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From Rohit Pujari <rpuj...@hortonworks.com>
Subject Re: Spark Streaming
Date Sat, 17 Jan 2015 10:37:16 GMT
That was it. Thanks Akhil and Owen for your quick response.

On Sat, Jan 17, 2015 at 4:27 AM, Sean Owen <sowen@cloudera.com> wrote:

> Not print(kafkaStream), which would just print some String description
> of the stream to the console, but kafkaStream.print(), which actually
> invokes the print operation on the stream.
>
> On Sat, Jan 17, 2015 at 10:17 AM, Rohit Pujari <rpujari@hortonworks.com>
> wrote:
> > Hi Francois:
> >
> > I tried using "print(kafkaStream)” as output operator but no luck. It
> throws
> > the same error. Any other thoughts?
> >
> > Thanks,
> > Rohit
> >
> >
> > From: "francois.garillot@typesafe.com" <francois.garillot@typesafe.com>
> > Date: Saturday, January 17, 2015 at 4:10 AM
> > To: Rohit Pujari <rpujari@hortonworks.com>
> > Subject: Re: Spark Streaming
> >
> > Streams are lazy. Their computation is triggered by an output operator,
> > which is apparently missing from your code. See the programming guide:
> >
> >
> https://spark.apache.org/docs/latest/streaming-programming-guide.html#output-operations-on-dstreams
> >
> > —
> > FG
> >
> >
> > On Sat, Jan 17, 2015 at 11:06 AM, Rohit Pujari <rpujari@hortonworks.com>
> > wrote:
> >>
> >> Hello Folks:
> >>
> >> I'm running into following error while executing relatively straight
> >> forward spark-streaming code. Am I missing anything?
> >>
> >> Exception in thread "main" java.lang.AssertionError: assertion failed:
> No
> >> output streams registered, so nothing to execute
> >>
> >>
> >> Code:
> >>
> >> val conf = new SparkConf().setMaster("local[2]").setAppName("Streams")
> >>     val ssc = new StreamingContext(conf, Seconds(1))
> >>
> >>     val kafkaStream = {
> >>       val sparkStreamingConsumerGroup = "spark-streaming-consumer-group"
> >>       val kafkaParams = Map(
> >>         "zookeeper.connect" ->
> "node1.c.emerald-skill-783.internal:2181",
> >>         "group.id" -> "twitter",
> >>         "zookeeper.connection.timeout.ms" -> "1000")
> >>       val inputTopic = "twitter"
> >>       val numPartitionsOfInputTopic = 2
> >>       val streams = (1 to numPartitionsOfInputTopic) map { _ =>
> >>         KafkaUtils.createStream(ssc, kafkaParams, Map(inputTopic -> 1),
> >> StorageLevel.MEMORY_ONLY_SER)
> >>       }
> >>       val unifiedStream = ssc.union(streams)
> >>       val sparkProcessingParallelism = 1
> >>       unifiedStream.repartition(sparkProcessingParallelism)
> >>     }
> >>
> >>     //print(kafkaStream)
> >>     ssc.start()
> >>     ssc.awaitTermination()
> >>
> >> --
> >> Rohit Pujari
> >>
> >>
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> >
> >
> >
> > CONFIDENTIALITY NOTICE
> > NOTICE: This message is intended for the use of the individual or entity
> to
> > which it is addressed and may contain information that is confidential,
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> any
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>



-- 
Rohit Pujari
Solutions Engineer, Hortonworks
rpujari@hortonworks.com
716-430-6899

-- 
CONFIDENTIALITY NOTICE
NOTICE: This message is intended for the use of the individual or entity to 
which it is addressed and may contain information that is confidential, 
privileged and exempt from disclosure under applicable law. If the reader 
of this message is not the intended recipient, you are hereby notified that 
any printing, copying, dissemination, distribution, disclosure or 
forwarding of this communication is strictly prohibited. If you have 
received this communication in error, please contact the sender immediately 
and delete it from your system. Thank You.

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