yes I noticed that
scala> val kafkaStream = KafkaUtils.createStream(ssc, "rhes564:2181",
"rhes564:9092", "newtopic", 1)
<console>:52: error: overloaded method value createStream with alternatives:
(jssc: org.apache.spark.streaming.api.java.JavaStreamingContext,zkQuorum:
String,groupId: String,topics: java.util.Map[String,Integer],storageLevel:
org.apache.spark.storage.StorageLevel)org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream[String,String]
<and>
(ssc: org.apache.spark.streaming.StreamingContext,zkQuorum:
String,groupId: String,topics:
scala.collection.immutable.Map[String,Int],storageLevel:
org.apache.spark.storage.StorageLevel)org.apache.spark.streaming.dstream.ReceiverInputDStream[(String,
String)]
cannot be applied to (org.apache.spark.streaming.StreamingContext, String,
String, String, Int)
val kafkaStream = KafkaUtils.createStream(ssc, "rhes564:2181",
"rhes564:9092", "newtopic", 1)
Dr Mich Talebzadeh
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On 1 April 2016 at 22:25, Cody Koeninger <c...@koeninger.org> wrote:
> You're not passing valid Scala values. rhes564:2181 without quotes
> isn't a valid literal, newtopic isn't a list of strings, etc.
>
> On Fri, Apr 1, 2016 at 4:04 PM, Mich Talebzadeh
> <mich.talebza...@gmail.com> wrote:
> > Thanks Cody.
> >
> > Can I use Receiver-based Approach here?
> >
> > I have created the topic newtopic as below
> >
> > ${KAFKA_HOME}/bin/kafka-topics.sh --create --zookeeper rhes564:2181
> > --replication-factor 1 --partitions 1 --topic newtopic
> >
> >
> > This is basically what I am doing the Spark
> >
> > val lines = ssc.socketTextStream("rhes564", 2181)
> >
> > Which obviously not working
> >
> > This is what is suggested in the doc
> >
> > import org.apache.spark.streaming.kafka._
> >
> > val kafkaStream = KafkaUtils.createStream(streamingContext,
> > [ZK quorum], [consumer group id], [per-topic number of Kafka
> partitions
> > to consume])
> >
> > * <zkQuorum> is a list of one or more zookeeper servers that make
> quorum
> > * <group> is the name of kafka consumer group
> > * <topics> is a list of one or more kafka topics to consume from
> > * <numThreads> is the number of threads the kafka consumer should use
> >
> > Now this comes back with error. onviously not passing parameters
> correctly!
> >
> > scala> val kafkaStream = KafkaUtils.createStream(streamingContext,
> > rhes564:2181, rhes564:9092, newtopic 1)
> > <console>:1: error: identifier expected but integer literal found.
> > val kafkaStream = KafkaUtils.createStream(streamingContext,
> > rhes564:2181, rhes564:9092, newtopic 1)
> >
> >
> >
> >
> >
> >
> > Dr Mich Talebzadeh
> >
> >
> >
> > LinkedIn
> >
> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> >
> >
> >
> > http://talebzadehmich.wordpress.com
> >
> >
> >
> >
> > On 1 April 2016 at 21:13, Cody Koeninger <c...@koeninger.org> wrote:
> >>
> >> It looks like you're using a plain socket stream to connect to a
> >> zookeeper port, which won't work.
> >>
> >> Look at spark.apache.org/docs/latest/streaming-kafka-integration.html
> >>
> >> On Fri, Apr 1, 2016 at 3:03 PM, Mich Talebzadeh
> >> <mich.talebza...@gmail.com> wrote:
> >> >
> >> > Hi,
> >> >
> >> > I am just testing Spark streaming with Kafka.
> >> >
> >> > Basically I am broadcasting topic every minute to Host:port ->
> >> > rhes564:2181.
> >> > This is sending few lines through a shell script as follows:
> >> >
> >> > cat ${IN_FILE} | ${KAFKA_HOME}/bin/kafka-console-producer.sh
> >> > --broker-list
> >> > rhes564:9092 --topic newtopic
> >> >
> >> > That works fine and I can see the messages in
> >> >
> >> > ${KAFKA_HOME}/bin/kafka-console-consumer.sh --zookeeper rhes564:2181
> >> > --topic
> >> > newtopic
> >> >
> >> > Fri Apr 1 21:00:01 BST 2016 ======= Sending messages from rhes5
> >> >
> >> >
> 1,'OZ9062Cx22qAHo8m_fsZb16Etlq5eTnL4jYPKmgPQPyQB7Kk5IMt2xQN3yy1Qb1O3Qph16TGlHzixw02mRLAiagU0Wh17fHi5dOQ',101
> >> >
> >> >
> 2,'Py_xzno6MEWPz1bp5Cc0JBPfX90mz2uVMLPBJUWucvNPlPnVMMm81PExZ5uM0K9iEdKmleY7XFsn8O3Oxr6e07qdycvuk_lR84vI',102
> >> >
> >> >
> 3,'i2FS2ODjRBdaIpyE362JVPu4KEYSHDNTjPh46YFANquxNRK9JQT8h1W4Tph9DqGfwIgQG5ZJ8BCBklRQreyJhoLIPMbJQeH_rhN1',103
> >> >
> >> >
> 4,'Yp_q_uyH16UPTRvPdeKaslw8bhheFqqdwWaG_e8TZZ6jyscyQN556jJMxYOZjx5Zv7GV6zoa2ORsTEGcAKbKUChPFfuGAujgDkjT',104
> >> >
> >> >
> 5,'t3uuFOkNEjDE_7rc9cLbgT1o0B_jZXWsWNtmBgiC4ACffzTHUGRkl5YIZSUXB3kew2yytvB8nbCklImDa0BWxYseSbMWiKg1R9ae',105
> >> >
> >> > Now I try to see the topic in spark streaming as follows:
> >> >
> >> > val conf = new SparkConf().
> >> > setAppName("StreamTest").
> >> > setMaster("local[12]").
> >> > set("spark.driver.allowMultipleContexts", "true").
> >> > set("spark.hadoop.validateOutputSpecs", "false")
> >> > val sc = new SparkContext(conf)
> >> > // Create sqlContext based on HiveContext
> >> > val sqlContext = new HiveContext(sc)
> >> > val HiveContext = new org.apache.spark.sql.hive.HiveContext(sc)
> >> > //
> >> > // Create a local StreamingContext with two working thread and batch
> >> > interval of 1 second.
> >> > // The master requires 2 cores to prevent from a starvation scenario.
> >> > val ssc = new StreamingContext(conf, Minutes(1))
> >> > // Create a DStream that will connect to hostname:port, like
> >> > localhost:9999
> >> > //val lines = ssc.socketTextStream("rhes564", 9092)
> >> > val lines = ssc.socketTextStream("rhes564", 2181)
> >> > // Split each line into words
> >> > val words = lines.flatMap(_.split(" "))
> >> > val pairs = words.map(word => (word, 1))
> >> > val wordCounts = pairs.reduceByKey(_ + _)
> >> > // Print the first ten elements of each RDD generated in this DStream
> to
> >> > the
> >> > console
> >> > wordCounts.print()
> >> > ssc.start()
> >> >
> >> > This is what I am getting:
> >> >
> >> >
> >> > scala> -------------------------------------------
> >> > Time: 1459541760000 ms
> >> > -------------------------------------------
> >> >
> >> > But no values
> >> >
> >> > Have I got the port wrong in this case or the set up is incorrect?
> >> >
> >> >
> >> > Thanks
> >> >
> >> > Dr Mich Talebzadeh
> >> >
> >> >
> >> >
> >> > LinkedIn
> >> >
> >> >
> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
> >> >
> >> >
> >> >
> >> > http://talebzadehmich.wordpress.com
> >> >
> >> >
> >
> >
>
