I believe they r still debating about renaming SchemaRDD -> Data Frame. I must admit Dmitriy had suggested this to me few months ago reusing SchemaRDD if possible. Dmitriy was right "U told us".
On Wed, Feb 4, 2015 at 11:09 AM, Pat Ferrel <p...@occamsmachete.com> wrote: > This sound like a great idea but I wonder is we can get rid of Mahout DRM > as a native format. If we have DataFrames (have they actually renamed > SchemaRDD?) backed DRMs we ideally don’t need Mahout native DRMs or > IndexedDatasets, right? This would be a huge step! If we get data > interchangeability with MLlib its a win. If we get general row and column > IDs that follow the data through math, its a win. Need to think through how > to use a DataFrame in a streaming case, probably through some checkpointing > of the window DStream—hmm. > > On Feb 4, 2015, at 7:37 AM, Andrew Palumbo <ap....@outlook.com> wrote: > > > On 02/03/2015 08:22 PM, Dmitriy Lyubimov wrote: > > I'd suggest to consider this: remember all this talk about > > language-integrated spark ql being basically dataframe manipulation DSL? > > > > so now Spark devs are noticing this generality as well and are actually > > proposing to rename SchemaRDD into DataFrame and make it mainstream data > > structure. (my "told you so" moment of sorts :) > > > > What i am getting at, i'd suggest to make DRM and Spark's newly renamed > > DataFrame our two major structures. In particular, standardize on using > > DataFrame for things that may include non-numerical data and require more > > grace about column naming and manipulation. Maybe relevant to TF-IDF work > > when it deals with non-matrix content. > Sounds like a worthy effort to me. We'd be basically implementing an API > at the math-scala level for SchemaRDD/Dataframe datastructures correct? > > On Tue, Feb 3, 2015 at 5:01 PM, Pat Ferrel <p...@occamsmachete.com> wrote: > >> Seems like seq2sparse would be really easy to replace since it takes > text > >> files to start with, then the whole pipeline could be kept in rdds. The > >> dictionaries and counts could be either in-memory maps or rdds for use > with > >> joins? This would get rid of sequence files completely from the > pipeline. > >> Item similarity uses in-memory maps but the plan is to make it more > >> scalable using joins as an alternative with the same API allowing the > user > >> to trade-off footprint for speed. > > I think you're right- should be relatively easy. I've been looking at > porting seq2sparse to the DSL for bit now and the stopper at the DSL level > is that we don't have a distributed data structure for strings..Seems like > getting a DataFrame implemented as Dmitriy mentioned above would take care > of this problem. > > The other issue i'm a little fuzzy on is the distributed collocation > mapping- it's a part of the seq2sparse code that I've not spent too much > time in. > > I think that this would be very worthy effort as well- I believe > seq2sparse is a particular strong mahout feature. > > I'll start another thread since we're now way off topic from the > refactoring proposal. > >> > >> My use for TF-IDF is for row similarity and would take a DRM (actually > >> IndexedDataset) and calculate row/doc similarities. It works now but > only > >> using LLR. This is OK when thinking of the items as tags or metadata but > >> for text tokens something like cosine may be better. > >> > >> I’d imagine a downsampling phase that would precede TF-IDF using LLR a > lot > >> like how CF preferences are downsampled. This would produce an > sparsified > >> all-docs DRM. Then (if the counts were saved) TF-IDF would re-weight the > >> terms before row similarity uses cosine. This is not so good for search > but > >> should produce much better similarities than Solr’s “moreLikeThis” and > does > >> it for all pairs rather than one at a time. > >> > >> In any case it can be used to do a create a personalized content-based > >> recommender or augment a CF recommender with one more indicator type. > >> > >> On Feb 3, 2015, at 3:37 PM, Andrew Palumbo <ap....@outlook.com> wrote: > >> > >> > >> On 02/03/2015 12:44 PM, Andrew Palumbo wrote: > >>> On 02/03/2015 12:22 PM, Pat Ferrel wrote: > >>>> Some issues WRT lower level Spark integration: > >>>> 1) interoperability with Spark data. TF-IDF is one example I actually > >> looked at. There may be other things we can pick up from their > committers > >> since they have an abundance. > >>>> 2) wider acceptance of Mahout DSL. The DSL’s power was illustrated to > >> me when someone on the Spark list asked about matrix transpose and an > MLlib > >> committer’s answer was something like “why would you want to do that?”. > >> Usually you don’t actually execute the transpose but they don’t even > >> support A’A, AA’, or A’B, which are core to what I work on. At present > you > >> pretty much have to choose between MLlib or Mahout for sparse matrix > stuff. > >> Maybe a half-way measure is some implicit conversions (ugh, I know). If > the > >> DSL could interchange datasets with MLlib, people would be pointed to > the > >> DSL for all of a bunch of “why would you want to do that?” features. > MLlib > >> seems to be algorithms, not math. > >>>> 3) integration of Streaming. DStreams support most of the RDD > >> interface. Doing a batch recalc on a moving time window would nearly > fall > >> out of DStream backed DRMs. This isn’t the same as incremental updates > on > >> streaming but it’s a start. > >>>> Last year we were looking at Hadoop Mapreduce vs Spark, H2O, Flink > >> faster compute engines. So we jumped. Now the need is for streaming and > >> especially incrementally updated streaming. Seems like we need to > address > >> this. > >>>> Andrew, regardless of the above having TF-IDF would be super > >> helpful—row similarity for content/text would benefit greatly. > >>> I will put a PR up soon. > >> Just to clarify, I'll be porting over the (very simple) TF, TFIDF > classes > >> and Weight interface over from mr-legacy to math-scala. They're > available > >> now in spark-shell but won't be after this refactoring. These still > >> require dictionary and a frequency count maps to vectorize incoming > text- > >> so they're more for use with the old MR seq2sparse and I don't think > they > >> can be used with Spark's HashingTF and IDF. I'll put them up soon. > >> Hopefully they'll be of some use. > >> > >> On Feb 3, 2015, at 8:47 AM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: > >>>> But first I need to do massive fixes and improvements to the > distributed > >>>> optimizer itself. Still waiting on green light for that. > >>>> On Feb 3, 2015 8:45 AM, "Dmitriy Lyubimov" <dlie...@gmail.com> wrote: > >>>> > >>>>> On Feb 3, 2015 7:20 AM, "Pat Ferrel" <p...@occamsmachete.com> wrote: > >>>>>> BTW what level of difficulty would making the DSL run on MLlib > Vectors > >>>>> and RowMatrix be? Looking at using their hashing TF-IDF but it raises > >>>>> impedance mismatch between DRM and MLlib RowMatrix. This would > further > >>>>> reduce artifact size by a bunch. > >>>>> > >>>>> Short answer, if it were possible, I'd not bother with Mahout code > >> base at > >>>>> all. The problem is it lacks sufficient flexibility semantics and > >>>>> abstruction. Breeze is indefinitely better in that department but at > >> the > >>>>> time it was sufficiently worse on abstracting interoperability of > >> matrices > >>>>> with different structures. And mllib does not expose breeze. > >>>>> > >>>>> Looking forward toward hardware acellerated bolt-on work I just must > >> say > >>>>> after reading breeze code for some time I still have much clearer > plan > >> how > >>>>> such back hybridization and cost calibration might work with current > >> Mahout > >>>>> math abstractions than with breeze. It is also more in line with my > >> current > >>>>> work tasks. > >>>>> > >>>>>> Also backing something like a DRM with DStreams. Periodic model > recalc > >>>>> with streams is maybe the first step towards truly streaming algos. > >> Looking > >>>>> at DStream -> DRM conversion for A’A, A’B, and AA’ in item and row > >>>>> similarity. Attach Kafka and get evergreen models, if not > incrementally > >>>>> updating models. > >>>>>> On Feb 2, 2015, at 4:54 PM, Dmitriy Lyubimov <dlie...@gmail.com> > >> wrote: > >>>>>> bottom line compile-time dependencies are satisfied with no extra > >> stuff > >>>>>> from mr-legacy or its transitives. This is proven by virtue of > >>>>> successful > >>>>>> compilation with no dependency on mr-legacy on the tree. > >>>>>> > >>>>>> Runtime sufficiency for no extra dependency is proven via running > >> shell > >>>>> or > >>>>>> embedded tests (unit tests) which are successful too. This implies > >>>>>> embedding and shell apis. > >>>>>> > >>>>>> Issue with guava is typical one. if it were an issue, i wouldn't be > >> able > >>>>> to > >>>>>> compile and/or run stuff. Now, question is what do we do if drivers > >> want > >>>>>> extra stuff that is not found in Spark. > >>>>>> > >>>>>> Now, It is so nice not to depend on anything extra so i am hesitant > to > >>>>>> offer anything here. either shading or lib with opt-in dependency > >> policy > >>>>>> would suffice though, since it doesn't look like we'd have to have > >> tons > >>>>> of > >>>>>> extra for drivers. > >>>>>> > >>>>>> > >>>>>> > >>>>>> On Sat, Jan 31, 2015 at 10:17 AM, Pat Ferrel <p...@occamsmachete.com > > > >>>>> wrote: > >>>>>>> I vaguely remember there being a Guava version problem where the > >>>>> version > >>>>>>> had to be rolled back in one of the hadoop modules. The math-scala > >>>>>>> IndexedDataset shouldn’t care about version. > >>>>>>> > >>>>>>> BTW It seems pretty easy to take out the option parser and replace > >> with > >>>>>>> match and tuples especially if we can extend the Scala App class. > It > >>>>> might > >>>>>>> actually simplify things since I can then use several case classes > to > >>>>> hold > >>>>>>> options (scopt needed one object), which in turn takes out all > those > >>>>> ugly > >>>>>>> casts. I’ll take a look next time I’m in there. > >>>>>>> > >>>>>>> On Jan 30, 2015, at 4:07 PM, Dmitriy Lyubimov <dlie...@gmail.com> > >>>>> wrote: > >>>>>>> in 'spark' module it is overwritten with spark dependency, which > also > >>>>> comes > >>>>>>> at the same version so happens. so should be fine with 1.1.x > >>>>>>> > >>>>>>> [INFO] --- maven-dependency-plugin:2.8:tree (default-cli) @ > >>>>>>> mahout-spark_2.10 --- > >>>>>>> [INFO] org.apache.mahout:mahout-spark_2.10:jar:1.0-SNAPSHOT > >>>>>>> [INFO] +- org.apache.spark:spark-core_2.10:jar:1.1.0:compile > >>>>>>> [INFO] | +- org.apache.hadoop:hadoop-client:jar:2.2.0:compile > >>>>>>> [INFO] | | +- org.apache.hadoop:hadoop-common:jar:2.2.0:compile > >>>>>>> [INFO] | | | +- commons-cli:commons-cli:jar:1.2:compile > >>>>>>> [INFO] | | | +- org.apache.commons:commons-math:jar:2.1:compile > >>>>>>> [INFO] | | | +- commons-io:commons-io:jar:2.4:compile > >>>>>>> [INFO] | | | +- > commons-logging:commons-logging:jar:1.1.3:compile > >>>>>>> [INFO] | | | +- commons-lang:commons-lang:jar:2.6:compile > >>>>>>> [INFO] | | | +- > >>>>>>> commons-configuration:commons-configuration:jar:1.6:compile > >>>>>>> [INFO] | | | | +- > >>>>>>> commons-collections:commons-collections:jar:3.2.1:compile > >>>>>>> [INFO] | | | | +- > >> commons-digester:commons-digester:jar:1.8:compile > >>>>>>> [INFO] | | | | | \- > >>>>>>> commons-beanutils:commons-beanutils:jar:1.7.0:compile > >>>>>>> [INFO] | | | | \- > >>>>>>> commons-beanutils:commons-beanutils-core:jar:1.8.0:compile > >>>>>>> [INFO] | | | +- org.apache.avro:avro:jar:1.7.4:compile > >>>>>>> [INFO] | | | +- > >> com.google.protobuf:protobuf-java:jar:2.5.0:compile > >>>>>>> [INFO] | | | +- org.apache.hadoop:hadoop-auth:jar:2.2.0:compile > >>>>>>> [INFO] | | | \- > >>>>> org.apache.commons:commons-compress:jar:1.4.1:compile > >>>>>>> [INFO] | | | \- org.tukaani:xz:jar:1.0:compile > >>>>>>> [INFO] | | +- org.apache.hadoop:hadoop-hdfs:jar:2.2.0:compile > >>>>>>> [INFO] | | +- > >>>>>>> org.apache.hadoop:hadoop-mapreduce-client-app:jar:2.2.0:compile > >>>>>>> [INFO] | | | +- > >>>>>>> org.apache.hadoop:hadoop-mapreduce-client-common:jar:2.2.0:compile > >>>>>>> [INFO] | | | | +- > >>>>>>> org.apache.hadoop:hadoop-yarn-client:jar:2.2.0:compile > >>>>>>> [INFO] | | | | | +- com.google.inject:guice:jar:3.0:compile > >>>>>>> [INFO] | | | | | | +- javax.inject:javax.inject:jar:1:compile > >>>>>>> [INFO] | | | | | | \- aopalliance:aopalliance:jar:1.0:compile > >>>>>>> [INFO] | | | | | +- > >>>>>>> > >>>>>>> > >> > com.sun.jersey.jersey-test-framework:jersey-test-framework-grizzly2:jar:1.9:compile > >>>>>>> [INFO] | | | | | | +- > >>>>>>> > >>>>>>> > >> > com.sun.jersey.jersey-test-framework:jersey-test-framework-core:jar:1.9:compile > >>>>>>> [INFO] | | | | | | | +- > >>>>>>> javax.servlet:javax.servlet-api:jar:3.0.1:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>> com.sun.jersey:jersey-client:jar:1.9:compile > >>>>>>> [INFO] | | | | | | \- > >>>>> com.sun.jersey:jersey-grizzly2:jar:1.9:compile > >>>>>>> [INFO] | | | | | | +- > >>>>>>> org.glassfish.grizzly:grizzly-http:jar:2.1.2:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>>>> org.glassfish.grizzly:grizzly-framework:jar:2.1.2:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>>>> org.glassfish.gmbal:gmbal-api-only:jar:3.0.0-b023:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>>>> org.glassfish.external:management-api:jar:3.0.0-b012:compile > >>>>>>> [INFO] | | | | | | +- > >>>>>>> org.glassfish.grizzly:grizzly-http-server:jar:2.1.2:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>>>> org.glassfish.grizzly:grizzly-rcm:jar:2.1.2:compile > >>>>>>> [INFO] | | | | | | +- > >>>>>>> org.glassfish.grizzly:grizzly-http-servlet:jar:2.1.2:compile > >>>>>>> [INFO] | | | | | | \- > >>>>> org.glassfish:javax.servlet:jar:3.1:compile > >>>>>>> [INFO] | | | | | +- > com.sun.jersey:jersey-server:jar:1.9:compile > >>>>>>> [INFO] | | | | | | +- asm:asm:jar:3.1:compile > >>>>>>> [INFO] | | | | | | \- > >> com.sun.jersey:jersey-core:jar:1.9:compile > >>>>>>> [INFO] | | | | | +- com.sun.jersey:jersey-json:jar:1.9:compile > >>>>>>> [INFO] | | | | | | +- > >>>>> org.codehaus.jettison:jettison:jar:1.1:compile > >>>>>>> [INFO] | | | | | | | \- stax:stax-api:jar:1.0.1:compile > >>>>>>> [INFO] | | | | | | +- > >>>>> com.sun.xml.bind:jaxb-impl:jar:2.2.3-1:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>> javax.xml.bind:jaxb-api:jar:2.2.2:compile > >>>>>>> [INFO] | | | | | | | \- > >>>>>>> javax.activation:activation:jar:1.1:compile > >>>>>>> [INFO] | | | | | | +- > >>>>>>> org.codehaus.jackson:jackson-jaxrs:jar:1.8.3:compile > >>>>>>> [INFO] | | | | | | \- > >>>>>>> org.codehaus.jackson:jackson-xc:jar:1.8.3:compile > >>>>>>> [INFO] | | | | | \- > >>>>>>> com.sun.jersey.contribs:jersey-guice:jar:1.9:compile > >>>>>>> [INFO] | | | | \- > >>>>>>> org.apache.hadoop:hadoop-yarn-server-common:jar:2.2.0:compile > >>>>>>> [INFO] | | | \- > >>>>>>> org.apache.hadoop:hadoop-mapreduce-client-shuffle:jar:2.2.0:compile > >>>>>>> [INFO] | | +- org.apache.hadoop:hadoop-yarn-api:jar:2.2.0:compile > >>>>>>> [INFO] | | +- > >>>>>>> org.apache.hadoop:hadoop-mapreduce-client-core:jar:2.2.0:compile > >>>>>>> [INFO] | | | \- > >>>>> org.apache.hadoop:hadoop-yarn-common:jar:2.2.0:compile > >>>>>>> [INFO] | | +- > >>>>>>> > org.apache.hadoop:hadoop-mapreduce-client-jobclient:jar:2.2.0:compile > >>>>>>> [INFO] | | \- > >> org.apache.hadoop:hadoop-annotations:jar:2.2.0:compile > >>>>>>> [INFO] | +- net.java.dev.jets3t:jets3t:jar:0.7.1:compile > >>>>>>> [INFO] | | +- commons-codec:commons-codec:jar:1.3:compile > >>>>>>> [INFO] | | \- > commons-httpclient:commons-httpclient:jar:3.1:compile > >>>>>>> [INFO] | +- org.apache.curator:curator-recipes:jar:2.4.0:compile > >>>>>>> [INFO] | | +- > >> org.apache.curator:curator-framework:jar:2.4.0:compile > >>>>>>> [INFO] | | | \- > >> org.apache.curator:curator-client:jar:2.4.0:compile > >>>>>>> [INFO] | | \- org.apache.zookeeper:zookeeper:jar:3.4.5:compile > >>>>>>> [INFO] | | \- jline:jline:jar:0.9.94:compile > >>>>>>> [INFO] | +- > >> org.eclipse.jetty:jetty-plus:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | +- > >>>>>>> > >> > org.eclipse.jetty.orbit:javax.transaction:jar:1.1.1.v201105210645:compile > >>>>>>> [INFO] | | +- > >>>>> org.eclipse.jetty:jetty-webapp:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | | +- > >>>>> org.eclipse.jetty:jetty-xml:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | | \- > >>>>>>> org.eclipse.jetty:jetty-servlet:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | \- > >>>>> org.eclipse.jetty:jetty-jndi:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | \- > >>>>>>> > >>>>>>> > >> > org.eclipse.jetty.orbit:javax.mail.glassfish:jar:1.4.1.v201005082020:compile > >>>>>>> [INFO] | | \- > >>>>>>> > >> org.eclipse.jetty.orbit:javax.activation:jar:1.1.0.v201105071233:compile > >>>>>>> [INFO] | +- > >>>>> org.eclipse.jetty:jetty-security:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | +- > >> org.eclipse.jetty:jetty-util:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | +- > >>>>> org.eclipse.jetty:jetty-server:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | +- > >>>>>>> > org.eclipse.jetty.orbit:javax.servlet:jar:3.0.0.v201112011016:compile > >>>>>>> [INFO] | | +- > >>>>>>> org.eclipse.jetty:jetty-continuation:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | \- > >>>>> org.eclipse.jetty:jetty-http:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | | \- > >>>>> org.eclipse.jetty:jetty-io:jar:8.1.14.v20131031:compile > >>>>>>> [INFO] | +- com.google.guava:guava:jar:16.0:compile > >>>>>>> d > >>>>>>> > >>>>>>> On Fri, Jan 30, 2015 at 4:03 PM, Dmitriy Lyubimov < > dlie...@gmail.com > >>>>>>> wrote: > >>>>>>> > >>>>>>>> looks like it is also requested by mahout-math, wonder what is > using > >>>>> it > >>>>>>>> there. > >>>>>>>> > >>>>>>>> At very least, it needs to be synchronized to the one currently > used > >>>>> by > >>>>>>>> spark. > >>>>>>>> > >>>>>>>> [INFO] --- maven-dependency-plugin:2.8:tree (default-cli) @ > >>>>> mahout-hadoop > >>>>>>>> --- > >>>>>>>> [INFO] org.apache.mahout:mahout-hadoop:jar:1.0-SNAPSHOT > >>>>>>>> *[INFO] +- org.apache.mahout:mahout-math:jar:1.0-SNAPSHOT:compile* > >>>>>>>> [INFO] | +- org.apache.commons:commons-math3:jar:3.2:compile > >>>>>>>> *[INFO] | +- com.google.guava:guava:jar:16.0:compile* > >>>>>>>> [INFO] | \- com.tdunning:t-digest:jar:2.0.2:compile > >>>>>>>> [INFO] +- > >>>>> org.apache.mahout:mahout-math:test-jar:tests:1.0-SNAPSHOT:test > >>>>>>>> [INFO] +- org.apache.hadoop:hadoop-client:jar:2.2.0:compile > >>>>>>>> [INFO] | +- org.apache.hadoop:hadoop-common:jar:2.2.0:compile > >>>>>>>> > >>>>>>>> > >>>>>>>> On Fri, Jan 30, 2015 at 7:52 AM, Pat Ferrel < > p...@occamsmachete.com> > >>>>>>> wrote: > >>>>>>>>> Looks like Guava is in Spark. > >>>>>>>>> > >>>>>>>>> On Jan 29, 2015, at 4:03 PM, Pat Ferrel <p...@occamsmachete.com> > >>>>> wrote: > >>>>>>>>> IndexedDataset uses Guava. Can’t tell from sure but it sounds > like > >>>>> this > >>>>>>>>> would not be included since I think it was taken from the > mrlegacy > >>>>> jar. > >>>>>>>>> On Jan 25, 2015, at 10:52 AM, Dmitriy Lyubimov < > dlie...@gmail.com> > >>>>>>> wrote: > >>>>>>>>> ---------- Forwarded message ---------- > >>>>>>>>> From: "Pat Ferrel" <p...@occamsmachete.com> > >>>>>>>>> Date: Jan 25, 2015 9:39 AM > >>>>>>>>> Subject: Re: Codebase refactoring proposal > >>>>>>>>> To: <dev@mahout.apache.org> > >>>>>>>>> Cc: > >>>>>>>>> > >>>>>>>>>> When you get a chance a PR would be good. > >>>>>>>>> Yes, it would. And not just for that. > >>>>>>>>> > >>>>>>>>>> As I understand it you are putting some class jars somewhere in > >> the > >>>>>>>>> classpath. Where? How? > >>>>>>>>> /bin/mahout > >>>>>>>>> > >>>>>>>>> (Computes 2 different classpaths. See 'bin/mahout classpath' vs. > >>>>>>>>> 'bin/mahout -spark'.) > >>>>>>>>> > >>>>>>>>> If i interpret current shell code there correctky, legacy path > >> tries > >>>>> to > >>>>>>>>> use > >>>>>>>>> examples assemblies if not packaged, or /lib if packaged. True > >>>>>>> motivation > >>>>>>>>> of that significantly predates 2010 and i suspect only Benson > knows > >>>>>>> whole > >>>>>>>>> true intent there. > >>>>>>>>> > >>>>>>>>> The spark path, which is really a quick hack of the script, tries > >> to > >>>>> get > >>>>>>>>> only selected mahout jars and locally instlalled spark classpath > >>>>> which i > >>>>>>>>> guess is just the shaded spark jar in recent spark releases. It > >> also > >>>>>>>>> apparently tries to include /libs/*, which is never compiled in > >>>>>>> unpackaged > >>>>>>>>> version, and now i think it is a bug it is included because > >> /libs/* > >>>>> is > >>>>>>>>> apparently legacy packaging, and shouldnt be used in spark jobs > >>>>> with a > >>>>>>>>> wildcard. I cant beleive how lazy i am, i still did not find time > >> to > >>>>>>>>> understand mahout build in all cases. > >>>>>>>>> > >>>>>>>>> I am not even sure if packaged mahout will work with spark, > >> honestly, > >>>>>>>>> because of the /lib. Never tried that, since i mostly use > >> application > >>>>>>>>> embedding techniques. > >>>>>>>>> > >>>>>>>>> The same solution may apply to adding external dependencies and > >>>>> removing > >>>>>>>>> the assembly in the Spark module. Which would leave only one > major > >>>>> build > >>>>>>>>> issue afaik. > >>>>>>>>>> On Jan 24, 2015, at 11:53 PM, Dmitriy Lyubimov < > dlie...@gmail.com > >>>>>>>>> wrote: > >>>>>>>>>> No, no PR. Only experiment on private. But i believe i > >> sufficiently > >>>>>>>>> defined > >>>>>>>>>> what i want to do in order to gauge if we may want to advance it > >>>>> some > >>>>>>>>> time > >>>>>>>>>> later. Goal is much lighter dependency for spark code. Eliminate > >>>>>>>>> everything > >>>>>>>>>> that is not compile-time dependent. (and a lot of it is thru > >> legacy > >>>>> MR > >>>>>>>>> code > >>>>>>>>>> which we of course don't use). > >>>>>>>>>> > >>>>>>>>>> Cant say i understand the remaining issues you are talking about > >>>>>>> though. > >>>>>>>>>> If you are talking about compiling lib or shaded assembly, no, > >> this > >>>>>>>>> doesn't > >>>>>>>>>> do anything about it. Although point is, as it stands, the > algebra > >>>>> and > >>>>>>>>>> shell don't have any external dependencies but spark and these 4 > >>>>> (5?) > >>>>>>>>>> mahout jars so they technically don't even need an assembly (as > >>>>>>>>>> demonstrated). > >>>>>>>>>> > >>>>>>>>>> As i said, it seems driver code is the only one that may need > some > >>>>>>>>> external > >>>>>>>>>> dependencies, but that's a different scenario from those i am > >>>>> talking > >>>>>>>>>> about. But i am relatively happy with having the first two > working > >>>>>>>>> nicely > >>>>>>>>>> at this point. > >>>>>>>>>> > >>>>>>>>>> On Sat, Jan 24, 2015 at 9:06 AM, Pat Ferrel < > >> p...@occamsmachete.com> > >>>>>>>>> wrote: > >>>>>>>>>>> +1 > >>>>>>>>>>> > >>>>>>>>>>> Is there a PR? You mention a "tiny mahout-hadoop” module. It > >> would > >>>>> be > >>>>>>>>> nice > >>>>>>>>>>> to see how you’ve structured that in case we can use the same > >>>>> model to > >>>>>>>>>>> solve the two remaining refactoring issues. > >>>>>>>>>>> 1) external dependencies in the spark module > >>>>>>>>>>> 2) no spark or h2o in the release artifacts. > >>>>>>>>>>> > >>>>>>>>>>> On Jan 23, 2015, at 6:45 PM, Shannon Quinn <squ...@gatech.edu> > >>>>> wrote: > >>>>>>>>>>> Also +1 > >>>>>>>>>>> > >>>>>>>>>>> iPhone'd > >>>>>>>>>>> > >>>>>>>>>>>> On Jan 23, 2015, at 18:38, Andrew Palumbo <ap....@outlook.com > > > >>>>>>> wrote: > >>>>>>>>>>>> +1 > >>>>>>>>>>>> > >>>>>>>>>>>> > >>>>>>>>>>>> Sent from my Verizon Wireless 4G LTE smartphone > >>>>>>>>>>>> > >>>>>>>>>>>> <div>-------- Original message --------</div><div>From: > Dmitriy > >>>>>>>>> Lyubimov > >>>>>>>>>>> <dlie...@gmail.com> </div><div>Date:01/23/2015 6:06 PM > >>>>> (GMT-05:00) > >>>>>>>>>>> </div><div>To: dev@mahout.apache.org </div><div>Subject: > >> Codebase > >>>>>>>>>>> refactoring proposal </div><div> > >>>>>>>>>>>> </div> > >>>>>>>>>>>> So right now mahout-spark depends on mr-legacy. > >>>>>>>>>>>> I did quick refactoring and it turns out it only _irrevocably_ > >>>>>>> depends > >>>>>>>>> on > >>>>>>>>>>>> the following classes there: > >>>>>>>>>>>> > >>>>>>>>>>>> MatrixWritable, VectorWritable, Varint/Varlong and > >> VarintWritable, > >>>>>>> and > >>>>>>>>>>> ... > >>>>>>>>>>>> *sigh* o.a.m.common.Pair > >>>>>>>>>>>> > >>>>>>>>>>>> So I just dropped those five classes into new a new tiny > >>>>>>>>> mahout-hadoop > >>>>>>>>>>>> module (to signify stuff that is directly relevant to > >> serializing > >>>>>>>>> thigns > >>>>>>>>>>> to > >>>>>>>>>>>> DFS API) and completely removed mrlegacy and its transients > from > >>>>>>> spark > >>>>>>>>>>> and > >>>>>>>>>>>> spark-shell dependencies. > >>>>>>>>>>>> > >>>>>>>>>>>> So non-cli applications (shell scripts and embedded api use) > >>>>> actually > >>>>>>>>>>> only > >>>>>>>>>>>> need spark dependencies (which come from SPARK_HOME classpath, > >> of > >>>>>>>>> course) > >>>>>>>>>>>> and mahout jars (mahout-spark, mahout-math(-scala), > >> mahout-hadoop > >>>>> and > >>>>>>>>>>>> optionally mahout-spark-shell (for running shell)). > >>>>>>>>>>>> > >>>>>>>>>>>> This of course still doesn't address driver problems that want > >> to > >>>>>>>>> throw > >>>>>>>>>>>> more stuff into front-end classpath (such as cli parser) but > at > >>>>> least > >>>>>>>>> it > >>>>>>>>>>>> renders transitive luggage of mr-legacy (and the size of > >>>>>>>>> worker-shipped > >>>>>>>>>>>> jars) much more tolerable. > >>>>>>>>>>>> > >>>>>>>>>>>> How does that sound? > >>>>>>>>> > >> > >> > > >
