Thursday, 07 December 2017 10:37

Seminario: Big data analytics beyond MapReduce

Written by 

Venerdì 15 Dicembre 2015, ore 14,00-16,00, nell'Aula P1.6, nell'ambito degli Insegnamenti di Big Data Analysis e Progettazione del Software del Corso di laurea magistrale in INGEGNERIA INFORMATICA, il dottore di ricerca Matteo Interlandi, terrà il  Seminario:


" Big data analytics beyond MapReduce"

Abstract: MapReduce was introduced by Google in 2004. Thanks to its functional programming abstraction and fault-tolerant distributed framework, MapReduce makes easy to write parallel programs. In 2004 MapReduce was mostly used for web indexing; however nowadays we are seeing different type of applications (relational, graphs or machine learning analytics for example) which does not fit well within the MapReduce paradigm. In this talk I will use some research projects I have been working on in the past years to (1) introduce Apache Spark and Apache REEF; (2) describe how relational, graphs and machine learning applications can be efficiently run at scale using such systems; and (3) illustrate system's pros, cons and design choices.

Bio: Matteo Interlandi is a Research Scientist in the Cloud and Information Services Lab (CISL) at Microsoft, working on scalable Machine Learning Systems. Before Microsoft, he was a Postdoctoral Scholar in the CS Department at the University of California, Los Angeles. Prior to joining UCLA, he was Research Associate at the Qatar Computing Research Institute and at the Institute for Human and Machine Cognition. He obtained his PhD in Computer Science at the University of Modena and Reggio Emilia under the supervision of Sonia Bergamaschi.

Copyright @  2017   DataBase Group for suggestions write to  Webmaster