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https://issues.apache.org/jira/browse/SPARK-6319?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14647289#comment-14647289
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Apache Spark commented on SPARK-6319:
-------------------------------------

User 'viirya' has created a pull request for this issue:
https://github.com/apache/spark/pull/7787

> DISTINCT doesn't work for binary type
> -------------------------------------
>
>                 Key: SPARK-6319
>                 URL: https://issues.apache.org/jira/browse/SPARK-6319
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.0.2, 1.1.1, 1.2.1, 1.3.0
>            Reporter: Cheng Lian
>            Priority: Critical
>
> Spark shell session for reproduction:
> {noformat}
> scala> import sqlContext.implicits._
> scala> import org.apache.spark.sql.types._
> scala> Seq(1, 1, 2, 2).map(i => Tuple1(i.toString)).toDF("c").select($"c" 
> cast BinaryType).distinct.show()
> ...
> CAST(c, BinaryType)
> [B@43f13160
> [B@5018b648
> [B@3be22500
> [B@476fc8a1
> {noformat}
> Spark SQL uses plain byte arrays to represent binary values. However, arrays 
> are compared by reference rather than by value. On the other hand, the 
> DISTINCT operator uses a {{HashSet}} and its {{.contains}} method to check 
> for duplicated values. These two facts together cause the problem.



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