I'm not sure of the answer to your question; however, when performing
aggregates I find it useful to specify an *alias* for each column. That
will give you explicit control over the name of the resulting column.
In your example, that would look something like:
df.groupby(col("...")).agg(count("number"))*.alias("ColumnNameCount")*
Hope that helps!
Kevin
On Thu, Mar 23, 2017 at 2:41 AM, Wen Pei Yu <yuw...@cn.ibm.com> wrote:
> Hi All
>
> I found some spark version(spark 1.4) return upper case aggregated
> column, and some return low case.
> As below code,
> df.groupby(col("...")).agg(count("number"))
> may return
>
> COUNT(number) ------ spark 1,4
> count(number) ----- spark 1.6
>
> Anyone know if there is configure parameter for this, or which PR change
> this?
>
> Thank you very much.
> Yu Wenpei.
>
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