+1, in fact I would be very much indebted if someone (namely Dmitry :) ) could do a google hangout focused on spark where folks can ask questions and learn more, to this end I want to bring up something else, it'd be great if mahout itself either through the apache project foundation or through committer means have a hadoop cluster to test algorithms, it seems like folks have their own cluster to test on but I think it'd be a benefit to the community to have a cluster that everyone can leverage.
> Subject: Mahout on Spark > From: [email protected] > Date: Wed, 26 Mar 2014 09:05:02 -0700 > To: [email protected]; [email protected] > > New name for a new thread. > > A lot of the discussion on MAHOUT-1464 has been around integrating that > feature with the Scala DSL. As Saikat says this is of general interest since > people seem to agree that this is a good place to integrate efforts. > > I’m interested in what I think Dmitriy called data frames. Being a complete > noob on Spark I may have gotten this wrong but let me take a shot so he can > correct me. > > There are a lot of problems that require a pipeline. The text input pipeline > is an example, but almost any input to Mahout requires at least an id > translation step. What I though Dmitriy was suggesting was that by avoiding > the disk write + read between steps we might get significant speedups. This > has many implications, I’m sure. > > For one I think it means the non-serialized objects are being used by > multiple parts of the pipeline and so are not subject to “translation”. > > Dmitriy can you explain more? You mentioned a talk you have given, do you > have slides somewhere or a PDF? > > > On Mar 26, 2014, at 7:15 AM, Ted Dunning <[email protected]> wrote: > > It would be great to have you. > > > (go ahead and start new threads when appropriate ... better than hijacking) > > > On Wed, Mar 26, 2014 at 6:00 AM, Hardik Pandya <[email protected]>wrote: > > > Sorry to hijack the thread, > > > > this seems like first steps of mahout geeting it to work on spark > > > > there are similar efforts going on with R+Spark aka Spark R > > > > not sure if this helpos, played with spark ec2 scripts and it brings up > > multinode cluster using mesos and its configurable - willing to contribute > > donations for mahout-dev > > > > > > > > > > > > On Sun, Mar 23, 2014 at 11:22 PM, Saikat Kanjilal (JIRA) <[email protected] > >> wrote: > > > >> > >> [ > >> > > https://issues.apache.org/jira/browse/MAHOUT-1464?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13944710#comment-13944710 > > ] > >> > >> Saikat Kanjilal commented on MAHOUT-1464: > >> ----------------------------------------- > >> > >> +1 on Andrew's suggestion on using AWS to do this. Andrew is it possible > >> to have a shared account so mahout contributors can use this, I 'd even > > be > >> willing to chip in donations :) to have a shared AWS account > >> > >>> RowSimilarityJob on Spark > >>> ------------------------- > >>> > >>> Key: MAHOUT-1464 > >>> URL: https://issues.apache.org/jira/browse/MAHOUT-1464 > >>> Project: Mahout > >>> Issue Type: Improvement > >>> Components: Collaborative Filtering > >>> Affects Versions: 0.9 > >>> Environment: hadoop, spark > >>> Reporter: Pat Ferrel > >>> Labels: performance > >>> Fix For: 1.0 > >>> > >>> Attachments: MAHOUT-1464.patch, MAHOUT-1464.patch, > >> MAHOUT-1464.patch > >>> > >>> > >>> Create a version of RowSimilarityJob that runs on Spark. Ssc has a > >> prototype here: https://gist.github.com/sscdotopen/8314254. This should > >> be compatible with Mahout Spark DRM DSL so a DRM can be used as input. > >>> Ideally this would extend to cover MAHOUT-1422 which is a feature > >> request for RSJ on two inputs to calculate the similarity of rows of one > >> DRM with those of another. This cross-similarity has several applications > >> including cross-action recommendations. > >> > >> > >> > >> -- > >> This message was sent by Atlassian JIRA > >> (v6.2#6252) > >> > > >
