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 <mboe...@gmail.com> 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] 
> https://github.com/apache/systemml/blob/master/src/main/java/org/apache/sysml/runtime/instructions/spark/MatrixIndexingSPInstruction.java#L603
> Regards,
> Matthias
> On Sat, Apr 14, 2018 at 3:12 PM, Thodoris Zois <z...@ics.forth.gr> 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
>> ---------------------------------------------------------------------
>> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org

To unsubscribe e-mail: dev-unsubscr...@spark.apache.org

Reply via email to