-Original Message-
From: Xiangrui Meng [mailto:men...@gmail.com]
Sent: Wednesday, May 14, 2014 11:56 AM
To: user@spark.apache.org
Subject: Re: How to use Mahout VectorWritable in Spark.
You need
val raw = sc.sequenceFile(path, classOf[Text],
classOf[VectorWriteable])
to load
]
Sent: Wednesday, May 14, 2014 11:56 AM
To: user@spark.apache.org
Subject: Re: How to use Mahout VectorWritable in Spark.
You need
val raw = sc.sequenceFile(path, classOf[Text],
classOf[VectorWriteable])
to load the data. After that, you can do
val data = raw.values.map(_.get
Mahout now supports doing its distributed linalg natively on Spark so the
problem of sequence file input load into Spark is already solved there
(trunk, http://mahout.apache.org/users/sparkbindings/home.html,
drmFromHDFS() call -- and then you can access to the direct rdd via rdd
matrix property
: Wednesday, May 14, 2014 1:13 PM
To: user@spark.apache.org
Subject: RE: How to use Mahout VectorWritable in Spark.
Hi Xiangrui,
Thanks for the response .. I tried few ways to include mahout-math jar while
launching Spark shell.. but no success.. Can you please point what I am doing
wrong
1. mahout
-Original Message-
From: Xiangrui Meng [mailto:men...@gmail.com]
Sent: Wednesday, May 14, 2014 11:56 AM
To: user@spark.apache.org
Subject: Re: How to use Mahout VectorWritable in Spark.
You need
val raw = sc.sequenceFile(path, classOf[Text],
classOf[VectorWriteable])
to load the data. After
