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From Himanshu Mohan <Himanshu.Mo...@aexp.com.INVALID>
Subject RE: MatrixUDT and VectorUDT in Spark ML
Date Sat, 24 Mar 2018 04:39:00 GMT
I agree



Thanks
Himanshu

From: Li Jin [mailto:ice.xelloss@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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