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From "Ilya Ganelin (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-1962) Add RDD cache reference counting
Date Tue, 02 Dec 2014 03:16:12 GMT

    [ https://issues.apache.org/jira/browse/SPARK-1962?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14230908#comment-14230908
] 

Ilya Ganelin commented on SPARK-1962:
-------------------------------------

Patrick Wendell - is this a reasonable thing to implement? I could knock this out. 


> Add RDD cache reference counting
> --------------------------------
>
>                 Key: SPARK-1962
>                 URL: https://issues.apache.org/jira/browse/SPARK-1962
>             Project: Spark
>          Issue Type: New Feature
>          Components: Spark Core
>    Affects Versions: 1.0.0
>            Reporter: Taeyun Kim
>            Priority: Minor
>
> It would be nice if the RDD cache() method incorporate a reference counting information.
> That is,
> {code}
> void test()
> {
>     JavaRDD<...> rdd = ...;
>     rdd.cache();  // to reference count 1. actual caching happens.
>     rdd.cache();  // to reference count 2. Nop as long as the storage level is the same.
Else, exception.
>     ...
>     rdd.uncache();  // to reference count 1. Nop.
>     rdd.uncache();  // to reference count 0. Actual unpersist happens.
> }
> {code}
> This can be useful when writing code in modular way.
> When a function receives an RDD as an argument, it doesn't necessarily know the cache
status of the RDD.
> But it could want to cache the RDD, since it will use the RDD multiple times.
> But with the current RDD API, it cannot determine whether it should unpersist it or leave
it alone (so that the caller can continue to use that RDD without rebuilding).
> For API compatibility, introducing a new method or adding a parameter may be required.



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