Mailing-List: contact issues-help@flink.apache.org; run by ezmlm
Precedence: bulk
Reply-To: dev@flink.apache.org
Date: Thu, 21 May 2015 09:11:00 +0000 (UTC)
From: "ASF GitHub Bot (JIRA)" <jira@apache.org>
To: issues@flink.apache.org
Message-ID: <JIRA.12830667.1431952896000.179243.1432199460691@Atlassian.JIRA>
In-Reply-To: <JIRA.12830667.1431952896000@Atlassian.JIRA>
References: <JIRA.12830667.1431952896000@Atlassian.JIRA>
 <JIRA.12830667.1431952896854@arcas>
Subject: [jira] [Commented] (FLINK-2034) Add vision and roadmap for ML
 library to docs
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: quoted-printable


    [ https://issues.apache.org/jira/browse/FLINK-2034?page=3Dcom.atlassian=
.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=3D1455=
3946#comment-14553946 ]=20

ASF GitHub Bot commented on FLINK-2034:
---------------------------------------

Github user tillrohrmann commented on a diff in the pull request:

    https://github.com/apache/flink/pull/688#discussion_r30784829
 =20
    --- Diff: docs/libs/ml/index.md ---
    @@ -20,8 +20,100 @@ specific language governing permissions and limitat=
ions
     under the License.
     -->
    =20
    +The Machine Learning (ML) library for Flink is a new effort to bring s=
calable ML tools to the Flink
    +community. Our goal is is to design and implement a system that is sca=
lable and can deal with
    +problems of various sizes, whether your data size is measured in megab=
ytes or terabytes and beyond.
    +We call this library FlinkML.
    +
    +An important concern for developers of ML systems is the amount of glu=
e code that developers are
    +forced to write [1] in the process of implementing an end-to-end ML sy=
stem. Our goal with FlinkML
    +is to help developers keep glue code to a minimum. The Flink ecosystem=
 provides a great setting to
    +tackle this problem, with its scalable ETL capabilities that can be ea=
sily combined inside the same
    +program with FlinkML, allowing the development of robust pipelines wit=
hout the need to use yet
    +another technology for data ingestion and data munging.
    +
    +Another goal for FlinkML is to make the library easy to use. To that e=
nd we will be providing
    +detailed documentation along with examples for every part of the syste=
m. Our aim is that developers
    +will be able to get started with writing their ML pipelines quickly, u=
sing familiar programming
    +concepts and terminology.
    +
    +Contrary to other data-processing systems, Flink exploits in-memory da=
ta streaming, and natively
    +executes iterative processing algorithms which are common in ML. We pl=
an to exploit the streaming
    +nature of Flink, and provide functionality designed specifically for d=
ata streams.
    +
    +FlinkML will allow data scientists to test their models locally and us=
ing subsets of data, and then
    +use the same code to run their algorithms at a much larger scale in a =
cluster setting.
    +
    +We are inspired by other open source efforts to provide ML systems, in=
 particular
    +[scikit-learn](http://scikit-learn.org/) for cleanly specifying ML pip=
elines, and Spark=E2=80=99s
    +[MLLib](https://spark.apache.org/mllib/) for providing ML algorithms t=
hat scale with problem and
    +cluster sizes.
    +
    +We already have some of the building blocks for FlinkML in place, and =
will continue to extend the
    +library with more algorithms. An example of how simple it is to create=
 a learning model in
    +FlinkML is given below:
    --- End diff --
   =20
    Good idea to show how to use FlinkML. I would extend the example a litt=
le bit and put it into a separate section. Maybe making a small tutorial ou=
t of it including the things you have to add to the your pom etc.


> Add vision and roadmap for ML library to docs
> ---------------------------------------------
>
>                 Key: FLINK-2034
>                 URL: https://issues.apache.org/jira/browse/FLINK-2034
>             Project: Flink
>          Issue Type: Improvement
>          Components: Machine Learning Library
>            Reporter: Theodore Vasiloudis
>            Assignee: Theodore Vasiloudis
>              Labels: ML
>             Fix For: 0.9
>
>
> We should have a document describing the vision of the Machine Learning l=
ibrary in Flink and an up to date roadmap.


--
This message was sent by Atlassian JIRA
(v6.3.4#6332)