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From "Pat Ferrel (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAHOUT-1507) Support External/Foreign Keys/IDs for Vectors and Matrices
Date Sat, 05 Apr 2014 00:11:17 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-1507?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13960837#comment-13960837
] 

Pat Ferrel commented on MAHOUT-1507:
------------------------------------

OK, desired behavior is to support a method to preserve user specified arbitrary keys for
row and column vectors. Put another way preserve IDs for for rows and columns of a DRM. Below
the term ID and Key is used interchangeably. 

For example, the DRM created for the item based recommender has rows of users, columns of
items. If the user specified ID could be preserved through to the output this would make usage
of the recommender much easier.

Also kmeans or other clustering, if user specified row IDs were preserved (possibly document
IDs in text clustering) this would make usage much easier. 

By preserve I mean that the user specified keys would be available in the sequence file output
of the appropriate job. Failing this, a Dictionary of user specified key <-> Mahout
keys be created for the output. In the case of a DRM as output, if the row vector was stored
with it's user specified key and a dictionary of the user specified column keys were created
then the user would not have to implement this behavior for every Mahout job.

Partial examples of this behavior in Mahout 0.9 are provided by Named or Property Vectors.
Also the text analysis pipeline creates a dictionary of word tokens <-> mahout column
id. This dictionary has to be created by Mahout since the tokens are created as a consequence
of phases in the job.

I should emphasize that this ID or Key translation is an absolute requirement for Mahout use
(except where the partial solution is enough). Why put the burden for this on every user?

> Support External/Foreign Keys/IDs for Vectors and Matrices
> ----------------------------------------------------------
>
>                 Key: MAHOUT-1507
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1507
>             Project: Mahout
>          Issue Type: Bug
>          Components: Math
>    Affects Versions: 0.9
>         Environment: Spark Scala
>            Reporter: Pat Ferrel
>              Labels: spark
>             Fix For: 1.0
>
>
> All users of Mahout have data which is addressed by keys or IDs of their own devise.
In order to use much of Mahout they must translate these IDs into Mahout IDs, then run their
jobs and translate back again when retrieving the output. If the ID space is very large this
is a difficult problem for users to solve at scale.
> For many Mahout operations this would not be necessary if these external keys could be
maintained for vectors and dimensions, or for rows and columns of a DRM.
> The reason I bring this up now is that much groundwork is being laid for Mahout's future
on Spark so getting this notion in early could be fundamentally important and used to build
on.
> If external IDs for rows and columns were maintained then RSJ, DRM Transpose (and other
DRM ops), vector extraction, clustering, and recommenders would need no ID translation steps,
a big user win.
> A partial solution might be to support external row IDs alone somewhat like the NamedVector
and PropertyVector in the Mahout hadoop code.
> On Apr 3, 2014, at 11:00 AM, Pat Ferrel <pat@occamsmachete.com> wrote:
> Perhaps this is best phrased as a feature request.
> On Apr 2, 2014, at 2:55 PM, Dmitriy Lyubimov <dlieu.7@gmail.com> wrote:
> PS.
> sequence file keys have also special meaning if they are Ints. .E.g. A'
> physical operator requires keys to be ints, in which case it interprets
> them as row indexes that become column indexes. This of course isn't always
> the case, e.g. (Aexpr).t %*% Aexpr doesn't require int indices because in
> reality optimizer will never choose actual transposition as a physical step
> in such pipeline. This interpretation is consistent with interpretation of
> long-existing Hadoop-side DistributedRowMatrix#transpose.
> On Wed, Apr 2, 2014 at 2:45 PM, Dmitriy Lyubimov <dlieu.7@gmail.com> wrote:
> On Wed, Apr 2, 2014 at 1:56 PM, Pat Ferrel <pat@occamsmachete.com> wrote:
> On Apr 2, 2014, at 1:39 PM, Dmitriy Lyubimov <dlieu.7@gmail.com> wrote:
> I think this duality, names and keys, is not very healthy really, and
> just
> creates addtutiinal hassle. Spark drm takes care of keys automatically
> thoughout, but propagating names from name vectors is solely algorithm
> concern as it stands.
> Not sure what you mean.
> Not what you think, it looks like.
> I mean that Mahout DRM structure is a bag of (key -> Vector) pairs. When
> persisted, key goes to the key of a sequence file. In particular, it means
> that there is a case of Bag[ key -> NamedVector]. Which means, external
> anchor could be saved to either key or name of a row. In practice it causes
> compatibility mess, e.g. we saw those numerous cases where e.g. seq2sparse
> saves external keys (file paths) into  key, whereas e.g. clustering
> algorithms are not seeing them because they expect them to be the name part
> of the vector. I am just saying we have two ways to name the rows, and it
> is generally not a healthy choice for the aforementioned reason.
> In my experience Names and Properties are primarily used to store
> external keys, which are quite healthy.
> Users never have data with Mahout keys, they must constantly go back and
> forth. This is exactly what the R data frame does, no? I'm not so concerned
> with being able to address an element by the external key
> drmB["pat"]["iPad'] like a HashMap. But it would sure be nice to have the
> external ids follow the data through any calculation that makes sense.
> I am with you on this.
> This would mean clustering, recommendations, transpose, RSJ would require
> no id transforming steps. This would make dealing with Mahout much easier.
> Data frames is a little bit a different thing, right now we work just with
> matrices. Although, yes, our in-core matrices support row and column names
> (just like in R) and distributed matrices support row keys only.  what i
> mean is that algebraic expression e.g.
> Aexpr %*% Bexpr will automatically propagate _keys_ from Aexpr as implied
> above, but not necessarily named vectors, because internally algorithms
> blockify things into matrix blocks, and i am far from sure that Mahout
> in-core stuff works correctly with named vectors as part of a matrix block
> in all situations. I may be wrong. I always relied on sequence file keys to
> identify data points.
> Note that sequence file keys are bigger than just a name, it is anything
> Writable. I.e. you could save a data structure there, as long as you have a
> Writable for it.
> On Apr 2, 2014 1:08 PM, "Pat Ferrel" <pat@occamsmachete.com> wrote:
> Are the Spark efforts supporting all Mahout Vector types? Named,
> Property
> Vectors? It occurred to me that data frames in R is a related but more
> general solution. If all rows and columns of a DRM and their
> coresponding
> Vectors (row or column vectors) were to support arbitrary properties
> attached to them in such a way that they are preserved during
> transpose,
> Vector extraction, and any other operations that make sense there
> would be
> a huge benefit for users.
> One of the constant problems with input to Mahout is translation of
> IDs.
> External to Mahout going in, Mahout to external coming out. Most of
> this
> would be unneeded if Mahout supported data frames, some would be
> avoided by
> supporting named or property vectors universally.



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