Can We Make Big Data Management Easier?
Channel: The DRIVE/conference
Date: 19/03/2014

Today's Big Data management systems and services are increasingly fast but they are not always easy to use. In this talk, we present recent research results around the theme of facilitating the management and processing of Big Data. We first present Presonalized Service Level Agreements, a new type of SLAs for Cloud services, where users can forget about numbers of instances and bytes processed. Instead, users upload their data and are shown a personalized menu of fixed hourly prices associated with different query performance and capability choices. Second, once users have access to a data management service, they need to write SQL queries to explore their data. We present SnipSuggest, an autocompletion tool for SQL that provides context-aware assistance in the query composition process. Finally, once the user executes a query, the performance may be different from what they expected. Here, we describe, PerfXplain, a tool for explaining the performance of MapReduce jobs running on a shared-nothing cluster.

Magdalena Balazinska is an Associate Professor in the department of Computer Science and Engineering at the University of Washington. Magdalena's research interests are in the field of database management systems. Her current research focuses on big data management, sensor and scientific data management, and cloud computing. Magdalena holds a Ph.D. from the Massachusetts Institute of Technology (2006). She is a Microsoft Research New Faculty Fellow (2007), received an NSF CAREER Award (2009), a 10-year most influential paper award (2010), an HP Labs Research Innovation Award (2009 and 2010), a Rogel Faculty Support Award (2006), a Microsoft Research Graduate Fellowship (2003-2005), and multiple best-paper awards.