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https://issues.apache.org/jira/browse/SPARK-24983?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17157132#comment-17157132
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Apache Spark commented on SPARK-24983:
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User 'constzhou' has created a pull request for this issue:
https://github.com/apache/spark/pull/29094
> Collapsing multiple project statements with dependent When-Otherwise
> statements on the same column can OOM the driver
> ---------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-24983
> URL: https://issues.apache.org/jira/browse/SPARK-24983
> Project: Spark
> Issue Type: Bug
> Components: Optimizer, SQL
> Affects Versions: 2.3.1
> Reporter: David Vogelbacher
> Priority: Major
>
> I noticed that writing a spark job that includes many sequential
> {{when-otherwise}} statements on the same column can easily OOM the driver
> while generating the optimized plan because the project node will grow
> exponentially in size.
> Example:
> {noformat}
> scala> import org.apache.spark.sql.functions._
> import org.apache.spark.sql.functions._
> scala> val df = Seq("a", "b", "c", "1").toDF("text")
> df: org.apache.spark.sql.DataFrame = [text: string]
> scala> var dfCaseWhen = df.filter($"text" =!= lit("0"))
> dfCaseWhen: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [text:
> string]
> scala> for( a <- 1 to 5) {
> | dfCaseWhen = dfCaseWhen.withColumn("text", when($"text" ===
> lit(a.toString), lit("r" + a.toString)).otherwise($"text"))
> | }
> scala> dfCaseWhen.queryExecution.analyzed
> res6: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
> Project [CASE WHEN (text#12 = 5) THEN r5 ELSE text#12 END AS text#14]
> +- Project [CASE WHEN (text#10 = 4) THEN r4 ELSE text#10 END AS text#12]
> +- Project [CASE WHEN (text#8 = 3) THEN r3 ELSE text#8 END AS text#10]
> +- Project [CASE WHEN (text#6 = 2) THEN r2 ELSE text#6 END AS text#8]
> +- Project [CASE WHEN (text#3 = 1) THEN r1 ELSE text#3 END AS text#6]
> +- Filter NOT (text#3 = 0)
> +- Project [value#1 AS text#3]
> +- LocalRelation [value#1]
> scala> dfCaseWhen.queryExecution.optimizedPlan
> res5: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
> Project [CASE WHEN (CASE WHEN (CASE WHEN (CASE WHEN (CASE WHEN (value#1 = 1)
> THEN r1 ELSE value#1 END = 2) THEN r2 ELSE CASE WHEN (value#1 = 1) THEN r1
> ELSE value#1 END END = 3) THEN r3 ELSE CASE WHEN (CASE WHEN (value#1 = 1)
> THEN r1 ELSE value#1 END = 2) THEN r2 ELSE CASE WHEN (value#1 = 1) THEN r1
> ELSE value#1 END END END = 4) THEN r4 ELSE CASE WHEN (CASE WHEN (CASE WHEN
> (value#1 = 1) THEN r1 ELSE value#1 END = 2) THEN r2 ELSE CASE WHEN (value#1 =
> 1) THEN r1 ELSE value#1 END END = 3) THEN r3 ELSE CASE WHEN (CASE WHEN
> (value#1 = 1) THEN r1 ELSE value#1 END = 2) THEN r2 ELSE CASE WHEN (value#1 =
> 1) THEN r1 ELSE value#1 END END END END = 5) THEN r5 ELSE CASE WHEN (CASE
> WHEN (CASE WHEN (CASE WHEN (value#1 = 1) THEN r1 ELSE va...
> {noformat}
> As one can see the optimized plan grows exponentially in the number of
> {{when-otherwise}} statements here.
> I can see that this comes from the {{CollapseProject}} optimizer rule.
> Maybe we should put a limit on the resulting size of the project node after
> collapsing and only collapse if we stay under the limit.
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