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From Aniket Bhatnagar <aniket.bhatna...@gmail.com>
Subject Re: Execute function once on each node
Date Tue, 19 Jul 2016 06:42:28 GMT
Thanks for the explanation. Try creating a custom RDD whose getPartitions
returns an array of custom partition objects of size n (= number of nodes).
In a custom partition object, you can have the file path and ip/hostname
where the partition needs to be computed. Then, have getPreferredLocations
return the ip/hostname from the partition object and in compute function,
assert that you are in right ip/hostname (or fail) and read the content of
the file.

Not a 100% sure it will work though.

On Tue, Jul 19, 2016, 2:54 AM Josh Asplund <joshasplund@gmail.com> wrote:

> The spark workers are running side-by-side with scientific simulation
> code. The code writes output to local SSDs to keep latency low. Due to the
> volume of data being moved (10's of terabytes +), it isn't really feasible
> to copy the data to a global filesystem. Executing a function on each node
> would allow us to read the data in situ without a copy.
>
> I understand that manually assigning tasks to nodes reduces fault
> tolerance, but the simulation codes already explicitly assign tasks, so a
> failure of any one node is already a full-job failure.
>
> On Mon, Jul 18, 2016 at 3:43 PM Aniket Bhatnagar <
> aniket.bhatnagar@gmail.com> wrote:
>
>> You can't assume that the number to nodes will be constant as some may
>> fail, hence you can't guarantee that a function will execute at most once
>> or atleast once on a node. Can you explain your use case in a bit more
>> detail?
>>
>> On Mon, Jul 18, 2016, 10:57 PM joshuata <joshasplund@gmail.com> wrote:
>>
>>> I am working on a spark application that requires the ability to run a
>>> function on each node in the cluster. This is used to read data from a
>>> directory that is not globally accessible to the cluster. I have tried
>>> creating an RDD with n elements and n partitions so that it is evenly
>>> distributed among the n nodes, and then mapping a function over the RDD.
>>> However, the runtime makes no guarantees that each partition will be
>>> stored
>>> on a separate node. This means that the code will run multiple times on
>>> the
>>> same node while never running on another.
>>>
>>> I have looked through the documentation and source code for both RDDs and
>>> the scheduler, but I haven't found anything that will do what I need.
>>> Does
>>> anybody know of a solution I could use?
>>>
>>>
>>>
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