel#4:Subset#1.NONE.[],condition==($0,
$2),joinType=inner), rowcount=1.0, cumulative cost={inf}
rel#15:LogicalProject.NONE.[](input=rel#14:Subset#3.NONE.[],id=$2,name=$3,id0=$0,name0=$1),
rowcount=1.0, cumulative cost={inf}
rel#7:Subset#2.ENUMERABLE.[], best=null, importance=1.0
rel#8:AbstractConverter.ENUMERABLE.[](input=rel#6:Subset#2.NONE.[],convention=ENUMERABLE,sort=[]),
rowcount=1.0, cumulative cost={inf}
rel#11:EnumerableMergeJoin.ENUMERABLE.[[0],
[2]](left=rel#9:Subset#0.ENUMERABLE.[0],right=rel#10:Subset#1.ENUMERABLE.[0],condition==($0,
$2),joinType=inner), rowcount=1.0, cumulative cost={inf}
Set#3, type: RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0, CHAR(1) name0)
rel#14:Subset#3.NONE.[], best=null, importance=0.81
rel#12:LogicalJoin.NONE.[](left=rel#4:Subset#1.NONE.[],right=rel#3:Subset#0.NONE.[1],condition==($2,
$0),joinType=inner), rowcount=1.0, cumulative cost={inf}
rel#18:LogicalProject.NONE.[](input=rel#6:Subset#2.NONE.[],id=$2,name=$3,id0=$0,name0=$1),
rowcount=1.0, cumulative cost={inf}
rel#26:Subset#3.ENUMERABLE.[], best=null, importance=0.405
rel#25:EnumerableMergeJoin.ENUMERABLE.[[0],
[2]](left=rel#10:Subset#1.ENUMERABLE.[0],right=rel#9:Subset#0.ENUMERABLE.[0],condition==($0,
$2),joinType=inner), rowcount=1.0, cumulative cost={inf}
at
org.apache.calcite.plan.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:437)
at
org.apache.calcite.plan.volcano.RelSubset.buildCheapestPlan(RelSubset.java:296){noformat}
> EnumerableMergeJoin is never taken
> ----------------------------------
>
> Key: CALCITE-2592
> URL: https://issues.apache.org/jira/browse/CALCITE-2592
> Project: Calcite
> Issue Type: Bug
> Components: core
> Affects Versions: 1.17.0
> Reporter: Vladimir Sitnikov
> Priority: Major
>
> I have added a test case
> {{org.apache.calcite.plan.volcano.VolcanoPlannerTest#testMergeJoin}}
> The test fails as follows:
> {noformat}org.apache.calcite.plan.RelOptPlanner$CannotPlanException: There
> are not enough rules to produce a node with desired properties:
> convention=ENUMERABLE, sort=[].
> Missing conversion is LogicalValues[convention: NONE -> ENUMERABLE, sort: [1]
> -> [0]]
> There is 1 empty subset: rel#9:Subset#0.ENUMERABLE.[0], the relevant part of
> the original plan is as follows
> 0:LogicalValues(tuples=[[{ '2', 'a' }, { '1', 'b' }]])
> Root: rel#7:Subset#2.ENUMERABLE.[]
> Original rel:
> LogicalJoin(subset=[rel#7:Subset#2.ENUMERABLE.[]], condition=[=($0, $2)],
> joinType=[inner]): rowcount = 1.0, cumulative cost = {1.0 rows, 0.0 cpu, 0.0
> io}, id = 5
> LogicalValues(subset=[rel#3:Subset#0.NONE.[1]], tuples=[[{ '2', 'a' }, {
> '1', 'b' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io},
> id = 0
> LogicalValues(subset=[rel#4:Subset#1.NONE.[]], tuples=[[{ '1', 'x' }, {
> '2', 'y' }]]): rowcount = 2.0, cumulative cost = {2.0 rows, 1.0 cpu, 0.0 io},
> id = 1
> Sets:
> Set#0, type: RecordType(CHAR(1) id, CHAR(1) name)
> rel#3:Subset#0.NONE.[1], best=null, importance=0.81
> rel#0:LogicalValues.NONE.[1](type=RecordType(CHAR(1) id,
> CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }]), rowcount=2.0, cumulative
> cost={inf}
> rel#9:Subset#0.ENUMERABLE.[0], best=null, importance=0.9
> rel#24:Subset#0.ENUMERABLE.[1], best=rel#23, importance=0.45
> rel#23:EnumerableValues.ENUMERABLE.[1](type=RecordType(CHAR(1)
> id, CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }]), rowcount=2.0,
> cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
> Set#1, type: RecordType(CHAR(1) id, CHAR(1) name)
> rel#4:Subset#1.NONE.[], best=null, importance=0.81
> rel#1:LogicalValues.NONE.[[0, 1], [1]](type=RecordType(CHAR(1)
> id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }]), rowcount=2.0,
> cumulative cost={inf}
> rel#10:Subset#1.ENUMERABLE.[0], best=rel#21, importance=0.9
> rel#21:EnumerableValues.ENUMERABLE.[[0, 1],
> [1]](type=RecordType(CHAR(1) id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2',
> 'y' }]), rowcount=2.0, cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
> rel#22:Subset#1.ENUMERABLE.[], best=rel#21, importance=0.45
> rel#21:EnumerableValues.ENUMERABLE.[[0, 1],
> [1]](type=RecordType(CHAR(1) id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2',
> 'y' }]), rowcount=2.0, cumulative cost={2.0 rows, 1.0 cpu, 0.0 io}
> Set#2, type: RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0, CHAR(1) name0)
> rel#6:Subset#2.NONE.[], best=null, importance=0.9
>
> rel#5:LogicalJoin.NONE.[](left=RelSubset#3,right=RelSubset#4,condition==($0,
> $2),joinType=inner), rowcount=1.0, cumulative cost={inf}
>
> rel#15:LogicalProject.NONE.[](input=RelSubset#14,id=$2,name=$3,id0=$0,name0=$1),
> rowcount=1.0, cumulative cost={inf}
> rel#7:Subset#2.ENUMERABLE.[], best=null, importance=1.0
>
> rel#8:AbstractConverter.ENUMERABLE.[](input=RelSubset#6,convention=ENUMERABLE,sort=[]),
> rowcount=1.0, cumulative cost={inf}
> rel#11:EnumerableMergeJoin.ENUMERABLE.[[0],
> [2]](left=RelSubset#9,right=RelSubset#10,condition==($0, $2),joinType=inner),
> rowcount=1.0, cumulative cost={inf}
> Set#3, type: RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0, CHAR(1) name0)
> rel#14:Subset#3.NONE.[], best=null, importance=0.81
>
> rel#12:LogicalJoin.NONE.[](left=RelSubset#4,right=RelSubset#3,condition==($2,
> $0),joinType=inner), rowcount=1.0, cumulative cost={inf}
>
> rel#18:LogicalProject.NONE.[](input=RelSubset#6,id=$2,name=$3,id0=$0,name0=$1),
> rowcount=1.0, cumulative cost={inf}
> rel#20:Subset#3.ENUMERABLE.[], best=null, importance=0.405
> rel#19:EnumerableMergeJoin.ENUMERABLE.[[0],
> [2]](left=RelSubset#10,right=RelSubset#9,condition==($0, $2),joinType=inner),
> rowcount=1.0, cumulative cost={inf}
> Graphviz:
> digraph G {
> root [style=filled,label="Root"];
> subgraph cluster0{
> label="Set 0 RecordType(CHAR(1) id, CHAR(1) name)";
> rel0 [label="rel#0:LogicalValues(type=RecordType(CHAR(1) id,
> CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }])\nrows=2.0,
> cost={inf}",shape=box]
> rel23 [label="rel#23:EnumerableValues(type=RecordType(CHAR(1)
> id, CHAR(1) name),tuples=[{ '2', 'a' }, { '1', 'b' }])\nrows=2.0, cost={2.0
> rows, 1.0 cpu, 0.0 io}",color=blue,shape=box]
> subset3 [label="rel#3:Subset#0.NONE.[1]"]
> subset9 [label="rel#9:Subset#0.ENUMERABLE.[0]",color=red]
> subset24 [label="rel#24:Subset#0.ENUMERABLE.[1]"]
> }
> subgraph cluster1{
> label="Set 1 RecordType(CHAR(1) id, CHAR(1) name)";
> rel1 [label="rel#1:LogicalValues(type=RecordType(CHAR(1) id,
> CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }])\nrows=2.0,
> cost={inf}",shape=box]
> rel21 [label="rel#21:EnumerableValues(type=RecordType(CHAR(1)
> id, CHAR(1) name),tuples=[{ '1', 'x' }, { '2', 'y' }])\nrows=2.0, cost={2.0
> rows, 1.0 cpu, 0.0 io}",color=blue,shape=box]
> subset4 [label="rel#4:Subset#1.NONE.[]"]
> subset10 [label="rel#10:Subset#1.ENUMERABLE.[0]"]
> subset22 [label="rel#22:Subset#1.ENUMERABLE.[]"]
> subset22 -> subset10; }
> subgraph cluster2{
> label="Set 2 RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0,
> CHAR(1) name0)";
> rel5
> [label="rel#5:LogicalJoin(left=RelSubset#3,right=RelSubset#4,condition==($0,
> $2),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
> rel8
> [label="rel#8:AbstractConverter(input=RelSubset#6,convention=ENUMERABLE,sort=[])\nrows=1.0,
> cost={inf}",shape=box]
> rel11
> [label="rel#11:EnumerableMergeJoin(left=RelSubset#9,right=RelSubset#10,condition==($0,
> $2),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
> rel15
> [label="rel#15:LogicalProject(input=RelSubset#14,id=$2,name=$3,id0=$0,name0=$1)\nrows=1.0,
> cost={inf}",shape=box]
> subset6 [label="rel#6:Subset#2.NONE.[]"]
> subset7 [label="rel#7:Subset#2.ENUMERABLE.[]"]
> }
> subgraph cluster3{
> label="Set 3 RecordType(CHAR(1) id, CHAR(1) name, CHAR(1) id0,
> CHAR(1) name0)";
> rel12
> [label="rel#12:LogicalJoin(left=RelSubset#4,right=RelSubset#3,condition==($2,
> $0),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
> rel18
> [label="rel#18:LogicalProject(input=RelSubset#6,id=$2,name=$3,id0=$0,name0=$1)\nrows=1.0,
> cost={inf}",shape=box]
> rel19
> [label="rel#19:EnumerableMergeJoin(left=RelSubset#10,right=RelSubset#9,condition==($0,
> $2),joinType=inner)\nrows=1.0, cost={inf}",shape=box]
> subset14 [label="rel#14:Subset#3.NONE.[]"]
> subset20 [label="rel#20:Subset#3.ENUMERABLE.[]"]
> }
> root -> subset7;
> subset3 -> rel0;
> subset24 -> rel23[color=blue];
> subset4 -> rel1;
> subset22 -> rel21[color=blue];
> subset6 -> rel5; rel5 -> subset3[label="0"]; rel5 -> subset4[label="1"];
> subset7 -> rel8; rel8 -> subset6;
> subset7 -> rel11; rel11 -> subset9[label="0"]; rel11 ->
> subset10[label="1"];
> subset6 -> rel15; rel15 -> subset14;
> subset14 -> rel12; rel12 -> subset4[label="0"]; rel12 ->
> subset3[label="1"];
> subset14 -> rel18; rel18 -> subset6;
> subset20 -> rel19; rel19 -> subset10[label="0"]; rel19 ->
> subset9[label="1"];
> }
> at
> org.apache.calcite.plan.volcano.RelSubset$CheapestPlanReplacer.visit(RelSubset.java:587)
> at
> org.apache.calcite.plan.volcano.RelSubset.buildCheapestPlan(RelSubset.java:304)
> at
> org.apache.calcite.plan.volcano.VolcanoPlanner.findBestExp(VolcanoPlanner.java:655){noformat}
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