Sorry, I just said that I NEED to manage offsets, so in case of Kafka Direct 
Stream , how can I handle this ? 
Update Zookeeper manually ? why not but any other solutions ?

----- Mail original -----
De: "Cody Koeninger" <c...@koeninger.org>
À: "Nicolas Biau" <nib...@free.fr>
Cc: "user" <user@spark.apache.org>
Envoyé: Vendredi 2 Octobre 2015 18:29:09
Objet: Re: Spark Streaming over YARN


Neither of those statements are true. 
You need more receivers if you want more parallelism. 
You don't have to manage offset positioning with the direct stream if you don't 
want to, as long as you can accept the limitations of Spark checkpointing. 


On Fri, Oct 2, 2015 at 10:52 AM, < nib...@free.fr > wrote: 


>From my understanding as soon as I use YARN I don't need to use parrallelisme 
>(at least for RDD treatment) 
I don't want to use direct stream as I have to manage the offset positionning 
(in order to be able to start from the last offset treated after a spark job 
failure) 


----- Mail original ----- 
De: "Cody Koeninger" < c...@koeninger.org > 
À: "Nicolas Biau" < nib...@free.fr > 
Cc: "user" < user@spark.apache.org > 
Envoyé: Vendredi 2 Octobre 2015 17:43:41 
Objet: Re: Spark Streaming over YARN 




If you're using the receiver based implementation, and want more parallelism, 
you have to create multiple streams and union them together. 


Or use the direct stream. 


On Fri, Oct 2, 2015 at 10:40 AM, < nib...@free.fr > wrote: 


Hello, 
I have a job receiving data from kafka (4 partitions) and persisting data 
inside MongoDB. 
It works fine, but when I deploy it inside YARN cluster (4 nodes with 2 cores) 
only on node is receiving all the kafka partitions and only one node is 
processing my RDD treatment (foreach function) 
How can I force YARN to use all the resources nodes and cores to process the 
data (receiver & RDD treatment) 

Tks a lot 
Nicolas 

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