Please see https://issues.apache.org/jira/browse/SPARK-24258
On Wed, May 30, 2018 at 10:40 PM Dongjin Lee <dong...@apache.org> wrote:

> How is this issue going? Is there any Jira ticket about this?
>
> Thanks,
> Dongjin
>
> On Sat, Mar 24, 2018 at 1:39 PM, Himanshu Mohan <
> himanshu.mo...@aexp.com.invalid> wrote:
>
>> I agree
>>
>>
>>
>>
>>
>>
>>
>> Thanks
>>
>> Himanshu
>>
>>
>>
>> *From:* Li Jin [mailto:ice.xell...@gmail.com]
>> *Sent:* Friday, March 23, 2018 8:24 PM
>> *To:* dev <dev@spark.apache.org>
>> *Subject:* MatrixUDT and VectorUDT in Spark ML
>>
>>
>>
>> Hi All,
>>
>>
>>
>> I came across these two types MatrixUDT and VectorUDF in Spark ML when
>> doing feature extraction and preprocessing with PySpark. However, when
>> trying to do some basic operations, such as vector multiplication and
>> matrix multiplication, I had to go down to Python UDF.
>>
>>
>>
>> It seems to be it would be very useful to have built-in operators on
>> these types just like first class Spark SQL types, e.g.,
>>
>>
>>
>> df.withColumn('v', df.matrix_column * df.vector_column)
>>
>>
>>
>> I wonder what are other people's thoughts on this?
>>
>>
>>
>> Li
>>
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>
>
> --
> *Dongjin Lee*
>
> *A hitchhiker in the mathematical world.*
>
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