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Yin Huai commented on SPARK-6319:
---------------------------------
I believe that our aggregation and join will also be affected. I am changing the Priority
to Blocker.
> 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, 1.3.0, 1.2.1
> Reporter: Cheng Lian
> Priority: Blocker
>
> 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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