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https://issues.apache.org/jira/browse/SPARK-15679?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15308436#comment-15308436
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nalin garg commented on SPARK-15679:
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The purpose of the code is to load compute some logic based on the "myFunc"
method that operated on RDD to get parallelization benefit.
The following lines :
df_rdd = ParallelBuild().run().map(lambda line: line).persist()
r = df_rdd.map(ParallelBuild().myFunc)
gave me exit 0. Reading google suggested that Spark is lazy evaluation so some
action will trigger the effect and i add :
r.count() which give above mentioned stacktrace.
Noticeable thing was that :
r = df_rdd.map(ParallelBuild().myFunc)
gives "pipelinedrdd" not sure what that is but looks like some transformation?
Interesting part was that when I removed run method and implemented:
data = [(1,'a'), (1,'b'), (1,'c'), (2,'d'), (3,'r'), (4,'a'), (2,'t'), (3,'y'),
(1,'f')]
df = sqlContext.createDataFrame(data, schema= ['uid', 'address_uid'])
directly in my main function then things worked just fine. But obviously i
loose modular part of my code.
> Passing functions do not work in classes
> ----------------------------------------
>
> Key: SPARK-15679
> URL: https://issues.apache.org/jira/browse/SPARK-15679
> Project: Spark
> Issue Type: Bug
> Reporter: nalin garg
>
> {code}
> from pyspark import SparkContext
> from pyspark.sql import SQLContext, HiveContext
> import csv, io, StringIO
> from pyspark.sql.functions import *
> from pyspark.sql import Row
> from pyspark.sql import *
> from pyspark.sql import functions as F
> from pyspark.sql.functions import asc, desc
> sc = SparkContext("local", "Summary Report")
> sqlContext = SQLContext(sc)
> class ParallelBuild(object):
> def myFunc(self, s):
> l = s.split(',')
> print l[0], l[1]
> return l[0]
> def list_to_csv_str(x):
> output = StringIO.StringIO("")
> csv.writer(output).writerow(x)
> return output.getvalue().strip()
> def run(self):
> data = [(1,'a'), (1,'b'), (1,'c'), (2,'d'), (3,'r'), (4,'a'),
> (2,'t'), (3,'y'), (1,'f')]
> df = sqlContext.createDataFrame(data, schema= ['uid', 'address_uid'])
> return df
> if __name__ == "__main__":
> df_rdd = ParallelBuild().run().map(lambda line: line).persist()
> r = df_rdd.map(ParallelBuild().myFunc)
> r.count()
> {code}
> Above code returns JavaPackage not callable exception.
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