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https://issues.apache.org/jira/browse/KUDU-2671?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17396990#comment-17396990
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ASF subversion and git services commented on KUDU-2671:
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Commit 607d9d0a7e95e220864f43b88a64644bb6402163 in kudu's branch
refs/heads/master from Alexey Serbin
[ https://gitbox.apache.org/repos/asf?p=kudu.git;h=607d9d0 ]
[common] more generic API for IN list predicate pruning
While working on KUDU-2671, I found that the exposed internals of the
PartitionSchema class doesn't allow for updating the implementation of
the partition-related code to include per-range custom hash bucket
schemas in a consistent manner.
This patch introduces a bit more generic interface for pruning values of
IN list predicates by adding a new PartitionMayContainRow() method and
removes the following methods from the public API of the PartitionSchema
class:
* HashPartitionContainsRow()
* RangePartitionContainsRow()
* IsColumnSingleRangeSchema()
* TryGetSingleColumnHashPartitionIndex()
I also added one extra test scenario and updated existing ones to
increase readability of the assertion messages if they are triggered.
This is a follow-up to 6a7cadc7e and 83b8caf4f.
Change-Id: I2e2390cc4747864fdac71656dd7125ac3b15bf9d
Reviewed-on: http://gerrit.cloudera.org:8080/17764
Tested-by: Kudu Jenkins
Reviewed-by: Mahesh Reddy <[email protected]>
Reviewed-by: Andrew Wong <[email protected]>
> 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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