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From "Aditya" <aditya.calangut...@augmentiq.co.in>
Subject Re: Spark RDD and Memory
Date Fri, 23 Sep 2016 04:53:57 GMT
Thanks for the reply.

One more question.
How spark handles data if it does not fit in memory? The answer which I 
got is that it flushes the data to disk and handle the memory issue.
Plus in below example.
val textFile = sc.textFile("/user/emp.txt")
val textFile1 = sc.textFile("/user/emp1.xt")
val join = textFile.join(textFile1)
join.saveAsTextFile("/home/output")
val count = join.count()

When the first action is performed it loads textFile and textFile1 in 
memory, performes join and save the result.
But when the second action (count) is called, it again loads textFile 
and textFile1 in memory and again performs the join operation?
If it loads again what is the correct way to prevent it from loading 
again again the same data?

On Thursday 22 September 2016 11:12 PM, Mich Talebzadeh wrote:
> Hi,
>
> unpersist works on storage memory not execution memory. So I do not 
> think you can flush it out of memory if you have not cached it using 
> cache or something like below in the first place.
>
> s.persist(org.apache.spark.storage.StorageLevel.MEMORY_ONLY)
>
> s.unpersist
>
> I believe the recent versions of Spark deploy Least Recently Used 
> (LRU) mechanism to flush unused data out of memory much like RBMS 
> cache management. I know LLDAP does that.
>
> HTH
>
>
>
> Dr Mich Talebzadeh
>
> LinkedIn 
> /https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw/
>
> http://talebzadehmich.wordpress.com
>
>
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>
> On 22 September 2016 at 18:09, Hanumath Rao Maduri <hanu.ncr@gmail.com 
> <mailto:hanu.ncr@gmail.com>> wrote:
>
>     Hello Aditya,
>
>     After an intermediate action has been applied you might want to
>     call rdd.unpersist() to let spark know that this rdd is no longer
>     required.
>
>     Thanks,
>     -Hanu
>
>     On Thu, Sep 22, 2016 at 7:54 AM, Aditya
>     <aditya.calangutkar@augmentiq.co.in
>     <mailto:aditya.calangutkar@augmentiq.co.in>> wrote:
>
>         Hi,
>
>         Suppose I have two RDDs
>         val textFile = sc.textFile("/user/emp.txt")
>         val textFile1 = sc.textFile("/user/emp1.xt")
>
>         Later I perform a join operation on above two RDDs
>         val join = textFile.join(textFile1)
>
>         And there are subsequent transformations without including
>         textFile and textFile1 further and an action to start the
>         execution.
>
>         When action is called, textFile and textFile1 will be loaded
>         in memory first. Later join will be performed and kept in memory.
>         My question is once join is there memory and is used for
>         subsequent execution, what happens to textFile and textFile1
>         RDDs. Are they still kept in memory untill the full lineage
>         graph is completed or is it destroyed once its use is over? If
>         it is kept in memory, is there any way I can explicitly remove
>         it from memory to free the memory?
>
>
>
>
>
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