|Title||:||Large Scale Data Analytics and the Role of Stratified Data Placement|
|Speaker||:||Srinivasan Parthasarathy (Ohio State University)|
|Details||:||Tue, 21 Jul, 2015 2:00 PM @ BSB 361|
|Abstract:||:||With the increasing popularity of XML data stores, social
networks and Web 2.0 and 3.0 applications, complex data formats, such
as trees and graphs, are becoming ubiquitous. Managing and processing
such large and complex data stores, on modern computational
eco-systems, to realize actionable information efficiently, is
daunting. In this talk I will begin with discussing some of these
challenges. Subsequently I will discuss a critical element at the
heart of this challenge relates to the placement, storage and access
of such tera- and peta- scale data. In this work we develop a novel
distributed framework to ease the burden on the programmer and propose
an agile and intelligent placement service layer as a flexible yet
unified means to address this challenge. Central to our framework is
the notion of stratification which seeks to initially group
structurally (or semantically) similar entities into strata.
Subsequently strata are partitioned within this eco- system according
to the needs of the application to maximize locality, balance load,
minimize data skew or even take into account energy consumption.
Results on several real-world applications validate the efficacy and
efficiency of our approach.
Bio: Srinivasan Parthasarathy is a Professor in the Dept. of Computer Science and Engineering and Department of Biomedical Informatics at the The Ohio State University, Columbus, Ohio. He heads the Data Mining Research Lab at OSU wherein his he primarily works in data mining/machine learning and high performance computing and database systems. His group develops efficient and novel algorithms for managing and analyzing complex data. His current research is particularly motivated by applications that arise in the area of network science specifically biological networks and social networks. He is the recipient of numerous honors such as the IBM Faculty Award, the OSU Lumley Research Award and the Google Research Award to name a few.