[jira] [Commented] (SPARK-8666) checkpointing does not take advantage of persisted/cached RDDs

["Glenn Strycker (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-8666?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14603175#comment-14603175 ] 

Glenn Strycker commented on SPARK-8666:
---------------------------------------

I added a stackoverflow question to parallel this ticket:  http://stackoverflow.com/questions/31078350/spark-rdd-checkpoint-on-persisted-cached-rdds-are-performing-the-dag-twice

One idea I had is that maybe I have to "materialize" twice?

{noformat}
// this will create the RDD and cache, when materialized
val newRDD = prevRDD.map(a => (a._1, 1L)).distinct.persist(StorageLevel.MEMORY_AND_DISK_SER)
print(newRDD.count())

// will this now checkpoint FROM THE EXISTING CACHE IN MEMORY?
newRDD.checkpoint
print(newRDD.count())
{noformat}

> checkpointing does not take advantage of persisted/cached RDDs
> --------------------------------------------------------------
>
>                 Key: SPARK-8666
>                 URL: https://issues.apache.org/jira/browse/SPARK-8666
>             Project: Spark
>          Issue Type: New Feature
>            Reporter: Glenn Strycker
>
> I have been noticing that when checkpointing RDDs, all operations are occurring TWICE.
> For example, when I run the following code and watch the stages...
> {noformat}
> val newRDD = prevRDD.map(a => (a._1, 1L)).distinct.persist(StorageLevel.MEMORY_AND_DISK_SER)
> newRDD.checkpoint
> print(newRDD.count())
> {noformat}
> I see distinct and count operations appearing TWICE, and shuffle disk writes and reads (from the distinct) occurring TWICE.
> My newRDD is persisted to memory, why can't the checkpoint simply save those partitions to disk when the first operations have completed?



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