Spark 1.4 increase maxResultSize memory

I am using Spark 1.4 for my research and struggling with the memory settings. My machine has 16GB of memory so no problem there since the size of my file is only 300MB. Although, when I try to convert Spark RDD to panda dataframe using toPandas() function I receive the following error:

serialized results of 9 tasks (1096.9 MB) is bigger than spark.driver.maxResultSize (1024.0 MB)

I tried to fix this changing the spark-config file and still getting the same error. I've heard that this is a problem with spark 1.4 and wondering if you know how to solve this. Any help is much appreciated.

You can set spark.driver.maxResultSize parameter in the SparkConf object:

from pyspark import SparkConf, SparkContext

# In Jupyter you have to stop the current context first
sc.stop()

# Create new config
conf = (SparkConf()
    .set("spark.driver.maxResultSize", "2g"))

# Create new context
sc = SparkContext(conf=conf)

You should probably create a new SQLContext as well:

from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)

From the command line, such as with pyspark, --conf spark.driver.maxResultSize=3g can also be used to increase the max result size.