callUDF("MyUDF", col("col1").as("name")
or
callUDF("MyUDF", col("col1").alias("name")
On Fri, Oct 2, 2015 at 3:29 PM, Umesh Kacha <umesh.ka...@gmail.com> wrote:
> Hi Michael,
>
> Thanks much. How do we give alias name for resultant columns? For e.g.
> when using
>
> hiveContext.sql("select MyUDF("test") as mytest from myTable");
>
> how do we do that in DataFrame callUDF
>
> callUDF("MyUDF", col("col1"))???
>
> On Fri, Oct 2, 2015 at 8:23 PM, Michael Armbrust <mich...@databricks.com>
> wrote:
>
>> import org.apache.spark.sql.functions.*
>>
>> callUDF("MyUDF", col("col1"), col("col2"))
>>
>> On Fri, Oct 2, 2015 at 6:25 AM, unk1102 <umesh.ka...@gmail.com> wrote:
>>
>>> Hi I have registed my hive UDF using the following code:
>>>
>>> hiveContext.udf().register("MyUDF",new UDF1(String,String)) {
>>> public String call(String o) throws Execption {
>>> //bla bla
>>> }
>>> },DataTypes.String);
>>>
>>> Now I want to use above MyUDF in DataFrame. How do we use it? I know how
>>> to
>>> use it in a sql and it works fine
>>>
>>> hiveContext.sql(select MyUDF("test") from myTable);
>>>
>>> My hiveContext.sql() query involves group by on multiple columns so for
>>> scaling purpose I am trying to convert this query into DataFrame APIs
>>>
>>>
>>> dataframe.select("col1","col2","coln").groupby(""col1","col2","coln").count();
>>>
>>> Can we do the follwing dataframe.select(MyUDF("col1"))??? Please guide.
>>>
>>>
>>>
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>>
>
