tartarus created FLINK-21923:
-------------------------------- Summary: SplitAggregateRule will be abnormal, when the sum/count and avg in SQL at the same time Key: FLINK-21923 URL: https://issues.apache.org/jira/browse/FLINK-21923 Project: Flink Issue Type: Bug Components: Table SQL / Planner Affects Versions: 1.10.0 Reporter: tartarus Fix For: 1.13.0 SplitAggregateRule optimizes one-layer aggregation to two-layer aggregation to improve computing performance under data skew. In the partial phase, avg will be translated into count and sum. If count already exists in the original SQL at this time, the engine will remove the duplicate count, and then add Project to calculate and restore the optimized count result value. {code:java} relBuilder.aggregate( relBuilder.groupKey(fullGroupSet, ImmutableList.of[ImmutableBitSet](fullGroupSet)), newPartialAggCalls) relBuilder.peek().asInstanceOf[FlinkLogicalAggregate] .setPartialFinalType(PartialFinalType.PARTIAL) {code} so `relBuilder.peek()` will return `FlinkLogicalCalc` not `FlinkLogicalAggregate`, then will throw exception like {code:java} java.lang.ClassCastException: org.apache.flink.table.planner.plan.nodes.logical.FlinkLogicalCalc cannot be cast to org.apache.flink.table.planner.plan.nodes.logical.FlinkLogicalAggregate at org.apache.flink.table.planner.plan.rules.logical.SplitAggregateRule.onMatch(SplitAggregateRule.scala:286) at org.apache.calcite.plan.AbstractRelOptPlanner.fireRule(AbstractRelOptPlanner.java:333) at org.apache.calcite.plan.hep.HepPlanner.applyRule(HepPlanner.java:542) at org.apache.calcite.plan.hep.HepPlanner.applyRules(HepPlanner.java:407) at org.apache.calcite.plan.hep.HepPlanner.executeInstruction(HepPlanner.java:243) at org.apache.calcite.plan.hep.HepInstruction$RuleInstance.execute(HepInstruction.java:127) at org.apache.calcite.plan.hep.HepPlanner.executeProgram(HepPlanner.java:202) at org.apache.calcite.plan.hep.HepPlanner.findBestExp(HepPlanner.java:189) at org.apache.flink.table.planner.plan.optimize.program.FlinkHepProgram.optimize(FlinkHepProgram.scala:69) at org.apache.flink.table.planner.plan.optimize.program.FlinkHepRuleSetProgram.optimize(FlinkHepRuleSetProgram.scala:87) at org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram$$anonfun$optimize$1.apply(FlinkChainedProgram.scala:62) at org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram$$anonfun$optimize$1.apply(FlinkChainedProgram.scala:58) at scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157) at scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157) at scala.collection.Iterator$class.foreach(Iterator.scala:891) at scala.collection.AbstractIterator.foreach(Iterator.scala:1334) at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) at scala.collection.AbstractIterable.foreach(Iterable.scala:54) at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157) at scala.collection.AbstractTraversable.foldLeft(Traversable.scala:104) at org.apache.flink.table.planner.plan.optimize.program.FlinkChainedProgram.optimize(FlinkChainedProgram.scala:57) at org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.optimizeTree(StreamCommonSubGraphBasedOptimizer.scala:163) at org.apache.flink.table.planner.plan.optimize.StreamCommonSubGraphBasedOptimizer.doOptimize(StreamCommonSubGraphBasedOptimizer.scala:79) at org.apache.flink.table.planner.plan.optimize.CommonSubGraphBasedOptimizer.optimize(CommonSubGraphBasedOptimizer.scala:77) at org.apache.flink.table.planner.delegation.PlannerBase.optimize(PlannerBase.scala:284) at org.apache.flink.table.planner.utils.TableTestUtilBase.assertPlanEquals(TableTestBase.scala:889) at org.apache.flink.table.planner.utils.TableTestUtilBase.doVerifyPlan(TableTestBase.scala:780) at org.apache.flink.table.planner.utils.TableTestUtilBase.verifyPlan(TableTestBase.scala:283) at org.apache.flink.table.planner.plan.rules.logical.SplitAggregateRuleTest.testAggWithFilterClause2(SplitAggregateRuleTest.scala:205) {code} We can reproduce stably and pass the test cases in `SplitAggregateRuleTest` {code:java} @Test def testAggBothWithAvgAndCount(): Unit = { util.tableEnv.getConfig.getConfiguration.setBoolean( OptimizerConfigOptions.TABLE_OPTIMIZER_DISTINCT_AGG_SPLIT_ENABLED, true) val sqlQuery = s""" |SELECT | COUNT(DISTINCT b) FILTER (WHERE NOT b = 2), | SUM(b) FILTER (WHERE NOT b = 5), | count(b), | AVG(b), | sum(b) |FROM MyTable |GROUP BY a """.stripMargin util.verifyPlan(sqlQuery) } {code} -- This message was sent by Atlassian Jira (v8.3.4#803005) |
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