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From Akhil Das <ak...@sigmoidanalytics.com>
Subject Re: Compute Real-time Visualizations using spark streaming
Date Sun, 11 Oct 2015 17:46:10 GMT
Simplest approach would be to push the streaming data (after the
computations) to a SQL-Like DB and then let your visualization piece pull
it from the DB. Another approach would be to make your visualization piece
a web-socket (If you are using D3JS etc) and then from your streaming
application you can push the data to the web-socket which will power the
dashboards.

Thanks
Best Regards

On Fri, Oct 2, 2015 at 5:17 PM, Sureshv <suresh.kumar@transerainc.com>
wrote:

> Hi,
>
>  I am new to Spark and I would like know how to compute (dynamically)
> real-time visualizations using Spark streaming (Kafka).
>
> Use case : We have Real-time analytics dashboard (reports and dashboard),
> user can define report (visualization) with certain parameters like,
> refresh
> period, choose various metrics (segment variables & profile variables).
>
> We should compute only visualizations those are in use (users are
> accessing)
> with events coming from kafka streams using Spark streaming.
>
> Solution : One way of doing is compute visualizations for every incoming
> message and write back into result streams and application which consume
> the
> processed data/result streams.
>
> I would like to know is there any better approach? Please advice me here.
>
> Thanks,
> Suresh
>
>
>
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