Should I file a JIRA to remove the example? I think it is confusing to
include example code without explanation of how to run it, and it sounds
like this one isn't worth running or reviewing anyway.
On Mon, Apr 28, 2014 at 2:34 PM, Debasish Das wrote:
> Don't use SparkALS...that's the first v
Don't use SparkALS...that's the first version of the code and does not
scale...
Li is right...you have to do the dictionary generation on users, products
and then generate indexed fileI wrote some utilities but looks like it
is application dependentthe indexed netflix format is more generi
From: Sean Owen [mailto:so...@cloudera.com]
Sent: Monday, April 28, 2014 1:41 PM
To: user@spark.apache.org
Subject: Re: running SparkALS
Yeah you'd have to look at the source code in this case; it's not explained in
the scaladoc or usage message as far as I can see either.
The args
Thanks, Deb. But I'm looking at org.apache.spark.examples.SparkALS, which
is not in the mllib examples, and does not take any file parameters.
I don't see the class you refer to in the examples ...however, if I did
want to run that example, where would I find the file in question?
It would be g
http://spark.apache.org/docs/0.9.0/mllib-guide.html#collaborative-filtering-1
One thing which is undocumented: the integers representing users and
items have to be positive. Otherwise it throws exceptions.
Li
On 28 avr. 2014, at 10:30, Diana Carroll wrote:
> Hi everyone. I'm trying to run som
Diana,
Here are the parameters:
./bin/spark-class org.apache.spark.mllib.recommendation.ALS
Usage: ALS
[] [] [] []
Master: Local/Deployed spark cluster master
ratings_file: Netflix format data
rank: Reduced dimension of the User and Product factors
iterations: How many ALS iterations you wo
Yeah you'd have to look at the source code in this case; it's not
explained in the scaladoc or usage message as far as I can see either.
The args refer specifically to the example of recommending Movies to
Users. This example makes up a bunch of ratings and then makes
recommendations using ALS.
M
Hi Diana,
SparkALS is an example implementation of ALS. It doesn't call the ALS
algorithm implemented in MLlib. M, U, and F are used to generate
synthetic data.
I'm updating the examples. In the meantime, you can take a look at the
updated MLlib guide:
http://50.17.120.186:4000/mllib-collaborativ
