Hi Silvio,

Can you go into a little detail how the back pressure work? Does it block
the receiver? Or does it temporarily saves the incoming messages in
mem/disk? I have a custom actor receiver that uses store() to save dataa
to spark. Would the back pressure make store() call block?

On 1/17/16, 10:15 AM, "Silvio Fiorito" <silvio.fior...@granturing.com>
wrote:

>It will just queue up the subsequent batches, however if this delay is
>constant you may start losing batches. It can handle spikes in processing
>time, but if you know you're consistently running over your batch
>duration you either need to increase the duration or look at enabling
>back pressure support. See:
>http://spark.apache.org/docs/latest/configuration.html#spark-streaming
>(1.5+).
>
>________________________________________
>From: pyspark2555 <scet.a...@gmail.com>
>Sent: Sunday, January 17, 2016 11:32 AM
>To: user@spark.apache.org
>Subject: Spark Streaming: BatchDuration and Processing time
>
>Hi,
>
>If BatchDuration is set to 1 second in StreamingContext and the actual
>processing time is longer than one second, then how does Spark handle
>that?
>
>For example, I am receiving a continuous Input stream. Every 1 second
>(batch
>duration), the RDDs will be processed. What if this processing time is
>longer than 1 second? What happens in the next batch duration?
>
>Thanks.
>Amit
>
>
>
>--
>View this message in context:
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>uration-and-Processing-time-tp25986.html
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