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https://issues.apache.org/jira/browse/SPARK-14064?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15205994#comment-15205994
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Jian Chen commented on SPARK-14064:
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I should sort the key before zipWithIndex as the memory occupied by the dataID
is released and zipWithIndex can't ensure the same result for every execution
> count method of RDD doesn't take action
> ---------------------------------------
>
> Key: SPARK-14064
> URL: https://issues.apache.org/jira/browse/SPARK-14064
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.1
> Environment: CentOS-6.1
> Reporter: Jian Chen
> Fix For: 1.6.1
>
> Original Estimate: 1h
> Remaining Estimate: 1h
>
> I have some unique keys stored as RDD[Int] , then I use zipWithIndex to give
> an unique ID to every key.
> val dataID = data.zipWithIndex()
> Then I count the num :
> dataID.count
> At last, I save the dataID as textFile to HDFS.
> I save the data for three times as d1, d2 ,d2, but I find each result is
> different.
> dataID.saveAsTextFile("d1")
> dataID.saveAsTextFile("d2")
> dataID.saveAsTextFile("d3")
> For example
> The key 13552359 has an ID 187480 in d1, but has an another ID 187483 in d2.
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