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https://issues.apache.org/jira/browse/SPARK-37222?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Nicholas Chammas updated SPARK-37222:
-------------------------------------
Affects Version/s: 3.2.1
> 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, 3.2.1
> 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}
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