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https://issues.apache.org/jira/browse/SAMZA-334?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14062821#comment-14062821
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Martin Kleppmann commented on SAMZA-334:
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bq. How to detect bottlenecks. One can look at system metrics (memory or CPU 
utilization), but it also may be useful to look at more application level 
metrics

My hunch would be that the most useful metric would be processing lag (how much 
of a queue of unprocessed messages has built up in front of a stream 
processor), and whether the queue is growing or shrinking. Even in the absence 
of an auto-scaling mechanism, that would be a useful operational metric to have.

> Need for asymmetric container config
> ------------------------------------
>
>                 Key: SAMZA-334
>                 URL: https://issues.apache.org/jira/browse/SAMZA-334
>             Project: Samza
>          Issue Type: Improvement
>          Components: container
>    Affects Versions: 0.8.0
>            Reporter: Chinmay Soman
>
> The current (and upcoming) partitioning scheme(s) suggest that there might be 
> a skew in the amount of data ingested and computation performed across 
> different containers for a given Samza job. This directly affects the amount 
> of resources required by a container - which today are completely symmetric.
> Case A] Partitioning on Kafka partitions
> For instance, consider a partitioner job which reads data from different 
> Kafka topics (having different partition layouts). In this case, its possible 
> that a lot of topics have a smaller number of Kafka partitions. Consequently 
> the containers processing these partitions would need more resources than 
> those responsible for the higher numbered partitions. 
> Case B] Partitioning based on Kafka topics
> Even in this case, its very easy for some containers to be doing more work 
> than others - leading to a skew in resource requirements.
> Today, the container config is based on the requirements for the worst (doing 
> the most work) container. Needless to say, this leads to resource wastage. A 
> better approach needs to consider what is the true requirement per container 
> (instead of per job).



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