Scala defines transpose.
On Thu, Aug 21, 2014 at 4:22 PM, x <wasedax...@gmail.com> wrote:
> Yes.
> Now Spark API doesn't provide transpose function. You have to define it
> like below.
>
> def transpose(m: Array[Array[Double]]): Array[Array[Double]] = {
> (for {
> c <- m(0).indices
> } yield m.map(_(c)) ).toArray
> }
>
> xj @ Tokyo
>
>
> On Thu, Aug 21, 2014 at 10:12 PM, phoenix bai <mingzhi...@gmail.com>
> wrote:
>
>> this is exactly what I was looking for. thank you.
>>
>> one thing though, it doesn`t have transpose() function defined, so I have
>> to do the transpose myself for the localMat in your case.
>> hoping it will be supported in the future :-)
>>
>>
>>
>> On Thu, Aug 21, 2014 at 7:30 PM, x <wasedax...@gmail.com> wrote:
>>
>>> You could create a distributed matrix with RowMatrix.
>>>
>>> val rmat = new RowMatrix(rows)
>>>
>>> And then make a local DenseMatrix.
>>>
>>> val localMat = Matrices.dense(m, n, mat)
>>>
>>> Then multiply them.
>>>
>>> rmat.multiply(localMat)
>>>
>>>
>>> xj @ Tokyo
>>>
>>> On Thu, Aug 21, 2014 at 6:37 PM, Sean Owen <so...@cloudera.com> wrote:
>>>
>>>> Are you trying to multiply dense or sparse matrices? if sparse, are
>>>> they very large -- meaning, are you looking for distributed
>>>> operations?
>>>>
>>>> On Thu, Aug 21, 2014 at 10:07 AM, phoenix bai <mingzhi...@gmail.com>
>>>> wrote:
>>>> > there is RowMatrix implemented in spark.
>>>> > and I check for a while but failed to find any matrix operations (like
>>>> > multiplication etc) are defined in the class yet.
>>>> >
>>>> > so, my question is, if I want to do matrix multiplication, (to do
>>>> vector x
>>>> > matrix multiplication to be precise), need to convert the
>>>> vector/matrix to
>>>> > the the matrix type defined in breeze package right?
>>>> >
>>>> > thanks
>>>>
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>>>>
>>>
>>
>
