[CALCITE-2166] Cumulative cost of RelSubset.best RelNode is increased after calling RelSubset.propagateCostImprovements() for input RelNodes

• Type: Bug
• Status: Reopened
• Priority: Critical
• Resolution: Unresolved
• Affects Version/s: 1.15.0
• Component/s: core
• Labels: pull-request-available
• Assignee: Unassigned
• Reporter: Vova Vysotskyi
• Created: 05/Feb/18 17:00
• Updated: 28/Feb/24 06:03

Description

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:

          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);
            }
          }

into VolcanoPlanner.validate() method (line 907).
List of unit tests which fail with this check:

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}

For the test MaterializationTest.testJoinMaterializationUKFK9 initial best plan was:

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

Its cumulative cost is {221.5 rows, 123.75 cpu, 0.0 io}

After applying some rules it became:

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

Its cumulative cost is {233.0 rows, 148.0 cpu, 0.0 io}.

Issue Links

• blocks: CALCITE-2018 Queries failed with AssertionError: rel has lower cost than best cost of subset
• links to: GitHub Pull Request #1440