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https://issues.apache.org/jira/browse/SPARK-19317?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15834700#comment-15834700
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Barry Becker commented on SPARK-19317:
--------------------------------------
As far as I can tell, this only occurs when filtering for null values on a
cluster. I cannot reproduce it in a unit test in my linux VM which has spark
running in development mode.
> UnsupportedOperationException: empty.reduceLeft in LinearSeqOptimized
> ---------------------------------------------------------------------
>
> Key: SPARK-19317
> URL: https://issues.apache.org/jira/browse/SPARK-19317
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0
> Reporter: Barry Becker
>
> I wish I had more of a simple reproducible case to give, but I got the below
> exception while selecting null values in one of the columns of a dataframe.
> My client code that failed was
> df.filter(filterExp).count()
> where the filter expression was something like someColumn.isNull.
> There were 412 nulls out of 716,000 total rows for the column being filtered.
> Its odd because I have a different, smaller dataset where I did the same
> thing on a column with 100 nulls out of 800 and did not get the error.
> The exception seems to indicate that spark is trying to do reduceLeft on an
> empy list.
> {code}
> java.lang.UnsupportedOperationException:
> empty.reduceLeftscala.collection.LinearSeqOptimized$class.reduceLeft(LinearSeqOptimized.scala:137)
> scala.collection.immutable.List.reduceLeft(List.scala:84)
> scala.collection.TraversableOnce$class.reduce(TraversableOnce.scala:208)
> scala.collection.AbstractTraversable.reduce(Traversable.scala:104)
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$1.applyOrElse(InMemoryTableScanExec.scala:90)
>
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$1.applyOrElse(InMemoryTableScanExec.scala:54)
>
> scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$1.applyOrElse(InMemoryTableScanExec.scala:61)
>
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$1.applyOrElse(InMemoryTableScanExec.scala:54)
> scala.PartialFunction$Lifted.apply(PartialFunction.scala:223)
> scala.PartialFunction$Lifted.apply(PartialFunction.scala:219)
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$2.apply(InMemoryTableScanExec.scala:95)
>
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$2.apply(InMemoryTableScanExec.scala:94)
>
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
>
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> scala.collection.immutable.List.foreach(List.scala:381)
> scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
> scala.collection.immutable.List.flatMap(List.scala:344)
> org.apache.spark.sql.execution.columnar.InMemoryTableScanExec.(InMemoryTableScanExec.scala:94)
>
> org.apache.spark.sql.execution.SparkStrategies$InMemoryScans$$anonfun$6.apply(SparkStrategies.scala:306)
>
> org.apache.spark.sql.execution.SparkStrategies$InMemoryScans$$anonfun$6.apply(SparkStrategies.scala:306)
>
> org.apache.spark.sql.execution.SparkPlanner.pruneFilterProject(SparkPlanner.scala:96)
>
> org.apache.spark.sql.execution.SparkStrategies$InMemoryScans$.apply(SparkStrategies.scala:302)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:62)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$1.apply(QueryPlanner.scala:62)
> scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
> scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:92)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:77)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:74)
>
> scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
>
> scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
> scala.collection.Iterator$class.foreach(Iterator.scala:893)
> scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157)
> scala.collection.AbstractIterator.foldLeft(Iterator.scala:1336)
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:74)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:66)
> scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
> scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:92)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:77)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2$$anonfun$apply$2.apply(QueryPlanner.scala:74)
>
> scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
>
> scala.collection.TraversableOnce$$anonfun$foldLeft$1.apply(TraversableOnce.scala:157)
> scala.collection.Iterator$class.foreach(Iterator.scala:893)
> scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:157)
> scala.collection.AbstractIterator.foldLeft(Iterator.scala:1336)
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:74)
>
> org.apache.spark.sql.catalyst.planning.QueryPlanner$$anonfun$2.apply(QueryPlanner.scala:66)
> scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
> scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
> org.apache.spark.sql.catalyst.planning.QueryPlanner.plan(QueryPlanner.scala:92)
>
> org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:79)
>
> org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:75)
>
> org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:84)
>
> org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:84)
> org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2774)
> org.apache.spark.sql.Dataset.count(Dataset.scala:2404)
> mypackage.Selection(Selection.scala:34)
> {code}
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