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https://issues.apache.org/jira/browse/KYLIN-5011?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17363390#comment-17363390
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ASF GitHub Bot commented on KYLIN-5011:
---------------------------------------
zhengshengjun opened a new pull request #1662:
URL: https://github.com/apache/kylin/pull/1662
## Proposed changes
Describe the big picture of your changes here to communicate to the
maintainers why we should accept this pull request. If it fixes a bug or
resolves a feature request, be sure to link to that issue.
## Types of changes
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- [ ] Bugfix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [ ] Documentation Update (if none of the other choices apply)
## Checklist
_Put an `x` in the boxes that apply. You can also fill these out after
creating the PR. If you're unsure about any of them, don't hesitate to ask.
We're here to help! This is simply a reminder of what we are going to look for
before merging your code._
- [x] I have create an issue on [Kylin's
jira](https://issues.apache.org/jira/browse/KYLIN), and have described the
bug/feature there in detail
- [x] Commit messages in my PR start with the related jira ID, like
"KYLIN-0000 Make Kylin project open-source"
- [x] Compiling and unit tests pass locally with my changes
- [ ] I have added tests that prove my fix is effective or that my feature
works
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against the `document` branch
- [ ] Any dependent changes have been merged
## Further comments
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> Detect and scatter skewed data in dict encoding step
> ----------------------------------------------------
>
> Key: KYLIN-5011
> URL: https://issues.apache.org/jira/browse/KYLIN-5011
> Project: Kylin
> Issue Type: New Feature
> Components: Job Engine
> Affects Versions: v4.0.0-beta
> Reporter: ShengJun Zheng
> Assignee: ShengJun Zheng
> Priority: Major
> Fix For: v4.0.0
>
> Attachments: image-2021-06-15-10-54-19-419.png
>
>
> In KYLIN4, dictionaries are hashed into several buckets, column data are
> repartitioned to the same partition size as bucket size. Then, each encoding
> task is able to load a piece of dictionary bucket to accelerate the encoding
> step.
> Recently we are troubled by this improvement when data skew happens. In some
> of our cases, the repartition step during encoding is even impossible to
> finish . Whereas this works fine in KYLIN3, for each Spark task will load all
> dictionary of a column and encode column values to int values. There is no
> need to do repartition step in KYLIN3.
> We solve this by:
> # sample from source data and detect skewed data
> # build skewed data's dictionary
> # customize an repartition function to scatter skewed data to random
> partitions
> # do encoding with both skewed dictionary and dictionary loaded within each
> partition
> After this improvement, some of our cube's build time reduced from 190min to
> 30min
> !image-2021-06-15-10-54-19-419.png!
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