I think this is probably dying on the driver itself, as you are probably materializing the whole dataset inside your python driver. How large is spark_data_array compared to your driver memory?
On Fri, Jul 11, 2014 at 7:30 PM, Mohit Jaggi <mohitja...@gmail.com> wrote: > I put the same dataset into scala (using spark-shell) and it acts weird. I > cannot do a count on it, the executors seem to hang. The WebUI shows 0/96 > in the status bar, shows details about the worker nodes but there is no > progress. > sc.parallelize does finish (takes too long for the data size) in scala. > > > On Fri, Jul 11, 2014 at 2:00 PM, Mohit Jaggi <mohitja...@gmail.com> wrote: > >> 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) >> > >
