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https://issues.apache.org/jira/browse/SPARK-21459?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

David Allsopp updated SPARK-21459:
----------------------------------
    Description: 
When working with DataFrames with nested schemas, the behavior of the 
aggregation functions is inconsistent with respect to preserving the case of 
the nested field names.

For example, {{first()}} preserves the case of the field names, but 
{{collect_set()}} and {{collect_list()}} force the field names to lowercase.

Expected behavior: Field name case is preserved (or is at least consistent and 
documented)

Spark-shell session to reproduce:


{code:java}
scala> case class Inner(Key:String, Value:String)
scala> case class Outer(ID:Long, Pairs:Array[Inner])

val rdd = sc.parallelize(Seq(Outer(1L, Array(Inner("foo", "bar")))))
val df = sqlContext.createDataFrame(rdd)

scala> df
... = [ID: bigint, Pairs: array<struct<Key:string,Value:string>>]

scala>df.groupBy("ID").agg(first("Pairs"))
... = [ID: bigint, first(Pairs)(): array<struct<Key:string,Value:string>>]
// Note that Key and Value preserve their original case

scala>df.groupBy("ID").agg(collect_set("Pairs"))
... = [ID: bigint, collect_set(Pairs): array<struct<key:string,value:string>>]
// Note that key and value are now lowercased

{code}

Additionally, the column name is inconsistent: {{first(Pairs)()}} versus 
{{collect_set(Pairs)}} - note the extra parentheses in the first name.

  was:
When working with DataFrames with nested schemas, the behavior of the 
aggregation functions is inconsistent with respect to preserving the case of 
the nested field names.

For example, {{first()}} preserves the case of the field names, but 
{{collect_set()}} and {{collect_list()}} force the field names to lowercase.

Expected behavior: Field name case is preserved (or is at least consistent and 
documented)

Spark-shell session to reproduce:


{code:java}
scala> case class Inner(Key:String, Value:String)
scala> case class Outer(ID:Long, Pairs:Array[Inner])

val rdd = sc.parallelize(Seq(Outer(1L, Array(Inner("foo", "bar")))))
val df = sqlContext.createdataFrame(rdd)

scala> df
... = [ID: bigint, Pairs: array<struct<Key:string,Value:string>>]

scala>df.groupBy("ID").agg(first("Pairs"))
... = [ID: bigint, first(Pairs)(): array<struct<Key:string,Value:string>>]
// Note that Key and Value preserve their original case

scala>df.groupBy("ID").agg(collect_set("Pairs"))
... = [ID: bigint, collect_set(Pairs): array<struct<key:string,value:string>>]
// Note that key and value are now lowercased

{code}

Additionally, the column name is inconsistent: {{first(Pairs)()}} versus 
{{collect_set(Pairs)}} - note the extra parentheses for in the first name.


> Some aggregation functions change the case of nested field names
> ----------------------------------------------------------------
>
>                 Key: SPARK-21459
>                 URL: https://issues.apache.org/jira/browse/SPARK-21459
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.6.0
>            Reporter: David Allsopp
>            Priority: Minor
>
> When working with DataFrames with nested schemas, the behavior of the 
> aggregation functions is inconsistent with respect to preserving the case of 
> the nested field names.
> For example, {{first()}} preserves the case of the field names, but 
> {{collect_set()}} and {{collect_list()}} force the field names to lowercase.
> Expected behavior: Field name case is preserved (or is at least consistent 
> and documented)
> Spark-shell session to reproduce:
> {code:java}
> scala> case class Inner(Key:String, Value:String)
> scala> case class Outer(ID:Long, Pairs:Array[Inner])
> val rdd = sc.parallelize(Seq(Outer(1L, Array(Inner("foo", "bar")))))
> val df = sqlContext.createDataFrame(rdd)
> scala> df
> ... = [ID: bigint, Pairs: array<struct<Key:string,Value:string>>]
> scala>df.groupBy("ID").agg(first("Pairs"))
> ... = [ID: bigint, first(Pairs)(): array<struct<Key:string,Value:string>>]
> // Note that Key and Value preserve their original case
> scala>df.groupBy("ID").agg(collect_set("Pairs"))
> ... = [ID: bigint, collect_set(Pairs): array<struct<key:string,value:string>>]
> // Note that key and value are now lowercased
> {code}
> Additionally, the column name is inconsistent: {{first(Pairs)()}} versus 
> {{collect_set(Pairs)}} - note the extra parentheses in the first name.



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