Re: Codebase refactoring proposal

[Andrew Palumbo]

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.

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
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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
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[INFO] |  |  |  |  |  |  \- com.sun.jersey:jersey-core:jar:1.9:compile
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org.codehaus.jettison:jettison:jar:1.1:compile

[INFO] |  |  |  |  |  |  |  \- stax:stax-api:jar:1.0.1:compile
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com.sun.xml.bind:jaxb-impl:jar:2.2.3-1:compile

[INFO] |  |  |  |  |  |  |  \-

javax.xml.bind:jaxb-api:jar:2.2.2:compile

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javax.activation:activation:jar:1.1:compile
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org.codehaus.jackson:jackson-jaxrs:jar:1.8.3:compile
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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

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org.eclipse.jetty:jetty-webapp:jar:8.1.14.v20131031:compile

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org.eclipse.jetty:jetty-xml:jar:8.1.14.v20131031:compile

[INFO] |  |  |  \-
org.eclipse.jetty:jetty-servlet:jar:8.1.14.v20131031:compile
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org.eclipse.jetty:jetty-jndi:jar:8.1.14.v20131031:compile

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org.eclipse.jetty.orbit:javax.mail.glassfish:jar:1.4.1.v201005082020:compile

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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?