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https://issues.apache.org/jira/browse/SPARK-13691?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15183465#comment-15183465
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Shixiong Zhu commented on SPARK-13691:
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I would like to say the Scala behavior is more like the Python collection's
behavior. E.g.,
{code}
>>> i = 0
>>> map(lambda x: x + i, range(1, 10))
[1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> i += 1
>>> map(lambda x: x + i, range(1, 10))
[2, 3, 4, 5, 6, 7, 8, 9, 10]
{code}
> Scala and Python generate inconsistent results
> ----------------------------------------------
>
> Key: SPARK-13691
> URL: https://issues.apache.org/jira/browse/SPARK-13691
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.4.1, 1.5.2, 1.6.0
> Reporter: Shixiong Zhu
>
> Here is an example that Scala and Python generate different results
> {code}
> Scala:
> scala> var i = 0
> i: Int = 0
> scala> val rdd = sc.parallelize(1 to 10).map(_ + i)
> scala> rdd.collect()
> res0: Array[Int] = Array(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
> scala> i += 1
> scala> rdd.collect()
> res2: Array[Int] = Array(2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
> Python:
> >>> i = 0
> >>> rdd = sc.parallelize(range(1, 10)).map(lambda x: x + i)
> >>> rdd.collect()
> [1, 2, 3, 4, 5, 6, 7, 8, 9]
> >>> i += 1
> >>> rdd.collect()
> [1, 2, 3, 4, 5, 6, 7, 8, 9]
> {code}
> The difference is Scala will capture all variables' values when running a job
> every time, but Python just captures variables' values once and always uses
> them for all jobs.
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