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https://issues.apache.org/jira/browse/SPARK-1305?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14066465#comment-14066465
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Denis Serduik edited comment on SPARK-1305 at 7/18/14 4:00 PM:
---------------------------------------------------------------

I'm interested in using this feature especially with SchemeRDD to be able cache 
intermediate  results.
Where I can find some code examples how to use it ? 
>From SparkContext's code I see the following: 

  private[spark] def persistRDD(rdd: RDD[_]) {
    persistentRdds(rdd.id) = rdd
  }

  /**
   * Unpersist an RDD from memory and/or disk storage
   */
  private[spark] def unpersistRDD(rddId: Int, blocking: Boolean = true) {
    env.blockManager.master.removeRdd(rddId, blocking)
    persistentRdds.remove(rddId)
    listenerBus.post(SparkListenerUnpersistRDD(rddId))
  }

So  persist don't put RDD into tachyonStore of blockmanager ? How does this 
feature work ? 



was (Author: dmaverick):
I'm interesting in using this feature especially with SchemeRDD to be able 
cache intermediate  results.
Where I can find some code examples how to use it ? 
>From SparkContext's code I see the following: 

  private[spark] def persistRDD(rdd: RDD[_]) {
    persistentRdds(rdd.id) = rdd
  }

  /**
   * Unpersist an RDD from memory and/or disk storage
   */
  private[spark] def unpersistRDD(rddId: Int, blocking: Boolean = true) {
    env.blockManager.master.removeRdd(rddId, blocking)
    persistentRdds.remove(rddId)
    listenerBus.post(SparkListenerUnpersistRDD(rddId))
  }

So  persist don't put RDD into tachyonStore of blockmanager ? How does this 
feature work ? 


> Support persisting RDD's directly to Tachyon
> --------------------------------------------
>
>                 Key: SPARK-1305
>                 URL: https://issues.apache.org/jira/browse/SPARK-1305
>             Project: Spark
>          Issue Type: New Feature
>          Components: Block Manager
>            Reporter: Patrick Wendell
>            Assignee: Haoyuan Li
>            Priority: Blocker
>             Fix For: 1.0.0
>
>
> This is already an ongoing pull request - in a nutshell we want to support 
> Tachyon as a storage level in Spark.



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