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https://issues.apache.org/jira/browse/KUDU-2671?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17566609#comment-17566609
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ASF subversion and git services commented on KUDU-2671:
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Commit f1522c716f37e6a9db80de77a9783e0c48027a61 in kudu's branch
refs/heads/master from Alexey Serbin
[ https://gitbox.apache.org/repos/asf?p=kudu.git;h=f1522c716 ]
KUDU-2671 updated comments in C++ client API
Since the functionality of range-specific hash schemas becomes ready
to use, this patch removes the corresponding warning from the inline
documentation in the C++ client API. I also updated a few more comments
around to use already established terminology and wording.
This patch doesn't have any functional changes.
Change-Id: Ibc0ac12354dc265e1a9a651e47be08b46338defd
Reviewed-on: http://gerrit.cloudera.org:8080/18725
Tested-by: Kudu Jenkins
Reviewed-by: Mahesh Reddy <mre...@cloudera.com>
Reviewed-by: Abhishek Chennaka <achenn...@cloudera.com>
Reviewed-by: Yingchun Lai <acelyc1112...@gmail.com>
> Change hash number for range partitioning
> -----------------------------------------
>
> Key: KUDU-2671
> URL: https://issues.apache.org/jira/browse/KUDU-2671
> Project: Kudu
> Issue Type: Improvement
> Components: client, java, master, server
> Affects Versions: 1.8.0
> Reporter: yangz
> Assignee: Mahesh Reddy
> Priority: Major
> Labels: feature, roadmap-candidate, scalability
> Attachments: 屏幕快照 2019-01-24 下午12.03.41.png
>
>
> For our usage, the kudu schema design isn't flexible enough.
> We create our table for day range such as dt='20181112' as hive table.
> But our data size change a lot every day, for one day it will be 50G， but for
> some other day it will be 500G. For this case, it be hard to set the hash
> schema. If too big, for most case, it will be too wasteful. But too small,
> there is a performance problem in the case of a large amount of data.
>
> So we suggest a solution we can change the hash number by the history data of
> a table.
> for example
> # we create schema with one estimated value.
> # we collect the data size by day range
> # we create new day range partition by our collected day size.
> We use this feature for half a year, and it work well. We hope this feature
> will be useful for the community. Maybe the solution isn't so complete.
> Please help us make it better.
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