Actually this code is producing error leader not found exception. I am
unable to find the reason

On Mon, Jan 12, 2015 at 4:03 PM, kevinkim [via Apache Spark User List] <
ml-node+s1001560n21098...@n3.nabble.com> wrote:

> Well, you can use coalesce() to decrease number of partition to 1.
> (It will take time and quite not efficient, tough)
>
> Regards,
> Kevin.
>
> On Mon Jan 12 2015 at 7:57:39 PM Hafiz Mujadid [via Apache Spark User
> List] <[hidden email]
> <http:///user/SendEmail.jtp?type=node&node=21098&i=0>> wrote:
>
>> Hi experts!
>>
>>
>> I have a schemaRDD of messages to be pushed in kafka. So I am using
>> following piece of code to do that
>>
>> rdd.foreachPartition(itr => {
>>                                 val props = new Properties()
>>                                 props.put("metadata.broker.list",
>> brokersList)
>>                                 props.put("serializer.class",
>> "kafka.serializer.StringEncoder")
>>                                 props.put("compression.codec",
>> codec.toString)
>>                                 props.put("producer.type", "sync")
>>                                 props.put("batch.num.messages",
>> BatchSize.toString)
>>                                 props.put("message.send.max.retries",
>> maxRetries.toString)
>>                                 props.put("request.required.acks", "-1")
>>                                 producer = new Producer[String,
>> String](new ProducerConfig(props))
>>                                 itr.foreach(row => {
>>                                         val msg =
>> row.toString.drop(1).dropRight(1)
>>                                         this.synchronized {
>>                                                 producer.send(new
>> KeyedMessage[String, String](Topic, msg))
>>                                         }
>>                                 })
>>                                 producer.close
>>                         })
>>
>>
>>
>> the problem with this code is that it creates kafka producer separate for
>> each partition and I want a single producer for all partitions. Is there
>> any way to achieve this?
>>
>>
>> ------------------------------
>>  If you reply to this email, your message will be added to the
>> discussion below:
>>
>> http://apache-spark-user-list.1001560.n3.nabble.com/creating-a-single-kafka-producer-object-for-all-partitions-tp21097.html
>>  To unsubscribe from Apache Spark User List, click here.
>> NAML
>> <http://apache-spark-user-list.1001560.n3.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml>
>>
>
>
> ------------------------------
>  If you reply to this email, your message will be added to the discussion
> below:
>
> http://apache-spark-user-list.1001560.n3.nabble.com/creating-a-single-kafka-producer-object-for-all-partitions-tp21097p21098.html
>  To unsubscribe from creating a single kafka producer object for all
> partitions, click here
> <http://apache-spark-user-list.1001560.n3.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=21097&code=aGFmaXptdWphZGlkMDBAZ21haWwuY29tfDIxMDk3fC05MjEzOTMxMTE=>
> .
> NAML
> <http://apache-spark-user-list.1001560.n3.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml>
>



-- 
Regards: HAFIZ MUJADID




--
View this message in context: 
http://apache-spark-user-list.1001560.n3.nabble.com/creating-a-single-kafka-producer-object-for-all-partitions-tp21097p21099.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.

Reply via email to