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https://issues.apache.org/jira/browse/SPARK-27134?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-27134:
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Assignee: Apache Spark
> array_distinct function does not work correctly with columns containing array
> of array
> --------------------------------------------------------------------------------------
>
> Key: SPARK-27134
> URL: https://issues.apache.org/jira/browse/SPARK-27134
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.4.0
> Environment: Spark 2.4, scala 2.11.11
> Reporter: Mike Trenaman
> Assignee: Apache Spark
> Priority: Major
>
> The array_distinct function introduced in spark 2.4 is producing strange
> results when used on an array column which contains a nested array. The
> resulting output can still contain duplicate values, and furthermore,
> previously distinct values may be removed.
> This is easily repeatable, e.g. with this code:
> val df = Seq(
> Seq(Seq(1, 2), Seq(1, 2), Seq(1, 2), Seq(3, 4), Seq(4, 5))
> ).toDF("Number_Combinations")
> val dfWithDistinct = df.withColumn("distinct_combinations",
> array_distinct(col("Number_Combinations")))
>
> The initial 'df' DataFrame contains one row, where column
> 'Number_Combinations' contains the following values:
> [[1, 2], [1, 2], [1, 2], [3, 4], [4, 5]]
>
> The array_distinct function run on this column produces a new column
> containing the following values:
> [[1, 2], [1, 2], [1, 2]]
>
> As you can see, this contains three occurrences of the same value (1, 2), and
> furthermore, the distinct values (3, 4), (4, 5) have been removed.
>
>
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