I tried the same statement using Spark 1.6.1
There was no error with default memory setting.
Suggest logging a bug.
> On May 1, 2016, at 9:22 PM, Koert Kuipers <ko...@tresata.com> wrote:
>
> Yeah I got that too, then I increased heap for tests to 8G to get error I
> showed earlier.
>
>> On May 2, 2016 12:09 AM, "Ted Yu" <yuzhih...@gmail.com> wrote:
>> Using commit hash 90787de864b58a1079c23e6581381ca8ffe7685f and Java 1.7.0_67
>> , I got:
>>
>> 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$1.apply(Dataset.scala:1860)
>> at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2438)
>> at org.apache.spark.sql.Dataset.head(Dataset.scala:1860)
>> at org.apache.spark.sql.Dataset.take(Dataset.scala:2077)
>> at org.apache.spark.sql.Dataset.showString(Dataset.scala:238)
>> at org.apache.spark.sql.Dataset.show(Dataset.scala:529)
>> at org.apache.spark.sql.Dataset.show(Dataset.scala:489)
>> at org.apache.spark.sql.Dataset.show(Dataset.scala:498)
>> ... 6 elided
>>
>> scala>
>>
>>> On Sun, May 1, 2016 at 8:34 PM, Koert Kuipers <ko...@tresata.com> wrote:
>>> by removing dependencies it turns into a different error, see below.
>>> the test is simply writing a DataFrame out to file and reading it back in.
>>> i see the error for all data sources (json, parquet, etc.).
>>>
>>> this is the data that i write out and read back in:
>>> val dfComplicated = sc.parallelize(List((Map("1" -> "a"), List("b", "c")),
>>> (Map("2" -> "b"), List("d", "e")))).toDF
>>>
>>>
>>> [info] java.lang.RuntimeException: Error while decoding:
>>> java.lang.NegativeArraySizeException
>>> [info] createexternalrow(if (isnull(input[0, map<string,string>])) null
>>> else staticinvoke(class
>>> org.apache.spark.sql.catalyst.util.ArrayBasedMapData$, ObjectType(interface
>>> scala.collection.Map), toScalaMap, staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue16, MapObjects_loopIsNull17,
>>> StringType), lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType).toString, input[0,
>>> map<string,string>].keyArray).array, true), staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue18, MapObjects_loopIsNull19,
>>> StringType), lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType).toString, input[0,
>>> map<string,string>].valueArray).array, true), true), if (isnull(input[1,
>>> array<string>])) null else staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue20, MapObjects_loopIsNull21,
>>> StringType), lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType).toString, input[1,
>>> array<string>]).array, true),
>>> StructField(_1,MapType(StringType,StringType,true),true),
>>> StructField(_2,ArrayType(StringType,true),true))
>>> [info] :- if (isnull(input[0, map<string,string>])) null else
>>> staticinvoke(class org.apache.spark.sql.catalyst.util.ArrayBasedMapData$,
>>> ObjectType(interface scala.collection.Map), toScalaMap, staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue16, MapObjects_loopIsNull17,
>>> StringType), lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType).toString, input[0,
>>> map<string,string>].keyArray).array, true), staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue18, MapObjects_loopIsNull19,
>>> StringType), lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType).toString, input[0,
>>> map<string,string>].valueArray).array, true), true)
>>> [info] : :- isnull(input[0, map<string,string>])
>>> [info] : : +- input[0, map<string,string>]
>>> [info] : :- null
>>> [info] : +- staticinvoke(class
>>> org.apache.spark.sql.catalyst.util.ArrayBasedMapData$, ObjectType(interface
>>> scala.collection.Map), toScalaMap, staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue16, MapObjects_loopIsNull17,
>>> StringType), lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType).toString, input[0,
>>> map<string,string>].keyArray).array, true), staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue18, MapObjects_loopIsNull19,
>>> StringType), lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType).toString, input[0,
>>> map<string,string>].valueArray).array, true), true)
>>> [info] : :- staticinvoke(class scala.collection.mutable.WrappedArray$,
>>> ObjectType(interface scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue16, MapObjects_loopIsNull17,
>>> StringType), lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType).toString, input[0,
>>> map<string,string>].keyArray).array, true)
>>> [info] : : +- mapobjects(lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType),
>>> lambdavariable(MapObjects_loopValue16, MapObjects_loopIsNull17,
>>> StringType).toString, input[0, map<string,string>].keyArray).array
>>> [info] : : +- mapobjects(lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType),
>>> lambdavariable(MapObjects_loopValue16, MapObjects_loopIsNull17,
>>> StringType).toString, input[0, map<string,string>].keyArray)
>>> [info] : : :- lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType).toString
>>> [info] : : : +- lambdavariable(MapObjects_loopValue16,
>>> MapObjects_loopIsNull17, StringType)
>>> [info] : : +- input[0, map<string,string>].keyArray
>>> [info] : : +- input[0, map<string,string>]
>>> [info] : +- staticinvoke(class scala.collection.mutable.WrappedArray$,
>>> ObjectType(interface scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue18, MapObjects_loopIsNull19,
>>> StringType), lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType).toString, input[0,
>>> map<string,string>].valueArray).array, true)
>>> [info] : +- mapobjects(lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType),
>>> lambdavariable(MapObjects_loopValue18, MapObjects_loopIsNull19,
>>> StringType).toString, input[0, map<string,string>].valueArray).array
>>> [info] : +- mapobjects(lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType),
>>> lambdavariable(MapObjects_loopValue18, MapObjects_loopIsNull19,
>>> StringType).toString, input[0, map<string,string>].valueArray)
>>> [info] : :- lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType).toString
>>> [info] : : +- lambdavariable(MapObjects_loopValue18,
>>> MapObjects_loopIsNull19, StringType)
>>> [info] : +- input[0, map<string,string>].valueArray
>>> [info] : +- input[0, map<string,string>]
>>> [info] +- if (isnull(input[1, array<string>])) null else staticinvoke(class
>>> scala.collection.mutable.WrappedArray$, ObjectType(interface
>>> scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue20, MapObjects_loopIsNull21,
>>> StringType), lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType).toString, input[1,
>>> array<string>]).array, true)
>>> [info] :- isnull(input[1, array<string>])
>>> [info] : +- input[1, array<string>]
>>> [info] :- null
>>> [info] +- staticinvoke(class scala.collection.mutable.WrappedArray$,
>>> ObjectType(interface scala.collection.Seq), make,
>>> mapobjects(lambdavariable(MapObjects_loopValue20, MapObjects_loopIsNull21,
>>> StringType), lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType).toString, input[1,
>>> array<string>]).array, true)
>>> [info] +- mapobjects(lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType),
>>> lambdavariable(MapObjects_loopValue20, MapObjects_loopIsNull21,
>>> StringType).toString, input[1, array<string>]).array
>>> [info] +- mapobjects(lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType),
>>> lambdavariable(MapObjects_loopValue20, MapObjects_loopIsNull21,
>>> StringType).toString, input[1, array<string>])
>>> [info] :- lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType).toString
>>> [info] : +- lambdavariable(MapObjects_loopValue20,
>>> MapObjects_loopIsNull21, StringType)
>>> [info] +- input[1, array<string>]
>>> [info] at
>>> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.fromRow(ExpressionEncoder.scala:244)
>>> [info] at
>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1$$anonfun$apply$13.apply(Dataset.scala:2121)
>>> [info] at
>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1$$anonfun$apply$13.apply(Dataset.scala:2121)
>>> [info] at
>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
>>> [info] at
>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
>>> [info] at
>>> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>>> [info] at
>>> scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
>>> [info] at
>>> scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
>>> [info] at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
>>> [info] at
>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2121)
>>> [info] at
>>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:54)
>>> [info] at
>>> org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2408)
>>> [info] at
>>> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2120)
>>> [info] at
>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Dataset.scala:2125)
>>> [info] at
>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Dataset.scala:2125)
>>> [info] at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2421)
>>> [info] at
>>> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2125)
>>> [info] at org.apache.spark.sql.Dataset.collect(Dataset.scala:2101)
>>>
>>>
>>>
>>>> On Thu, Apr 28, 2016 at 2:41 PM, Ted Yu <yuzhih...@gmail.com> wrote:
>>>> Are you able to pastebin a unit test which can reproduce the following ?
>>>>
>>>> Thanks
>>>>
>>>>> On Apr 28, 2016, at 11:35 AM, Koert Kuipers <ko...@tresata.com> wrote:
>>>>>
>>>>> i tried for the first time to run our own in-house unit tests on spark 2,
>>>>> and i get the error below.
>>>>> has anyone seen this?
>>>>>
>>>>> it is reproducible. i tried latest java 7 and it is still there.
>>>>>
>>>>> # A fatal error has been detected by the Java Runtime Environment:
>>>>> #
>>>>> # SIGSEGV (0xb) at pc=0x00007f7c3a4b1f54, pid=21939, tid=140171011417856
>>>>> #
>>>>> # JRE version: Java(TM) SE Runtime Environment (7.0_75-b13) (build
>>>>> 1.7.0_75-b13)
>>>>> # Java VM: Java HotSpot(TM) 64-Bit Server VM (24.75-b04 mixed mode
>>>>> linux-amd64 compressed oops)
>>>>> # Problematic frame:
>>>>> # V [libjvm.so+0x747f54] _Copy_arrayof_conjoint_jlongs+0x44
>>>>>
>>>>> more info:
>>>>>
>>>>> Stack: [0x00007f7c1b47e000,0x00007f7c1b57f000], sp=0x00007f7c1b57a9a8,
>>>>> free space=1010k
>>>>> Native frames: (J=compiled Java code, j=interpreted, Vv=VM code, C=native
>>>>> code)
>>>>> V [libjvm.so+0x747f54] _Copy_arrayof_conjoint_jlongs+0x44
>>>>> j sun.misc.Unsafe.copyMemory(Ljava/lang/Object;JLjava/lang/Object;JJ)V+0
>>>>> j
>>>>> org.apache.spark.unsafe.Platform.copyMemory(Ljava/lang/Object;JLjava/lang/Object;JJ)V+34
>>>>> j org.apache.spark.unsafe.types.UTF8String.getBytes()[B+76
>>>>> j org.apache.spark.unsafe.types.UTF8String.toString()Ljava/lang/String;+5
>>>>> j
>>>>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Ljava/lang/Object;)Ljava/lang/Object;+876
>>>>> j
>>>>> org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.fromRow(Lorg/apache/spark/sql/catalyst/InternalRow;)Ljava/lang/Object;+5
>>>>> j
>>>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1$$anonfun$apply$13.apply(Lorg/apache/spark/sql/catalyst/InternalRow;)Ljava/lang/Object;+11
>>>>> j
>>>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1$$anonfun$apply$13.apply(Ljava/lang/Object;)Ljava/lang/Object;+5
>>>>> J 13277 C2
>>>>> scala.collection.mutable.ArrayOps$ofRef.map(Lscala/Function1;Lscala/collection/generic/CanBuildFrom;)Ljava/lang/Object;
>>>>> (7 bytes) @ 0x00007f7c25eeae08 [0x00007f7c25eead40+0xc8]
>>>>> j
>>>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply()Ljava/lang/Object;+43
>>>>> j
>>>>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(Lorg/apache/spark/sql/SparkSession;Lorg/apache/spark/sql/execution/QueryExecution;Lscala/Function0;)Ljava/lang/Object;+106
>>>>> j
>>>>> org.apache.spark.sql.Dataset.withNewExecutionId(Lscala/Function0;)Ljava/lang/Object;+12
>>>>> j
>>>>> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1()Ljava/lang/Object;+9
>>>>> j
>>>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Lorg/apache/spark/sql/Dataset;)Ljava/lang/Object;+4
>>>>> j
>>>>> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Ljava/lang/Object;)Ljava/lang/Object;+5
>>>>> j
>>>>> org.apache.spark.sql.Dataset.withCallback(Ljava/lang/String;Lorg/apache/spark/sql/Dataset;Lscala/Function1;)Ljava/lang/Object;+25
>>>>> j
>>>>> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Z)Ljava/lang/Object;+20
>>>>> j org.apache.spark.sql.Dataset.collect()Ljava/lang/Object;+2
