PySpark: java.lang.OutofMemoryError: Java heap space

Question

I have been using PySpark with Ipython lately on my server with 24 CPUs and 32GB RAM. Its running only on one machine. In my process, I want to collect huge amount of data as is give in below code:

train_dataRDD = (train.map(lambda x:getTagsAndText(x)) .filter(lambda x:x[-1]!=[]) .flatMap(lambda (x,text,tags): [(tag,(x,text)) for tag in tags]) .groupByKey() .mapValues(list)) 

When I do

training_data =  train_dataRDD.collectAsMap() 

It gives me outOfMemory Error. Java heap Space. Also, I can not perform any operations on Spark after this error as it looses connection with Java. It gives Py4JNetworkError: Cannot connect to the java server.

It looks like heap space is small. How can I set it to bigger limits?

EDIT:

Things that I tried before running: sc._conf.set('spark.executor.memory','32g').set('spark.driver.memory','32g').set('spark.driver.maxResultsSize','0')

I changed the spark options as per the documentation here(if you do ctrl-f and search for spark.executor.extraJavaOptions) : http://spark.apache.org/docs/1.2.1/configuration.html

It says that I can avoid OOMs by setting spark.executor.memory option. I did the same thing but it seem not be working.

Answer 1

After trying out loads of configuration parameters, I found that there is only one need to be changed to enable more Heap space and i.e. spark.driver.memory.

sudo vim $SPARK_HOME/conf/spark-defaults.conf #uncomment the spark.driver.memory and change it according to your use. I changed it to below spark.driver.memory 15g # press : and then wq! to exit vim editor 

Close your existing spark application and re run it. You will not encounter this error again. :)