[ https://issues.apache.org/jira/browse/SPARK-21096?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Irina Truong updated SPARK-21096: --------------------------------- Description: 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? was: 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? > 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? -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org