Thanks, Tim - I think I understand. You are proposing to do things at the
operator level, rather than at the DAG level.

B could then have 6 parallel partitions, some of which process the same
data simultaneously.
X1
X1
X2
X2
X3
X3

In this scenario, is it possible for the OPERATOR to fail terminating all
the pipelines or is it only possible for an individual physical pipeline
to fail - therefore not affecting the others?

On 9/23/15, 11:48 AM, "Timothy Farkas" <[email protected]> wrote:

>Hi Ilya,
>
>There are two ways to do this. You can do normal N x N partitioning, but
>write a partitioner for B which assigns the same partition keys to M
>operators in a partitioning. Then M partitions will receive the same data:
>An example of setting partition keys in a partitioner is here:
>
>https://github.com/apache/incubator-apex-core/blob/devel-3/common/src/main
>/java/com/datatorrent/common/partitioner/StatelessPartitioner.java
>
>An easier way is this:
>
>dag.addStream(“NAME”, A.output, B.input, C.input);
>
>You have to put all the input ports you want to receive the same data in
>the same stream declaration.
>
>Tim
>
>On Wed, Sep 23, 2015 at 7:39 AM, Ganelin, Ilya
><[email protected]>
>wrote:
>
>> Ram, thank you. I think this is a good starting point, however it
>>requires
>> having access to the stream at creation time (as well as the operator
>> being added). I¹d ideally like to create a function:
>>
>> static void parallelize(DAG dag);
>>
>> This function would take the head of the DAG, and parallelize all
>> downstream operators. It looks like at the moment, there is no interface
>> within DAG to provide access to its operators or streams. Does such an
>> interface exist or is this something I would need to expose? Was there a
>> design decision to not expose these?
>>
>>
>> On 9/23/15, 11:26 AM, "Munagala Ramanath" <[email protected]> wrote:
>>
>> >l
>>
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