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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2017/05/11 03:49:04 UTC
[jira] [Commented] (SPARK-20369) pyspark: Dynamic configuration
with SparkConf does not work
[ https://issues.apache.org/jira/browse/SPARK-20369?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16005842#comment-16005842 ]
Hyukjin Kwon commented on SPARK-20369:
--------------------------------------
I am resolving this as I can't reproduce as above and it looks the reporter is inactive.
> 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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