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https://issues.apache.org/jira/browse/SPARK-22310?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zhenhua Wang updated SPARK-22310:
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Issue Type: Sub-task (was: Improvement)
Parent: SPARK-21975
> Refactor join estimation to incorporate estimation logic for different kinds
> of statistics
> ------------------------------------------------------------------------------------------
>
> Key: SPARK-22310
> URL: https://issues.apache.org/jira/browse/SPARK-22310
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Zhenhua Wang
>
> The current join estimation logic is only based on basic column statistics
> (such as ndv, etc). If we want to add estimation for other kinds of
> statistics (such as histograms), it's not easy to incorporate into the
> current algorithm:
> 1. When we have multiple pairs of join keys, the current algorithm computes
> cardinality in a single formula. But if different join keys have different
> kinds of stats, the computation logic for each pair of join keys become
> different, so the previous formula does not apply.
> 2. Currently it computes cardinality and updates join keys' column stats
> separately. It's better to do these two steps together, since both
> computation and update logic are different for different kinds of stats.
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