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From "Michael Armbrust (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-15062) Show on DataFrame causes OutOfMemoryError, NegativeArraySizeException or segfault
Date Tue, 03 May 2016 01:22:13 GMT

     [ https://issues.apache.org/jira/browse/SPARK-15062?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Michael Armbrust updated SPARK-15062:
-------------------------------------
    Assignee: Bo Meng

> Show on DataFrame causes OutOfMemoryError, NegativeArraySizeException or segfault 
> ----------------------------------------------------------------------------------
>
>                 Key: SPARK-15062
>                 URL: https://issues.apache.org/jira/browse/SPARK-15062
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>         Environment: spark-2.0.0-SNAPSHOT using commit hash 90787de864b58a1079c23e6581381ca8ffe7685f
and Java 1.7.0_67
>            Reporter: koert kuipers
>            Assignee: Bo Meng
>            Priority: Blocker
>             Fix For: 2.0.0
>
>
> {noformat}
> scala> val dfComplicated = sc.parallelize(List((Map("1" -> "a"), List("b", "c")),
(Map("2" -> "b"), List("d", "e")))).toDF
> ...
> dfComplicated: org.apache.spark.sql.DataFrame = [_1: map<string,string>, _2: array<string>]
> scala> dfComplicated.show
> java.lang.OutOfMemoryError: Java heap space
>   at org.apache.spark.unsafe.types.UTF8String.getBytes(UTF8String.java:229)
>   at org.apache.spark.unsafe.types.UTF8String.toString(UTF8String.java:821)
>   at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Unknown
Source)
>   at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.fromRow(ExpressionEncoder.scala:241)
>   at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1$$anonfun$apply$13.apply(Dataset.scala:2121)
>   at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1$$anonfun$apply$13.apply(Dataset.scala:2121)
>   at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>   at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
>   at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>   at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
>   at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2121)
>   at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:54)
>   at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2408)
>   at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2120)
>   at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2127)
>   at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1861)
>   at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1860)
>   at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2438)
>   at org.apache.spark.sql.Dataset.head(Dataset.scala:1860)
>   at org.apache.spark.sql.Dataset.take(Dataset.scala:2077)
>   at org.apache.spark.sql.Dataset.showString(Dataset.scala:238)
>   at org.apache.spark.sql.Dataset.show(Dataset.scala:529)
>   at org.apache.spark.sql.Dataset.show(Dataset.scala:489)
>   at org.apache.spark.sql.Dataset.show(Dataset.scala:498)
>   ... 6 elided
> scala>
> {noformat}
> By increasing memory to 8G one will instead get a NegativeArraySizeException or a segfault.
> See here for original discussion:
> http://apache-spark-developers-list.1001551.n3.nabble.com/spark-2-segfault-td17381.html



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