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From Khanderao Kand Gmail <>
Subject Re: Spark streaming alerting
Date Mon, 23 Mar 2015 09:22:10 GMT

You are right in tour answer to what Mohit wrote. However what Mohit seems to be alluring
but did not write properly might be different.


You are wrong in saying "generally" streaming works in HDFS and cassandra . Streaming typically
works with streaming or queing source like Kafka, kinesis, Twitter, flume, zeroMQ, etc (but
can also from HDFS and S3 ) However , streaming context ( "receiver" wishing the streaming
context ) gets events/messages/records and forms a time window based batch (RDD)- 

So there is a maximum gap of window time from alert message was available to spark and when
the processing happens. I think you meant about this. 

As per spark programming model, RDD is the right way to deal with data.  If you are fine with
the minimum delay of say a sec (based on min time window that dstreaming can support) then
what Rohit gave is a right model. 


> On Mar 22, 2015, at 11:39 PM, Akhil Das <> wrote:
> What do you mean you can't send it directly from spark workers? Here's a simple approach
which you could do:
>     val data = ssc.textFileStream("sigmoid/")
>     val dist = data.filter(_.contains("ERROR")).foreachRDD(rdd => alert("Errors :"
+ rdd.count()))
> And the alert() function could be anything triggering an email or sending an SMS alert.
> Thanks
> Best Regards
>> On Sun, Mar 22, 2015 at 1:52 AM, Mohit Anchlia <> wrote:
>> Is there a module in spark streaming that lets you listen to the alerts/conditions
as they happen in the streaming module? Generally spark streaming components will execute
on large set of clusters like hdfs or Cassandra, however when it comes to alerting you generally
can't send it directly from the spark workers, which means you need a way to listen to the

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