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https://issues.apache.org/jira/browse/CASSANDRA-20167?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17911956#comment-17911956
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Dmitry Konstantinov commented on CASSANDRA-20167:
-------------------------------------------------

Hi [~mck], thank you for the review comments.

Regarding the branch. What do you think about split the patch to 2 parts (one 
for trunk only and another for 5.0 and trunk)? If the main concern is the 
amount of changes: I can select a more valuable small subset for 5.0. If the 
main concern is a complexity of some parts - they can be moved out to the trunk 
only part.

What is my motivation: I am going to start using 5.0 in few months and want to 
get it in a best shape from performance point of view :)

A related question: do you have any idea about potential release time for 5.1 
GA? I am understand that it is just a guess, definitely not a commitment, but 
is it like few months, a half a year, a year from your point of view?

> Reduce memory allocations in miscellaneous places along write path
> ------------------------------------------------------------------
>
>                 Key: CASSANDRA-20167
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-20167
>             Project: Apache Cassandra
>          Issue Type: Improvement
>          Components: Consistency/Coordination, Local/Other
>            Reporter: Dmitry Konstantinov
>            Assignee: Dmitry Konstantinov
>            Priority: Normal
>             Fix For: 5.0.x
>
>         Attachments: image-2024-12-26-22-01-32-592.png, 
> image-2024-12-26-22-01-55-614.png, image-2024-12-26-22-02-44-040.png, 
> image-2024-12-26-22-03-49-018.png
>
>          Time Spent: 2h
>  Remaining Estimate: 0h
>
> Avoid unnecessary allocations in different places along write path:
> * avoid iterator allocations if possible
> * handle typical cases (such as a single row, single table writes) more 
> efficiently
> * add fast paths for typical scenarios (like pending ranges is empty)
> * memorize things which can be computed once



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