[jira] [Resolved] (SPARK-21096) Pickle error when passing a member variable to Spark executors

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-21096?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-21096.
----------------------------------
    Resolution: Not A Problem

I am resolving this. Please reopen this if I misunderstood.

> Pickle error when passing a member variable to Spark executors
> --------------------------------------------------------------
>
>                 Key: SPARK-21096
>                 URL: https://issues.apache.org/jira/browse/SPARK-21096
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.1.1
>            Reporter: Irina Truong
>
> There is a pickle error when submitting a spark job that references a member variable in a lambda, even when the member variable is a simple type that should be serializable.
> Here is a minimal example:
> https://gist.github.com/j-bennet/8390c6d9a81854696f1a9b42a4ea8278
> In the gist above, this method will throw an exception:
> {quote}
> def build_fail(self):
>     processed = self.rdd.map(lambda row: process_row(row, self.multiplier))
>     return processed.collect()
> {quote}
> While this method will run just fine:
> {quote}
> def build_ok(self):
>     mult = self.multiplier
>     processed = self.rdd.map(lambda row: process_row(row, mult))
>     return processed.collect()
> {quote}
> In this example, {{self.multiplier}} is just an int. However, passing it into a lambda throws a pickle error, because it is trying to pickle the whole {{self}}, and that contains {{sc}}.
> If this is the expected behavior, then why should re-assigning {{self.multiplier}} to a variable make a difference?



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