Chowdary Davuluri commented on SPARK-6072:

Has this been fixed as part of 
https://issues.apache.org/jira/browse/SPARK-11111 ?

> Enable hash joins for null-safe equality predicates
> ---------------------------------------------------
>                 Key: SPARK-6072
>                 URL: https://issues.apache.org/jira/browse/SPARK-6072
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 1.2.1
>            Reporter: Dima Zhiyanov
> Currently joins such as 
> A join B on A.x = B.x AND A.y <=> B.y
> are evaluated as hash join on just x followed by filter on y. 
> This causes a skew problem (very long join) when a particular value of x has 
> a high cardinality even though (x, y) is evenly distributed
> Can we implement is as a hash join on (X, Option(Y))? This will eliminate the 
> skew in this case
> Imagine a join:
>  People as p1 join People as p2 on p1.name = p2.name and p1.address <=> 
> p2.address
> (very small percentage of people has unknown address)
> This causes a skewed join on popular names such as "Mary Brown" if we hash on 
> names alone, but will not cause a skew if we hash on (Name, Option(Address))

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