or local sparse-sparse matrix multiplic]Xiangrui
>>> Meng ---11/05/2014 01:13:40 PM---You can use breeze for local sparse-sparse
>>> matrix multiplication and then define an RDD of sub-matri
>>>
>>> From: Xiangrui Meng
>>> To: Duy Huynh
>>>
Watson Research Center
>>
>>
>> [image: Inactive hide details for Xiangrui Meng ---11/05/2014 01:13:40
>> PM---You can use breeze for local sparse-sparse matrix multiplic]Xiangrui
>> Meng ---11/05/2014 01:13:40 PM---You can use breeze for local sparse-sparse
>> matrix
ngrui
> Meng ---11/05/2014 01:13:40 PM---You can use breeze for local sparse-sparse
> matrix multiplication and then define an RDD of sub-matri
>
> From: Xiangrui Meng
> To: Duy Huynh
> Cc: user
> Date: 11/05/2014 01:13 PM
> Subject: Re: sparse x sparse matrix multiplica
01:13 PM
Subject: Re: sparse x sparse matrix multiplication
You can use breeze for local sparse-sparse matrix multiplication and
then define an RDD of sub-matrices
RDD[(Int, Int, CSCMatrix[Double])] (blockRowId, blockColId, sub-matrix)
and then use join and aggregateByKey to implement
You can use breeze for local sparse-sparse matrix multiplication and
then define an RDD of sub-matrices
RDD[(Int, Int, CSCMatrix[Double])] (blockRowId, blockColId, sub-matrix)
and then use join and aggregateByKey to implement this feature, which
is the same as in MapReduce.
-Xiangrui
--
ngrui!
>
> On Wed, Nov 5, 2014 at 4:24 AM, Xiangrui Meng wrote:
>
>> local matrix-matrix multiplication or distributed?
>>
>> On Tue, Nov 4, 2014 at 11:58 PM, ll wrote:
>> > what is the best way to implement a sparse x sparse matrix
>> multiplication
>&g
ment a sparse x sparse matrix multiplication
> > with spark?
> >
> >
> >
> > --
> > View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/sparse-x-sparse-matrix-multiplication-tp18163.html
> > Sent from t
local matrix-matrix multiplication or distributed?
On Tue, Nov 4, 2014 at 11:58 PM, ll wrote:
> what is the best way to implement a sparse x sparse matrix multiplication
> with spark?
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.100156
what is the best way to implement a sparse x sparse matrix multiplication
with spark?
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