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Shawn Smith commented on SPARK-37222: ------------------------------------- Plan at the start of one iteration: {noformat} Project [id#2, _gen_alias_110#110L AS nested.n#28L] +- Join LeftAnti, (id#2 = id#18) :- Project [id#2, nested#3.n AS _gen_alias_110#110L] : +- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, deserialized, 1 replicas) : +- LocalTableScan <empty>, [id#2, nested#3] +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 replicas) +- LocalTableScan <empty>, [id#18] {noformat} After {{org.apache.spark.sql.catalyst.optimizer.PushDownLeftSemiAntiJoin}} (moved {{Join}} down) {noformat} Project [id#2, _gen_alias_110#110L AS nested.n#28L] +- Project [id#2, nested#3.n AS _gen_alias_110#110L] +- Join LeftAnti, (id#2 = id#18) :- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, deserialized, 1 replicas) : +- LocalTableScan <empty>, [id#2, nested#3] +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 replicas) +- LocalTableScan <empty>, [id#18] {noformat} After {{org.apache.spark.sql.catalyst.optimizer.ColumnPruning}} the plan looks the same but plan objects are different. After {{org.apache.spark.sql.catalyst.optimizer.CollapseProject}} (moved {{Join}} up, added {{Project [id18]}}) {noformat} Project [id#2, _gen_alias_111#111L AS nested.n#28L] +- Join LeftAnti, (id#2 = id#18) :- Project [id#2, nested#3.n AS _gen_alias_111#111L] : +- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, deserialized, 1 replicas) : +- LocalTableScan <empty>, [id#2, nested#3] +- Project [id#18] +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 replicas) +- LocalTableScan <empty>, [id#18] {noformat} After {{org.apache.spark.sql.catalyst.optimizer.FoldablePropagation}} the plan looks the same but plan objects are different. After {{org.apache.spark.sql.catalyst.optimizer.RemoveNoopOperators}} (removed {{Project [id18]}}) {noformat} Project [id#2, _gen_alias_111#111L AS nested.n#28L] +- Join LeftAnti, (id#2 = id#18) :- Project [id#2, nested#3.n AS _gen_alias_111#111L] : +- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, deserialized, 1 replicas) : +- LocalTableScan <empty>, [id#2, nested#3] +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 replicas) +- LocalTableScan <empty>, [id#18] {noformat} Plan at the end of one iteration: {noformat} Project [id#2, _gen_alias_112#112L AS nested.n#28L] +- Join LeftAnti, (id#2 = id#18) :- Project [id#2, nested#3.n AS _gen_alias_112#112L] : +- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, deserialized, 1 replicas) : +- LocalTableScan <empty>, [id#2, nested#3] +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 replicas) +- LocalTableScan <empty>, [id#18] {noformat} > Max iterations reached in Operator Optimization w/left_anti or left_semi join > and nested structures > --------------------------------------------------------------------------------------------------- > > Key: SPARK-37222 > URL: https://issues.apache.org/jira/browse/SPARK-37222 > Project: Spark > Issue Type: Bug > Components: Optimizer > Affects Versions: 3.1.2, 3.2.0 > Environment: I've reproduced the error on Spark 3.1.2, 3.2.0, and > with the current branch-3.2 HEAD (git commit 966c90c0b5) as of November 5, > 2021. > The problem does not occur with Spark 3.0.1. > > Reporter: Shawn Smith > Priority: Major > > The query optimizer never reaches a fixed point when optimizing the query > below. This manifests as a warning: > > WARN: Max iterations (100) reached for batch Operator Optimization before > > Inferring Filters, please set 'spark.sql.optimizer.maxIterations' to a > > larger value. > But the suggested fix won't help. The actual problem is that the optimizer > fails to make progress on each iteration and gets stuck in a loop. > In practice, Spark logs a warning but continues on and appears to execute the > query successfully, albeit perhaps sub-optimally. > To reproduce, paste the following into the Spark shell. With Spark 3.1.2 and > 3.2.0 but not 3.0.1 it will throw an exception: > {noformat} > case class Nested(b: Boolean, n: Long) > case class Table(id: String, nested: Nested) > case class Identifier(id: String) > locally { > System.setProperty("spark.testing", "true") // Fail instead of logging a > warning > val df = List.empty[Table].toDS.cache() > val ids = List.empty[Identifier].toDS.cache() > df.join(ids, Seq("id"), "left_anti") // also fails with "left_semi" > .select('id, 'nested("n")) > .explain() > } > {noformat} > Looking at the query plan as the optimizer iterates in > {{RuleExecutor.execute()}}, here's an example of the plan after 49 iterations: > {noformat} > Project [id#2, _gen_alias_108#108L AS nested.n#28L] > +- Join LeftAnti, (id#2 = id#18) > :- Project [id#2, nested#3.n AS _gen_alias_108#108L] > : +- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, > deserialized, 1 replicas) > : +- LocalTableScan <empty>, [id#2, nested#3] > +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 > replicas) > +- LocalTableScan <empty>, [id#18] > {noformat} > And here's the plan after one more iteration. You can see that all that has > changed is new aliases for the column in the nested column: > "{{_gen_alias_108#108L}}" to "{{_gen_alias_109#109L}}". > {noformat} > Project [id#2, _gen_alias_109#109L AS nested.n#28L] > +- Join LeftAnti, (id#2 = id#18) > :- Project [id#2, nested#3.n AS _gen_alias_109#109L] > : +- InMemoryRelation [id#2, nested#3], StorageLevel(disk, memory, > deserialized, 1 replicas) > : +- LocalTableScan <empty>, [id#2, nested#3] > +- InMemoryRelation [id#18], StorageLevel(disk, memory, deserialized, 1 > replicas) > +- LocalTableScan <empty>, [id#18] > {noformat} > The optimizer continues looping and tweaking the alias until it hits the max > iteration count and bails out. > Here's an example that includes a stack trace: > {noformat} > $ bin/spark-shell > Welcome to > ____ __ > / __/__ ___ _____/ /__ > _\ \/ _ \/ _ `/ __/ '_/ > /___/ .__/\_,_/_/ /_/\_\ version 3.2.0 > /_/ > Using Scala version 2.12.15 (OpenJDK 64-Bit Server VM, Java 11.0.12) > Type in expressions to have them evaluated. > Type :help for more information. > scala> :paste > // Entering paste mode (ctrl-D to finish) > case class Nested(b: Boolean, n: Long) > case class Table(id: String, nested: Nested) > case class Identifier(id: String) > locally { > System.setProperty("spark.testing", "true") // Fail instead of logging a > warning > val df = List.empty[Table].toDS.cache() > val ids = List.empty[Identifier].toDS.cache() > df.join(ids, Seq("id"), "left_anti") // also fails with "left_semi" > .select('id, 'nested("n")) > .explain() > } > // Exiting paste mode, now interpreting. > java.lang.RuntimeException: Max iterations (100) reached for batch Operator > Optimization before Inferring Filters, please set > 'spark.sql.optimizer.maxIterations' to a larger value. > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:246) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:200) > at scala.collection.immutable.List.foreach(List.scala:431) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:200) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:179) > at > org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:179) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:138) > at > org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:196) > at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) > at > org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:196) > at > org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:134) > at > org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:130) > at > org.apache.spark.sql.execution.QueryExecution.assertOptimized(QueryExecution.scala:148) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$executedPlan$1(QueryExecution.scala:166) > at > org.apache.spark.sql.execution.QueryExecution.withCteMap(QueryExecution.scala:73) > at > org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:163) > at > org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:163) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$simpleString$2(QueryExecution.scala:220) > at > org.apache.spark.sql.catalyst.plans.QueryPlan$.append(QueryPlan.scala:600) > at > org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:220) > at > org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:247) > at > org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:228) > at org.apache.spark.sql.Dataset.$anonfun$explain$1(Dataset.scala:543) > at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) > at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) > at org.apache.spark.sql.Dataset.explain(Dataset.scala:543) > at org.apache.spark.sql.Dataset.explain(Dataset.scala:567) > ... 47 elided > {noformat} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org