SCHEDULE: NOV 10-16, 2012
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Hadoop's Adolescence: A Comparative Workload Analysis from Three Research Clusters
SESSION: Research Poster Reception
EVENT TYPE: Posters and Electronic Posters
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Kai Ren, Garth Gibson, YongChul Kwon, Magdalena Balazinska, Bill Howe
ROOM:East Entrance
ABSTRACT:
We analyze Hadoop workloads from three different research clusters
from an application-level perspective, with two goals: (1) explore new
issues in application patterns and user behavior and (2) understand
key performance challenges related to IO. Our
analysis suggests that Hadoop usage is still in its adolescence. We
see underuse of Hadoop features, extensions, and tools as well as significant
opportunities for optimization. We see significant diversity in
application styles, including some ``interactive'' workloads,
motivating new tools in the ecosystem. We find that some conventional
approaches to improving performance are not especially effective and
suggest some alternatives. Overall, we find significant opportunity
for simplifying the use and optimization of Hadoop.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Kai Ren - Carnegie Mellon University
Garth Gibson - Carnegie Mellon University
YongChul Kwon - University of Washington
Magdalena Balazinska - University of Washington
Bill Howe - University of Washington
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Hadoop's Adolescence: A Comparative Workload Analysis from Three Research Clusters
SESSION: Research Poster Reception
EVENT TYPE:
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Kai Ren, Garth Gibson, YongChul Kwon, Magdalena Balazinska, Bill Howe
ROOM:East Entrance
ABSTRACT:
We analyze Hadoop workloads from three different research clusters
from an application-level perspective, with two goals: (1) explore new
issues in application patterns and user behavior and (2) understand
key performance challenges related to IO. Our
analysis suggests that Hadoop usage is still in its adolescence. We
see underuse of Hadoop features, extensions, and tools as well as significant
opportunities for optimization. We see significant diversity in
application styles, including some ``interactive'' workloads,
motivating new tools in the ecosystem. We find that some conventional
approaches to improving performance are not especially effective and
suggest some alternatives. Overall, we find significant opportunity
for simplifying the use and optimization of Hadoop.
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Kai Ren - Carnegie Mellon University
Garth Gibson - Carnegie Mellon University
YongChul Kwon - University of Washington
Magdalena Balazinska - University of Washington
Bill Howe - University of Washington
Click here to download .ics calendar file