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https://issues.apache.org/jira/browse/KAFKA-3101?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15374085#comment-15374085
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Bill Bejeck commented on KAFKA-3101:
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[~enothereska] [~guozhang]
With regards to the performance comparison here is my plan:
Create a simple streams process with KTableAggregate utilizing
Objects(records) first then bytes.
Track the memory usage via the jamm library referenced above.
Track message throughput for both types (records vs bytes).
Profile how much CPU time is spent in the serialization/deserialization
process.
Is this reasonable? Any additional thoughts or comments?
> Optimize Aggregation Outputs
> ----------------------------
>
> Key: KAFKA-3101
> URL: https://issues.apache.org/jira/browse/KAFKA-3101
> Project: Kafka
> Issue Type: Improvement
> Components: streams
> Reporter: Guozhang Wang
> Labels: architecture
> Fix For: 0.10.1.0
>
>
> Today we emit one output record for each incoming message for Table /
> Windowed Stream Aggregations. For example, say we have a sequence of
> aggregate outputs computed from the input stream (assuming there is no agg
> value for this key before):
> V1, V2, V3, V4, V5
> Then the aggregator will output the following sequence of Change<newValue,
> oldValue>:
> <V1, null>, <V2, V1>, <V3, V2>, <V4, V3>, <V5, V4>
> where could cost a lot of CPU overhead computing the intermediate results.
> Instead if we can let the underlying state store to "remember" the last
> emitted old value, we can reduce the number of emits based on some configs.
> More specifically, we can add one more field in the KV store engine storing
> the last emitted old value, which only get updated when we emit to the
> downstream processor. For example:
> At Beginning:
> Store: key => empty (no agg values yet)
> V1 computed:
> Update Both in Store: key => (V1, V1), Emit <V1, null>
> V2 computed:
> Update NewValue in Store: key => (V2, V1), No Emit
> V3 computed:
> Update NewValue in Store: key => (V3, V1), No Emit
> V4 computed:
> Update Both in Store: key => (V4, V4), Emit <V4, V1>
> V5 computed:
> Update NewValue in Store: key => (V5, V4), No Emit
> One more thing to consider is that, we need a "closing" time control on the
> not-yet-emitted keys; when some time has elapsed (or the window is to be
> closed), we need to check for any key if their current materialized pairs
> have not been emitted (for example <V5, V4> in the above example).
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