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https://issues.apache.org/jira/browse/IMPALA-7171?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16512853#comment-16512853
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Alex Rodoni commented on IMPALA-7171:
-------------------------------------

[~twmarshall] In impala_hints.html, we have:

 

Starting from Impala 2.9, {{INSERT}} or {{UPSERT}} operations into Kudu tables 
automatically have an exchange and sort node added to the plan that partitions 
and sorts the rows according to the partitioning/primary key scheme of the 
target table (unless the number of rows to be inserted is small enough to 
trigger single node execution). Use the{{ /* +NOCLUSTERED */}} and {{/* 
+NOSHUFFLE */}} hints together to disable partitioning and sorting before the 
rows are sent to Kudu.

 

Do you want to use the same text in impala_kudu.html?

 

> Add docs for Kudu insert partitioning/sorting
> ---------------------------------------------
>
>                 Key: IMPALA-7171
>                 URL: https://issues.apache.org/jira/browse/IMPALA-7171
>             Project: IMPALA
>          Issue Type: Improvement
>          Components: Docs
>            Reporter: Thomas Tauber-Marshall
>            Assignee: Alex Rodoni
>            Priority: Major
>              Labels: docs
>
> On the page: 
> http://impala.apache.org/docs/build3x/html/topics/impala_kudu.html, at the 
> end of the section: "Impala DML Support for Kudu Tables (INSERT, UPDATE, 
> DELETE, UPSERT)", we should add text like:
> Starting from Impala 2.9, Impala will automatically add a partition and sort 
> step to INSERTs before sending the rows to Kudu. Since Kudu partitions and 
> sorts rows on write, pre-partitioning and sorting takes some of the load off 
> of Kudu, and helps ensure that large INSERTs complete without timing out, but 
> it may slow down the end-to-end performance of the INSERT. Starting from 
> Impala 2.10, the hints "/* +noshuffle,noclustered */" may be used to turn 
> this pre-partitioning and sorting off. Additionally, since sorting may 
> consume a lot of memory, users should consider setting a "mem_limit" for 
> these queries.



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