Thanks so much for your response Bobby.I have been reading this link for a 
while, and researching its details.Apache Flink 0.10.2 Documentation: Storm 
Compatibility

  
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Apache Flink 0.10.2 Documentation: Storm Compatibility
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I have not started to port our Storm app to Beam yest.But am going to start 
soon once I execute a FlinkRunner Beam app in my lab cluster LOL!Its getting 
there...
Question to the community: Is this link above the latest & the greatest on 
porting Storm to Beam (Flink or Spark).Cheers

      From: Bobby Evans <[email protected]>
 To: [email protected]; amir bahmanyari <[email protected]> 
 Sent: Wednesday, May 11, 2016 1:56 PM
 Subject: Re: Beam and Storm
   
Amir,
I am kind of new at this so I might be wrong, but in general if your bolts are 
stateless then they would translate directly into ParDos one to one.  The 
spouts are more complex and you would want to find an existing unbounded 
source, or you would have to write one.
I don't know if there are any custom groupings in BEAM, there doesn't appear to 
be, but in general a shuffle grouping would become a noop, a fields grouping 
becomes a GroupByKey transform.
If your bolts are stateful you need to find a way using windowing and 
aggregation to produce an equivalent result.

If you are using trident, it is similar all functions become ParDos.  The thing 
here is that for the state you need to find an equivalent output ParDo, or you 
need to write one.
- Bobby

On Wed, May 11, 2016 at 3:37 PM amir bahmanyari <[email protected]> 
wrote:

Is there a guideline on how to port an existing Storm code to Beam?Thanks

      From: Bobby Evans <[email protected]>
 To: [email protected]
 Sent: Wednesday, May 11, 2016 1:25 PM
 Subject: Re: Beam and Storm

Thanks for the quick response.  I'll keep digging.

On Wed, May 11, 2016 at 3:14 PM Dan Halperin <[email protected]>
wrote:

> Hi Bobby,
>
> You are correct that unbounded sinks are currently implemented as
> PTransforms that interact with an external service in a ParDo. Even bounded
> sinks are implemented this way -- look at the internals of the Write
> transform -- the sink class itself is just a convenience wrapper for one
> common pattern.
>
> Thanks,
> Dan
>
> On Wed, May 11, 2016 at 1:00 PM, Bobby Evans <[email protected]> wrote:
>
> > I have been trying to get my head wrapped around some of the internals of
> > beam so I can come up with an architecture/plan for STORM-1757
> > <https://issues.apache.org/jira/browse/STORM-1757> / BEAM-9
> > <https://issues.apache.org/jira/browse/BEAM-9>.
> >
> > I see that there are Sources and Sinks.  Sources can be unbounded, but
> > there appears to be no equivalent to an unbounded Sink.  What I do find
> are
> > things like WriteToBigQuery which despite some internal complexity ends
> up
> > being an idempotent transform producing a PDone.  Is this the intended
> way
> > for data to be output from a streaming DAG?
> >
> > I will likely have more questions as I dig more into state checkpointing,
> > etc.
> >
> > Thanks,
> >
> > Bobby Evans
> >
>


  


  

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