Specify --executor-memory in your spark-submit command.
On Thu, Jun 16, 2016 at 9:01 AM, spR <data.smar...@gmail.com> wrote:
> Thank you. Can you pls tell How to increase the executor memory?
>
>
>
> On Wed, Jun 15, 2016 at 5:59 PM, Jeff Zhang <zjf...@gmail.com> wrote:
>
>> >>> Caused by: java.lang.OutOfMemoryError: GC overhead limit exceeded
>>
>>
>> It is OOM on the executor. Please try to increase executor memory.
>> "--executor-memory"
>>
>>
>>
>>
>>
>> On Thu, Jun 16, 2016 at 8:54 AM, spR <data.smar...@gmail.com> wrote:
>>
>>> Hey,
>>>
>>> error trace -
>>>
>>> hey,
>>>
>>>
>>> error trace -
>>>
>>>
>>> ---------------------------------------------------------------------------Py4JJavaError
>>> Traceback (most recent call
>>> last)<ipython-input-22-925883e4d630> in <module>()----> 1 temp.take(2)
>>>
>>> /Users/my/Documents/My_Study_folder/spark-1.6.1/python/pyspark/sql/dataframe.pyc
>>> in take(self, num) 304 with SCCallSiteSync(self._sc) as css:
>>> 305 port =
>>> self._sc._jvm.org.apache.spark.sql.execution.EvaluatePython.takeAndServe(-->
>>> 306 self._jdf, num) 307 return
>>> list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
>>> 308
>>>
>>> /Users/my/Documents/My_Study_folder/spark-1.6.1/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py
>>> in __call__(self, *args) 811 answer =
>>> self.gateway_client.send_command(command) 812 return_value =
>>> get_return_value(--> 813 answer, self.gateway_client,
>>> self.target_id, self.name) 814
>>> 815 for temp_arg in temp_args:
>>>
>>> /Users/my/Documents/My_Study_folder/spark-1.6.1/python/pyspark/sql/utils.pyc
>>> in deco(*a, **kw) 43 def deco(*a, **kw): 44 try:--->
>>> 45 return f(*a, **kw) 46 except
>>> py4j.protocol.Py4JJavaError as e: 47 s =
>>> e.java_exception.toString()
>>> /Users/my/Documents/My_Study_folder/spark-1.6.1/python/lib/py4j-0.9-src.zip/py4j/protocol.py
>>> in get_return_value(answer, gateway_client, target_id, name) 306
>>> raise Py4JJavaError( 307 "An error occurred
>>> while calling {0}{1}{2}.\n".--> 308 format(target_id,
>>> ".", name), value) 309 else:
>>> 310 raise Py4JError(
>>> Py4JJavaError: An error occurred while calling
>>> z:org.apache.spark.sql.execution.EvaluatePython.takeAndServe.
>>> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
>>> in stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage
>>> 3.0 (TID 76, localhost): java.lang.OutOfMemoryError: GC overhead limit
>>> exceeded
>>> at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2205)
>>> at com.mysql.jdbc.MysqlIO.nextRow(MysqlIO.java:1984)
>>> at com.mysql.jdbc.MysqlIO.readSingleRowSet(MysqlIO.java:3403)
>>> at com.mysql.jdbc.MysqlIO.getResultSet(MysqlIO.java:470)
>>> at com.mysql.jdbc.MysqlIO.readResultsForQueryOrUpdate(MysqlIO.java:3105)
>>> at com.mysql.jdbc.MysqlIO.readAllResults(MysqlIO.java:2336)
>>> at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2729)
>>> at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2549)
>>> at
>>> com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:1861)
>>> at
>>> com.mysql.jdbc.PreparedStatement.executeQuery(PreparedStatement.java:1962)
>>> at
>>> org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:363)
>>> at
>>> org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:339)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>> at org.apache.spark.scheduler.Task.run(Task.scala:89)
>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>>> at java.lang.Thread.run(Thread.java:745)
>>>
>>> Driver stacktrace:
>>> at org.apache.spark.scheduler.DAGScheduler.org
>>> <http://org.apache.spark.scheduler.dagscheduler.org/>$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
>>> at
>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
>>> at scala.Option.foreach(Option.scala:236)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
>>> at
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
>>> at
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
>>> at
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
>>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
>>> at
>>> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:212)
>>> at
>>> org.apache.spark.sql.execution.EvaluatePython$$anonfun$takeAndServe$1.apply$mcI$sp(python.scala:126)
>>> at
>>> org.apache.spark.sql.execution.EvaluatePython$$anonfun$takeAndServe$1.apply(python.scala:124)
>>> at
>>> org.apache.spark.sql.execution.EvaluatePython$$anonfun$takeAndServe$1.apply(python.scala:124)
>>> at
>>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
>>> at
>>> org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:2086)
>>> at
>>> org.apache.spark.sql.execution.EvaluatePython$.takeAndServe(python.scala:124)
>>> at
>>> org.apache.spark.sql.execution.EvaluatePython.takeAndServe(python.scala)
>>> 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:231)
>>> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
>>> at py4j.Gateway.invoke(Gateway.java:259)
>>> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
>>> at py4j.commands.CallCommand.execute(CallCommand.java:79)
>>> at py4j.GatewayConnection.run(GatewayConnection.java:209)
>>> at java.lang.Thread.run(Thread.java:745)
>>> Caused by: java.lang.OutOfMemoryError: GC overhead limit exceeded
>>> at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2205)
>>> at com.mysql.jdbc.MysqlIO.nextRow(MysqlIO.java:1984)
>>> at com.mysql.jdbc.MysqlIO.readSingleRowSet(MysqlIO.java:3403)
>>> at com.mysql.jdbc.MysqlIO.getResultSet(MysqlIO.java:470)
>>> at com.mysql.jdbc.MysqlIO.readResultsForQueryOrUpdate(MysqlIO.java:3105)
>>> at com.mysql.jdbc.MysqlIO.readAllResults(MysqlIO.java:2336)
>>> at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2729)
>>> at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2549)
>>> at
>>> com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:1861)
>>> at
>>> com.mysql.jdbc.PreparedStatement.executeQuery(PreparedStatement.java:1962)
>>> at
>>> org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$$anon$1.<init>(JDBCRDD.scala:363)
>>> at
>>> org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:339)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>> at org.apache.spark.scheduler.Task.run(Task.scala:89)
>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>>> ... 1 more
>>>
>>>
>>>
>>> On Wed, Jun 15, 2016 at 5:39 PM, Jeff Zhang <zjf...@gmail.com> wrote:
>>>
>>>> Could you paste the full stacktrace ?
>>>>
>>>> On Thu, Jun 16, 2016 at 7:24 AM, spR <data.smar...@gmail.com> wrote:
>>>>
>>>>> Hi,
>>>>> I am getting this error while executing a query using sqlcontext.sql
>>>>>
>>>>> The table has around 2.5 gb of data to be scanned.
>>>>>
>>>>> First I get out of memory exception. But I have 16 gb of ram
>>>>>
>>>>> Then my notebook dies and I get below error
>>>>>
>>>>> Py4JNetworkError: An error occurred while trying to connect to the Java
>>>>> server
>>>>>
>>>>>
>>>>> Thank You
>>>>>
>>>>
>>>>
>>>>
>>>> --
>>>> Best Regards
>>>>
>>>> Jeff Zhang
>>>>
>>>
>>>
>>
>>
>> --
>> Best Regards
>>
>> Jeff Zhang
>>
>
>
--
Best Regards
Jeff Zhang
