Matthew McClain created SPARK-20369:
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Summary: pyspark: Dynamic configuration with SparkConf does not
work
Key: SPARK-20369
URL: https://issues.apache.org/jira/browse/SPARK-20369
Project: Spark
Issue Type: Bug
Components: PySpark
Affects Versions: 2.1.0
Environment: Ubuntu 14.04.1 LTS (GNU/Linux 3.13.0-40-generic x86_64)
and Mac OS X 10.11.6
Reporter: Matthew McClain
Priority: Minor
Setting spark properties dynamically in pyspark using SparkConf object does not
work. Here is the code that shows the bug:
---
from pyspark import SparkContext, SparkConf
def main():
conf = SparkConf().setAppName("spark-conf-test") \
.setMaster("local[2]") \
.set('spark.python.worker.memory',"1g") \
.set('spark.executor.memory',"3g") \
.set("spark.driver.maxResultSize","2g")
print "Spark Config values in SparkConf:"
print conf.toDebugString()
sc = SparkContext(conf=conf)
print "Actual Spark Config values:"
print sc.getConf().toDebugString()
if __name__ == "__main__":
main()
---
Here is the output; none of the config values set in SparkConf are used in the
SparkContext configuration:
Spark Config values in SparkConf:
spark.master=local[2]
spark.executor.memory=3g
spark.python.worker.memory=1g
spark.app.name=spark-conf-test
spark.driver.maxResultSize=2g
17/04/18 10:21:24 WARN NativeCodeLoader: Unable to load native-hadoop library
for your platform... using builtin-java classes where applicable
Actual Spark Config values:
spark.app.id=local-1492528885708
spark.app.name=sandbox.py
spark.driver.host=10.201.26.172
spark.driver.maxResultSize=4g
spark.driver.port=54657
spark.executor.id=driver
spark.files=file:/Users/matt.mcclain/dev/datascience-experiments/mmcclain/client_clusters/sandbox.py
spark.master=local[*]
spark.rdd.compress=True
spark.serializer.objectStreamReset=100
spark.submit.deployMode=client
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