You are viewing a plain text version of this content. The canonical link for it is here.
Posted to jira@kafka.apache.org by "Konstantine Karantasis (Jira)" <ji...@apache.org> on 2021/07/08 22:00:06 UTC

[jira] [Updated] (KAFKA-6718) Rack Aware Stand-by Task Assignment for Kafka Streams

     [ https://issues.apache.org/jira/browse/KAFKA-6718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Konstantine Karantasis updated KAFKA-6718:
------------------------------------------
    Fix Version/s:     (was: 3.0.0)
                   3.1.0

> Rack Aware Stand-by Task Assignment for Kafka Streams
> -----------------------------------------------------
>
>                 Key: KAFKA-6718
>                 URL: https://issues.apache.org/jira/browse/KAFKA-6718
>             Project: Kafka
>          Issue Type: New Feature
>          Components: streams
>            Reporter: Deepak Goyal
>            Assignee: Levani Kokhreidze
>            Priority: Major
>              Labels: kip
>             Fix For: 3.1.0
>
>
> |Machines in data centre are sometimes grouped in racks. Racks provide isolation as each rack may be in a different physical location and has its own power source. When tasks are properly replicated across racks, it provides fault tolerance in that if a rack goes down, the remaining racks can continue to serve traffic.
>   
>  This feature is already implemented at Kafka [KIP-36|https://cwiki.apache.org/confluence/display/KAFKA/KIP-36+Rack+aware+replica+assignment] but we needed similar for task assignments at Kafka Streams Application layer. 
>   
>  This features enables replica tasks to be assigned on different racks for fault-tolerance.
>  NUM_STANDBY_REPLICAS = x
>  totalTasks = x+1 (replica + active)
>  # If there are no rackID provided: Cluster will behave rack-unaware
>  # If same rackId is given to all the nodes: Cluster will behave rack-unaware
>  # If (totalTasks <= number of racks), then Cluster will be rack aware i.e. each replica task is each assigned to a different rack.
>  # Id (totalTasks > number of racks), then it will first assign tasks on different racks, further tasks will be assigned to least loaded node, cluster wide.|
> We have added another config in StreamsConfig called "RACK_ID_CONFIG" which helps StickyPartitionAssignor to assign tasks in such a way that no two replica tasks are on same rack if possible.
>  Post that it also helps to maintain stickyness with-in the rack.|



--
This message was sent by Atlassian Jira
(v8.3.4#803005)