Github user andrewor14 commented on the pull request:
https://github.com/apache/spark/pull/5685#issuecomment-96107937
Yes, this also affects user programs. For example I modified SparkPi to
follow the pattern I described in the PR description
```
...
val slices = if (args.length > 0) args(0).toInt else 2
(1 to 1).foreach { j =>
val count = spark.parallelize(1 until n, slices).map { i =>
val z = slices // *** This is the culprit ***
val x = random * 2 - 1
val y = random * 2 - 1
if (x * x + y * y < 1) 1 else 0
}.reduce(_ + _)
}
...
```
If you run this in master branch you will run into a task not serializable
exception. I was able to verify that this patch fixes this as long as
`spark.closureCleaner.transitive` is enabled. If this is not enabled, if fails
with the same exception as before.
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