Sailesh Krishnamurthy and Michael J. Franklin
EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-05-1381
October 2005
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2005/CSD-05-1381.pdf
Widely dispersed monitoring networks generate huge data volumes that are naturally organized via hierarchical aggregation. In a system that manages such data, applications pose periodic aggregate queries. In this paper we show how to efficiently process multiple periodic aggregate queries in a hierarchy. First, we use a novel query rewrite that optimally executes individual queries. Next, we show how to combine the rewritten queries to share computation and communication resources. Finally, we identify a challenge in shared aggregation across a heterogenous hierarchy, namely that push-down reduces sharing and pull-up increases communication. We then propose a "partial push-down" technique that permits effective sharing without increasing communication costs.
BibTeX citation:
@techreport{Krishnamurthy:CSD-05-1381, Author = {Krishnamurthy, Sailesh and Franklin, Michael J.}, Title = {Shared Hierarchical Aggregation for Monitoring Distributed Streams}, Institution = {EECS Department, University of California, Berkeley}, Year = {2005}, Month = {Oct}, URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2005/6508.html}, Number = {UCB/CSD-05-1381}, Abstract = {Widely dispersed monitoring networks generate huge data volumes that are naturally organized via hierarchical aggregation. In a system that manages such data, applications pose periodic aggregate queries. In this paper we show how to efficiently process multiple periodic aggregate queries in a hierarchy. First, we use a novel query rewrite that optimally executes individual queries. Next, we show how to combine the rewritten queries to share computation and communication resources. Finally, we identify a challenge in shared aggregation across a heterogenous hierarchy, namely that push-down reduces sharing and pull-up increases communication. We then propose a "partial push-down" technique that permits effective sharing without increasing communication costs.} }
EndNote citation:
%0 Report %A Krishnamurthy, Sailesh %A Franklin, Michael J. %T Shared Hierarchical Aggregation for Monitoring Distributed Streams %I EECS Department, University of California, Berkeley %D 2005 %@ UCB/CSD-05-1381 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2005/6508.html %F Krishnamurthy:CSD-05-1381