[
https://issues.apache.org/jira/browse/SPARK-7661?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14547642#comment-14547642
]
Murtaza Kanchwala commented on SPARK-7661:
------------------------------------------
Yes, it works I took 4 + 4 = 8 cores, where 4 is my total no. of cores and 4 is
my total no .of shards.
But there is still an another thing, Now If the Spark Consumer starts up it
takes 1 executor and 4 Network Receiver, when I Scale up my Kinesis Stream by 4
more shards,i.e. 8 Shards, then it also works but the Receiver count is still
4. So is there any way to scale up the receivers or not?
> Support for dynamic allocation of executors in Kinesis Spark Streaming
> ----------------------------------------------------------------------
>
> Key: SPARK-7661
> URL: https://issues.apache.org/jira/browse/SPARK-7661
> Project: Spark
> Issue Type: New Feature
> Components: Streaming
> Affects Versions: 1.3.1
> Environment: AWS-EMR
> Reporter: Murtaza Kanchwala
>
> Currently the no. of cores is (N + 1), where N is no. of shards in a Kinesis
> Stream.
> My Requirement is that if I use this Resharding util for Amazon Kinesis :
> Amazon Kinesis Resharding :
> https://github.com/awslabs/amazon-kinesis-scaling-utils
> Then there should be some way to allocate executors on the basis of no. of
> shards directly (for Spark Streaming only).
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
