spark_data_array here has about 35k rows with 4k columns. I have 4 nodes in the cluster and gave 48g to executors. also tried kyro serialization.
traceback (most recent call last): File "/mohit/./m.py", line 58, in <module> spark_data = sc.parallelize(spark_data_array) File "/mohit/spark/python/pyspark/context.py", line 265, in parallelize jrdd = readRDDFromFile(self._jsc, tempFile.name, numSlices) File "/mohit/spark/python/lib/py4j-0.8.1-src.zip/py4j/java_gateway.py", line 537, in __call__ File "/mohit/spark/python/lib/py4j-0.8.1-src.zip/py4j/protocol.py", line 300, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.readRDDFromFile. : java.lang.OutOfMemoryError: Java heap space at org.apache.spark.api.python.PythonRDD$.readRDDFromFile(PythonRDD.scala:279) at org.apache.spark.api.python.PythonRDD.readRDDFromFile(PythonRDD.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379) at py4j.Gateway.invoke(Gateway.java:259) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:207) at java.lang.Thread.run(Thread.java:745)