Archives of Support Questions (Read Only)

serg30911 · ‎11-10-2016

Hi!

I run 2 to spark an option

SPARK_MAJOR_VERSION=2 pyspark --master yarn  --verbose

spark starts, I run the SC and get an error, the field in the table exactly there. not the problem

SPARK_MAJOR_VERSION=2 pyspark --master yarn  --verbose
SPARK_MAJOR_VERSION is set to 2, using Spark2
Python 2.7.12 |Anaconda custom (64-bit)| (default, Jul  2 2016, 17:42:40)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
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Using properties file: /usr/hdp/current/spark2-historyserver/conf/spark-defaults.conf
Adding default property: spark.history.kerberos.keytab=none
Adding default property: spark.history.fs.logDirectory=hdfs:///spark2-history/
Adding default property: spark.eventLog.enabled=true
Adding default property: spark.driver.extraLibraryPath=/usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
Adding default property: spark.yarn.queue=default
Adding default property: spark.yarn.historyServer.address=en-002.msk.mts.ru:18081
Adding default property: spark.history.kerberos.principal=none
Adding default property: spark.history.provider=org.apache.spark.deploy.history.FsHistoryProvider
Adding default property: spark.executor.extraLibraryPath=/usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
Adding default property: spark.eventLog.dir=hdfs:///spark2-history/
Adding default property: spark.history.ui.port=18081
Parsed arguments:
  master                  yarn
  deployMode              null
  executorMemory          null
  executorCores           null
  totalExecutorCores      null
  propertiesFile          /usr/hdp/current/spark2-historyserver/conf/spark-defaults.conf
  driverMemory            null
  driverCores             null
  driverExtraClassPath    null
  driverExtraLibraryPath  /usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
  driverExtraJavaOptions  null
  supervise               false
  queue                   null
  numExecutors            null
  files                   null
  pyFiles                 null
  archives                null
  mainClass               null
  primaryResource         pyspark-shell
  name                    PySparkShell
  childArgs               []
  jars                    null
  packages                null
  packagesExclusions      null
  repositories            null
  verbose                 true


Spark properties used, including those specified through
 --conf and those from the properties file /usr/hdp/current/spark2-historyserver/conf/spark-defaults.conf:
  spark.yarn.queue -> default
  spark.history.kerberos.principal -> none
  spark.executor.extraLibraryPath -> /usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
  spark.driver.extraLibraryPath -> /usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
  spark.eventLog.enabled -> true
  spark.yarn.historyServer.address -> en-002.msk.mts.ru:18081
  spark.history.ui.port -> 18081
  spark.history.provider -> org.apache.spark.deploy.history.FsHistoryProvider
  spark.history.fs.logDirectory -> hdfs:///spark2-history/
  spark.history.kerberos.keytab -> none
  spark.eventLog.dir -> hdfs:///spark2-history/




Main class:
org.apache.spark.api.python.PythonGatewayServer
Arguments:


System properties:
spark.yarn.queue -> default
spark.history.kerberos.principal -> none
spark.executor.extraLibraryPath -> /usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
spark.driver.extraLibraryPath -> /usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64
spark.yarn.historyServer.address -> en-002.msk.mts.ru:18081
spark.eventLog.enabled -> true
spark.history.ui.port -> 18081
SPARK_SUBMIT -> true
spark.history.provider -> org.apache.spark.deploy.history.FsHistoryProvider
spark.history.fs.logDirectory -> hdfs:///spark2-history/
spark.app.name -> PySparkShell
spark.history.kerberos.keytab -> none
spark.submit.deployMode -> client
spark.eventLog.dir -> hdfs:///spark2-history/
spark.master -> yarn
spark.yarn.isPython -> true
Classpath elements:








Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.0.0.2.5.0.0-1245
      /_/


Using Python version 2.7.12 (default, Jul  2 2016 17:42:40)
SparkSession available as 'spark'.
>>>
>>>
>>> ds = sqlContext.table('default.geo').limit(100000)
>>> ds.groupby('id').count().show(10)
[Stage 0:==========================================>                (5 + 2) / 7]16/11/09 18:11:56 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID 7, wn-019): java.lang.NullPointerException
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:784)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:784)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
        at org.apache.spark.scheduler.Task.run(Task.scala:85)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

traceback.

 ERROR TaskSetManager: Task 0 in stage 1.0 failed 4 times; aborting job
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/hdp/2.5.0.0-1245/spark2/python/pyspark/sql/dataframe.py", line 287, in show
    print(self._jdf.showString(n, truncate))
  File "/usr/hdp/2.5.0.0-1245/spark2/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__
  File "/usr/hdp/2.5.0.0-1245/spark2/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)


  File "/usr/hdp/2.5.0.0-1245/spark2/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py", line 312, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o45.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 10, wn-029): java.lang.NullPointerException
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:784)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:784)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
        at org.apache.spark.scheduler.Task.run(Task.scala:85)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)


Driver stacktrace:
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1438)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1437)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
        at scala.Option.foreach(Option.scala:257)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1871)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1884)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1897)
        at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347)
        at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39)
        at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2183)
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
        at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2532)
        at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2182)
        at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2189)
        at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1925)
        at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1924)
        at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2562)
        at org.apache.spark.sql.Dataset.head(Dataset.scala:1924)
        at org.apache.spark.sql.Dataset.take(Dataset.scala:2139)
        at org.apache.spark.sql.Dataset.showString(Dataset.scala:239)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:498)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
        at py4j.Gateway.invoke(Gateway.java:280)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:211)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.NullPointerException
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
        at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:784)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:784)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
        at org.apache.spark.scheduler.Task.run(Task.scala:85)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        ... 1 more

my ENV

OS: RHEL 6.5

HDP: 2.5.0.0

SPARK: 2.0

Python: 2.7 on Anaconda

cstanca · ‎12-26-2016

@Sergey Paramoshkin

Your rdd is getting empty somewhere. The null pointer exception indicates that an aggregation task is attempted against of a null value. Check your data for null where not null should be present and especially on those columns that are subject of aggregation, like a reduce task, for example. In your case, it may be the id field.

View solution in original post

rajkumar_singh · ‎12-26-2016

@Sergey Paramoshkin

possibly you are hitting this bug in spark codegen https://issues.apache.org/jira/browse/SPARK-18528

cstanca · ‎12-26-2016

@Sergey Paramoshkin

Your rdd is getting empty somewhere. The null pointer exception indicates that an aggregation task is attempted against of a null value. Check your data for null where not null should be present and especially on those columns that are subject of aggregation, like a reduce task, for example. In your case, it may be the id field.

sandyy006 · ‎01-05-2017

@Sergey Paramoshkin Were you able to fix this issue?

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Archives of Support Questions (Read Only)

PySpark failuer spark.SparkException: Job aborted due to stage failure