Hi
I even tried the dataframe.cache() action to carry out the cross tab
transformation. However still I get the
same OOM error.
recommender_ct.cache()
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-15-6d6114a78785> in <module>()
----> 1 recommender_ct.cache()
/Users/i854319/spark/python/pyspark/sql/dataframe.pyc in cache(self)
375 """
376 self.is_cached = True
--> 377 self._jdf.cache()
378 return self
379
/Users/i854319/spark/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/i854319/spark/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/i854319/spark/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 o40.cache.
: java.lang.OutOfMemoryError
at
java.io.ByteArrayOutputStream.hugeCapacity(ByteArrayOutputStream.java:123)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:117)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:101)
at
org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:301)
at
org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:294)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:122)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2055)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:707)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:706)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.mapPartitions(RDD.scala:706)
at
org.apache.spark.sql.execution.ConvertToUnsafe.doExecute(rowFormatConverters.scala:38)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130)
at
org.apache.spark.sql.execution.columnar.InMemoryRelation.buildBuffers(InMemoryColumnarTableScan.scala:129)
at
org.apache.spark.sql.execution.columnar.InMemoryRelation.<init>(InMemoryColumnarTableScan.scala:118)
at
org.apache.spark.sql.execution.columnar.InMemoryRelation$.apply(InMemoryColumnarTableScan.scala:41)
at
org.apache.spark.sql.execution.CacheManager$$anonfun$cacheQuery$1.apply(CacheManager.scala:93)
at
org.apache.spark.sql.execution.CacheManager.writeLock(CacheManager.scala:60)
at
org.apache.spark.sql.execution.CacheManager.cacheQuery(CacheManager.scala:84)
at org.apache.spark.sql.DataFrame.persist(DataFrame.scala:1581)
at org.apache.spark.sql.DataFrame.cache(DataFrame.scala:1590)
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)
--
View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Java-Heap-Error-tp27669p27696.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.
---------------------------------------------------------------------
To unsubscribe e-mail: user-unsubscr...@spark.apache.org
