There is also the mahout Reader and Writer traits and classes that currently work with text delimited file I/O. These were imagined as a general framework to support parallelized read/write to any format and store using whatever method is expedient, including the ones Dmitriy mentions. I personally would like to do MongoDB since I have an existing app using that.
These are built to support a sort of extended-DRM (IndexedDataset) which maintains external IDs. These IDs can be anything you can put in a string like Mongo or Cassandra keys or can be left as human readable external keys. From an IndexedDataset you can get a CheckpointedDRM and do anything in the DSL with it. They are in the spark module but the base traits have been moved to the core “math-scala” to make the concepts core with implementations in left in the engine specific modules. This is work about to be put in a PR but you can look at it in the master to see if it helps—expect some refactoring shortly. I’m sure there will be changes needed for DBs but haven’t gotten to that so would love another set of eyes on the code. On Oct 9, 2014, at 3:08 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: Bottom line, some very smart people decided to do all that work in Spark and give us for free. Not sure why, but that did. If the capability already found in Spark, there's no need for us to replicate it. WRT specifically NoSql, Spark can read HBase trivially. I also did a bit more advanced things with a custom rdd implementation in Spark that was able to stream coprocessor outputs into rdd functors. In either case this is actually a fairly small effort. I never looked at it closely, but i know there are also Cassandra adapters for spark as well. Chances are, you could probably load data from any thinkable distributed data store into Spark these days via off the shelf implementations. If not, Spark actually makes it very easy to come with one on your own. On Thu, Oct 9, 2014 at 2:47 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: > Matrix defines structure. Not necessarily where it can be imported from. > You're right in the sense that framework itself avoids defining apis for > custom partition formation. But you're wrong in implying you cannot do it > if you wanted, our that you d have to do anything that complex as you say. > As long as you can form your own rdd of keys and row vectors, you can > always wrap it into a matrix (drmWrap api). Hdfs drm persistence on the > other hand had been around for as long as I remember, not just in 1.0. So > naturally those are provided to be interoperable with mahout .9 and before, > e g be able to load output from stuff like seq2sparse and such. > > Note that if you instruct your backend to use some sort off data locality > information, it will also be able capitalize on that automatically. > > There is actually far greater number of concerns of interacting with > native engine capabilities than just reading the data. For example, what if > we wanted to wrap an output of a shark query into a matrix. Instead of > addressing all those individually, we just chose to delegate those to > actual capabilities of backend. Chances are they already have (and, in > fact, do in case of spark) all that tooling far better than we will ever > have on our own. > > Sent from my phone. > On Oct 9, 2014 12:56 PM, "Reinis Vicups" <mah...@orbit-x.de> wrote: > >> Hello, >> >> I am currently looking into the new (DRM) mahout framework. >> >> I find myself wondering why is it so that from one side there is a lot >> of thought, effort and design complexity being invested into abstracting >> engines, contexts or algebraic operations, >> >> but from the other side, even abstract interfaces, are defined in a way >> that everything has to be read or written from files (on HDFS). >> >> I am considering to implement reading/writing to NoSQL database and >> initially I assumed it will be enough just to implement own >> ReaderWriter, but I am currently realizing that I will have to >> re-implement or hack-around by derivating own versions of large(?) >> portions of framework including own variant of CheckpointedDrm, >> DistributedEngine and what not. >> >> Is it because abstracting away storage type would introduce even more >> complexity or because there are aspects of design that absolutely >> require to read/write only to (seq)files? >> >> kind regards >> reinis >> >>
