Volodymyr Vysotskyi created CALCITE-2166:
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Summary: Cumulative cost of RelSubset.best RelNode is increased
after calling RelSubset.propagateCostImprovements() for input RelNodes
Key: CALCITE-2166
URL: https://issues.apache.org/jira/browse/CALCITE-2166
Project: Calcite
Issue Type: Bug
Components: core
Affects Versions: 1.15.0
Reporter: Volodymyr Vysotskyi
Assignee: Julian Hyde
After calling {{RelSubset.propagateCostImprovements()}} cumulative cost of
{{RelSubset.best}} {{RelNode}} may be increased due to the increase of the
non-cumulative cost caused by changing of input best {{RelNode}}.
To observe this issue, add this code:
{code:java}
if (subset.best != null) {
RelOptCost bestCost = getCost(subset.best,
RelMetadataQuery.instance());
if (!subset.bestCost.equals(bestCost)) {
throw new AssertionError(
"relSubset [" + subset.getDescription()
+ "] has wrong best cost "
+ subset.bestCost + ". Correct cost is " + bestCost);
}
}
{code}
into {{VolcanoPlanner.validate()}} method (line 907).
List of unit tests which fail with this check:
{noformat}
Failed tests:
MaterializationTest.testJoinMaterializationUKFK9:1823->checkMaterialize:198->checkMaterialize:205->checkThatMaterialize:233
relSubset [rel#226287:Subset#8.ENUMERABLE.[]] has wrong best cost {221.5 rows,
128.25 cpu, 0.0 io}. Correct cost is {233.0 rows, 178.0 cpu, 0.0 io}
ScannableTableTest.testPFPushDownProjectFilterAggregateNested:279 relSubset
[rel#12950:Subset#5.ENUMERABLE.[]] has wrong best cost {63.8 rows, 62.308 cpu,
0.0 io}. Correct cost is {70.4 rows, 60.404 cpu, 0.0 io}
ScannableTableTest.testPFTableRefusesFilterCooperative:221 relSubset
[rel#13382:Subset#2.ENUMERABLE.[]] has wrong best cost {81.0 rows, 181.01 cpu,
0.0 io}. Correct cost is {150.5 rows, 250.505 cpu, 0.0 io}
ScannableTableTest.testProjectableFilterableCooperative:148 relSubset
[rel#13611:Subset#2.ENUMERABLE.[]] has wrong best cost {81.0 rows, 181.01 cpu,
0.0 io}. Correct cost is {150.5 rows, 250.505 cpu, 0.0 io}
ScannableTableTest.testProjectableFilterableNonCooperative:165 relSubset
[rel#13754:Subset#2.ENUMERABLE.[]] has wrong best cost {81.0 rows, 181.01 cpu,
0.0 io}. Correct cost is {150.5 rows, 250.505 cpu, 0.0 io}
FrameworksTest.testUpdate:336->executeQuery:367 relSubset
[rel#22533:Subset#2.ENUMERABLE.any] has wrong best cost {19.5 rows, 37.75 cpu,
0.0 io}. Correct cost is {22.575 rows, 52.58 cpu, 0.0 io}
{noformat}
For the test {{MaterializationTest.testJoinMaterializationUKFK9}} initial best
plan was:
{noformat}
EnumerableProject(empid0=[$5], empid00=[$5], deptno0=[$7]): rowcount = 15.0,
cumulative cost = {15.0 rows, 45.0 cpu, 0.0 io}, id = 3989
EnumerableJoin(subset=[rel#3988:Subset#34.ENUMERABLE.[]], condition=[=($1,
$7)], joinType=[inner]): rowcount = 15.0, cumulative cost = {116.0 rows, 0.0
cpu, 0.0 io}, id = 4797
EnumerableFilter(subset=[rel#4274:Subset#47.ENUMERABLE.[0]],
condition=[=(CAST($2):VARCHAR CHARACTER SET "ISO-8859-1" COLLATE
"ISO-8859-1$en_US$primary", 'Bill')]): rowcount = 1.0, cumulative cost = {1.0
rows, 1.0 cpu, 0.0 io}, id = 16522
EnumerableTableScan(subset=[rel#158:Subset#11.ENUMERABLE.[0]],
table=[[hr, m0]]): rowcount = 1.0, cumulative cost = {0.0 rows, 1.0 cpu, 0.0
io}, id = 79
EnumerableTableScan(subset=[rel#115:Subset#5.ENUMERABLE.[]], table=[[hr,
depts]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0 cpu, 0.0 io},
id = 62
{noformat}
Its cumulative cost is \{221.5 rows, 123.75 cpu, 0.0 io}
After applying some rules it became:
{noformat}
EnumerableProject(empid0=[$3], empid00=[$3], deptno0=[$0]): rowcount = 2.25,
cumulative cost = {2.25 rows, 6.75 cpu, 0.0 io}, id = 4012
EnumerableFilter(subset=[rel#4007:Subset#41.ENUMERABLE.[]],
condition=[=(CAST($2):VARCHAR CHARACTER SET "ISO-8859-1" COLLATE
"ISO-8859-1$en_US$primary", 'Bill')]): rowcount = 2.25, cumulative cost = {2.25
rows, 15.0 cpu, 0.0 io}, id = 4811
EnumerableProject(subset=[rel#4203:Subset#61.ENUMERABLE.[]], deptno=[$7],
deptno0=[$1], name0=[$2], empid0=[$5]): rowcount = 15.0, cumulative cost =
{15.0 rows, 60.0 cpu, 0.0 io}, id = 4206
EnumerableJoin(subset=[rel#4204:Subset#52.ENUMERABLE.[]],
condition=[=($1, $7)], joinType=[inner]): rowcount = 15.0, cumulative cost =
{116.0 rows, 0.0 cpu, 0.0 io}, id = 4795
EnumerableTableScan(subset=[rel#158:Subset#11.ENUMERABLE.[0]],
table=[[hr, m0]]): rowcount = 1.0, cumulative cost = {0.0 rows, 1.0 cpu, 0.0
io}, id = 79
EnumerableTableScan(subset=[rel#115:Subset#5.ENUMERABLE.[]],
table=[[hr, depts]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0
cpu, 0.0 io}, id = 62
{noformat}
Its cumulative cost is {{{233.0 rows, 148.0 cpu, 0.0 io}}}.
The new plan does not contain {{EnumerableProject}} RelNode, therefore the
cumulative cost of the plan for some RelNodes becomes smaller, but since the
increase of row count caused an increase of non-cumulative cost, the cost of
best RelNode increased.
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