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Posted to issues@spark.apache.org by "David Figueroa (JIRA)" <ji...@apache.org> on 2018/04/25 20:11:00 UTC
[jira] [Updated] (SPARK-24092) spark.python.worker.reuse does not
work?
[ https://issues.apache.org/jira/browse/SPARK-24092?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
David Figueroa updated SPARK-24092:
-----------------------------------
Description:
{{spark.python.worker.reuse is true by default but even after explicitly setting to true the code below does not print the same python worker process ids.}}
{code:java|title=procid.py|borderStyle=solid}
def return_pid(_): yield os.getpid()
spark = SparkSession.builder.getOrCreate()
pids = set(spark.sparkContext.range(32).mapPartitions(return_pid).collect())
print(pids)
pids = set(spark.sparkContext.range(32).mapPartitions(return_pid).collect())
print(pids){code}
was:
{{spark.python.worker.reuse is true by default but even after explicitly setting to true the code below does not print the same python worker process ids.}}
{code:java|title=procid.py|borderStyle=solid}
def return_pid(_): yield os.getpid()
spark = SparkSession.builder.getOrCreate()
pids = set(spark.sparkContext.range(32).mapPartitions(return_pid).collect())
print(pids)
pids = set(spark.sparkContext.range(32).mapPartitions(return_pid).collect())
print(pids){code}
> spark.python.worker.reuse does not work?
> ----------------------------------------
>
> Key: SPARK-24092
> URL: https://issues.apache.org/jira/browse/SPARK-24092
> Project: Spark
> Issue Type: Question
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: David Figueroa
> Priority: Minor
>
> {{spark.python.worker.reuse is true by default but even after explicitly setting to true the code below does not print the same python worker process ids.}}
> {code:java|title=procid.py|borderStyle=solid}
> def return_pid(_): yield os.getpid()
> spark = SparkSession.builder.getOrCreate()
> pids = set(spark.sparkContext.range(32).mapPartitions(return_pid).collect())
> print(pids)
> pids = set(spark.sparkContext.range(32).mapPartitions(return_pid).collect())
> print(pids){code}
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