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https://issues.apache.org/jira/browse/SPARK-12616?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin updated SPARK-12616:
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Description:
Union logical plan is a binary node. However, a typical use case for union is
to union a very large number of input sources (DataFrames, RDDs, or files). In
this case, our optimizer can become very slow due to the large number of
logical unions. We should change the Union logical plan to support an arbitrary
number of children, and add a single rule in the optimizer (or analyzer?) to
collapse all adjacent Unions into one.
Note that this problem doesn't exist in physical plan, because the physical
Union already supports arbitrary number of children.
was:
Union logical plan is a binary node. However, a typical use case for union is
to union a very large number of input sources (DataFrames, RDDs, or files). In
this case, our optimizer can become very slow due to the large number of
logical unions. We should change the Union logical plan to support an arbitrary
number of children, and add a single rule in the optimizer (or analyzer?) to
collapse all adjacent Unions into one.
> Improve union logical plan efficiency
> -------------------------------------
>
> Key: SPARK-12616
> URL: https://issues.apache.org/jira/browse/SPARK-12616
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Reynold Xin
>
> Union logical plan is a binary node. However, a typical use case for union is
> to union a very large number of input sources (DataFrames, RDDs, or files).
> In this case, our optimizer can become very slow due to the large number of
> logical unions. We should change the Union logical plan to support an
> arbitrary number of children, and add a single rule in the optimizer (or
> analyzer?) to collapse all adjacent Unions into one.
> Note that this problem doesn't exist in physical plan, because the physical
> Union already supports arbitrary number of children.
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