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From Thodoris Zois <>
Subject Re: Isolate 1 partition and perform computations
Date Sat, 14 Apr 2018 22:59:59 GMT
I forgot to mention that I would like my approach to be independent from the application that
user is going to submit to Spark. 

Assume that I don’t know anything about user’s application… I expected to find a simpler
approach. I saw in RDD.scala that an RDD is characterized by a list of partitions. If I modify
this list and keep only one partition, is it going to work? 
- Thodoris

> On 15 Apr 2018, at 01:40, Matthias Boehm <> wrote:
> you might wanna have a look into using a PartitionPruningRDD to select
> a subset of partitions by ID. This approach worked very well for
> multi-key lookups for us [1].
> A major advantage compared to scan-based operations is that, if your
> source RDD has an existing partitioner, only relevant partitions are
> accessed.
> [1]
> Regards,
> Matthias
> On Sat, Apr 14, 2018 at 3:12 PM, Thodoris Zois <> wrote:
>> Hello list,
>> I am sorry for sending this message here, but I could not manage to get any response
in “users”. For specific purposes I would like to isolate 1 partition of the RDD and perform
computations only to this.
>> For instance, suppose that a user asks Spark to create 500 partitions for the RDD.
I would like Spark to create the partitions but perform computations only in one partition
from those 500 ignoring the other 499.
>> At first I tried to modify executor in order to run only 1 partition (task) but I
didn’t manage to make it work. Then I tried the DAG Scheduler but I think that I should
modify the code in a higher level and let Spark make the partitioning but at the end see only
one partition and throw throw away all the others.
>> My question is which file should I modify in order to achieve isolating 1 partition
of the RDD? Where does the actual partitioning is made?
>> I hope it is clear!
>> Thank you very much,
>> Thodoris
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