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https://issues.apache.org/jira/browse/SPARK-18393?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-18393.
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Resolution: Duplicate
> DataFrame pivot output column names should respect aliases
> ----------------------------------------------------------
>
> Key: SPARK-18393
> URL: https://issues.apache.org/jira/browse/SPARK-18393
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Eric Liang
> Priority: Minor
>
> For example
> {code}
> val df = spark.range(100).selectExpr("id % 5 as x", "id % 2 as a", "id as b")
> df
> .groupBy('x)
> .pivot("a", Seq(0, 1))
> .agg(expr("sum(b)").as("blah"), expr("count(b)").as("foo"))
> .show()
> +---+--------------------+---------------------+--------------------+---------------------+
> | x|0_sum(`b`) AS `blah`|0_count(`b`) AS `foo`|1_sum(`b`) AS
> `blah`|1_count(`b`) AS `foo`|
> +---+--------------------+---------------------+--------------------+---------------------+
> | 0| 450| 10| 500|
> 10|
> | 1| 510| 10| 460|
> 10|
> | 3| 530| 10| 480|
> 10|
> | 2| 470| 10| 520|
> 10|
> | 4| 490| 10| 540|
> 10|
> +---+--------------------+---------------------+--------------------+---------------------+
> {code}
> The column names here are quite hard to read. Ideally we would respect the
> aliases and generate column names like 0_blah, 0_foo, 1_blah, 1_foo instead.
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