Hi Manjul,

Each StreamingContext will have its own batch size. If that doesn’t work 
for the different sources you have then you would have to create different 
streaming apps. You can only create a new StreamingContext in the same 
Spark app, once you’ve stopped the previous one.

Spark certainly supports multiple streams within the same streaming app. 
In fact if the ingest rate of your stream is very high you can create 
multiple receivers and union the streams.

Just remember that each receiver will require a core. The receivers will 
be distributed appropriately across your executors.

Thanks,
Silvio




On 1/6/15, 7:11 PM, "manjuldixit" <manjul.di...@kronos.com> wrote:

>Hi,
>
>We have a requirement of receiving live input messages from RabbitMQ and
>process them into micro batches. For this we have selected SparkStreaming
>and we have written a connector for RabbitMQ receiver and Spark streaming,
>it is working fine. 
>
>Now the main requirement is to receive different category of events from
>different channels/queues in a spark streaming context.
>
>Q1 : So how can I create different streaming context to receive message 
>from
>different source (may or may not be in same frequency) within a Spark
>context? 
>
>Q2: Is is advisable to use single StreamingContext to create different 
>input
>streams from different sources?
>
>Q3: What all design consideration I need to take care in terms of 
>specifying
>no of Cores for Spark master.
>
>Q4: Is there a was to distribute different Streaming receiving task to
>different workers ?
>
>You suggestions will be very valuable in my application design and if you
>can have some example for complex application which you can share may some
>URL reference or whatever ; it is very appreciated.
>
>Thanks 
>Manjul  
>
>
>
>   
>
>
>
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