=Paper=
{{Paper
|id=Vol-1521/paper7
|storemode=property
|title=Mining Big Data Streams with Apache SAMOA
|pdfUrl=https://ceur-ws.org/Vol-1521/paper7.pdf
|volume=Vol-1521
|dblpUrl=https://dblp.org/rec/conf/pkdd/Bifet15
}}
==Mining Big Data Streams with Apache SAMOA==
<pdf width="1500px">https://ceur-ws.org/Vol-1521/paper7.pdf</pdf>
<pre>
    Mining Big Data Streams with Apache SAMOA

                                       Albert Bifet

                          LTCI, CNRS, Télécom ParisTech,
                      Université Paris-Saclay, 75013, Paris, France



    Abstract. In this talk, we present Apache SAMOA, an open-source platform for
    mining big data streams with Apache Flink, Storm and Samza. Real time ana-
    lytics is becoming the fastest and most efficient way to obtain useful knowledge
    from what is happening now, allowing organizations to react quickly when prob-
    lems appear or to detect new trends helping to improve their performance. Apache
    SAMOA includes algorithms for the most common machine learning tasks such
    as classification and clustering. It provides a pluggable architecture that allows it
    to run on Apache Flink, but also with other several distributed stream processing
    engines such as Storm and Samza.




Copyright c 2015 by the paper’s authors. Copying permitted only for private and academic
purposes. In: M. Atzmueller, F. Lemmerich (Eds.): Proceedings of 6th International Workshop
on Mining Ubiquitous and Social Environments (MUSE), co-located with the ECML PKDD
2015. Published at http://ceur-ws.org

</pre>