Babcock, Brian and Datar, Mayur and Motwani, Rajeev (2004) Load Shedding for Aggregation Queries over Data Streams. In: 20th International Conference on Data Engineering (ICDE 2004), March 30 - April 2, 2004, Boston, MA.
Systems for processing continuous monitoring queries over data streams must be adaptive because data streams are often bursty and data characteristics may vary over time. In this paper, we focus on one particular type of adaptivity: the ability to gracefully degrade performance via "load shedding" (dropping unprocessed tuples to reduce system load) when the demands placed on the system cannot be met in full given available resources. Focusing on aggregation queries, we present algorithms that determine at what points in a query plan should load shedding be performed and what amount of load should be shed at each point in order to minimize the degree of inaccuracy introduced into query answers. We report the results of experiments that validate our analytical conclusions.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Computer Science > Data Streams|
|Related URLs:||Project Homepage||http://infolab.stanford.edu/stream/|
|Deposited By:||Import Account|
|Deposited On:||07 Jan 2004 16:00|
|Last Modified:||23 Dec 2008 08:38|
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