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From "Apache Spark (JIRA)" <>
Subject [jira] [Assigned] (SPARK-20233) Apply star-join filter heuristics to dynamic programming join enumeration
Date Thu, 06 Apr 2017 04:17:41 GMT


Apache Spark reassigned SPARK-20233:

    Assignee:     (was: Apache Spark)

> Apply star-join filter heuristics to dynamic programming join enumeration
> -------------------------------------------------------------------------
>                 Key: SPARK-20233
>                 URL:
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>    Affects Versions: 2.2.0
>            Reporter: Ioana Delaney
>            Priority: Critical
> This JIRA integrates star-join detection with the cost-based optimizer. 
> The join enumeration using dynamic programming generates a set of feasible joins. The
sub-optimal plans can be eliminated by a sequence of independent, optional filters. The optional
filters include heuristics for reducing the search space. For example,
> # Star-join: Tables in a star schema relationship are planned together since they are
assumed to have an optimal execution.
> # Cartesian products: Cartesian products are deferred as late as possible to avoid large
intermediate results (expanding joins, in general).
> # Composite inners: “Bushy tree” plans are not generated to avoid materializing intermediate
> For reference, see “Measuring the Complexity of Join Enumeration in Query Optimization”
by Ono et al.
> This JIRA implements the star join filter. 

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