Sure. @Saikat et al:
Check out the http://mahout.apache.org/users/sparkbindings/home.html "Wanted" section. Of course, data frames and vectorization(feature prep) standardization is very high priority there. Another high priority is interactive shell /scripting (just like spark shell). Something very similar in R interactive/script runner mode in spirit. It is very important. Re: data frames. Anyone familiar with R, knows what it is. Basically a set of named columnar vectors (with rows named or enumerated as well). A set of filtering/modifying DSL expressions similar to R (I haven't really thought about it at depth). The tricky part here is in-core data frame support of course, since data frames are based on vectors that go beyond just a real (double) values we have right now. in R, vector values could be integral, boolean and character(i.e.string) types as well. If we had an in-core support for that (or borrowed it from somewhere), the rest would have been easy -- it is just a matter of semantic elegance. Really, i suggest to look at R paradigms there, it is a pretty elegant way to work with closures there. Of course we could use off-the-shelf stuff such as Map's to support something named, with string values. I don't know at this point. Scala itself comes a long way to help out here. As for slides, they are of little interest themselves since they mostly re-interpret and summarize the working notes pdf in a bit more palatable way. It is just an opportunity to deliver some content to folks who shy away from reading docs for some reason *wink wink*. I will put them on the site after meetup if it is ok. On Wed, Mar 26, 2014 at 9:09 AM, Saikat Kanjilal <[email protected]>wrote: > +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) > > >> > > > > > >
