Sciweavers

SIGMOD
2008
ACM

Sampling time-based sliding windows in bounded space

14 years 3 months ago
Sampling time-based sliding windows in bounded space
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often interested in analyzing only the most recent fraction of the data stream in order to avoid outdated results. In this paper, we focus on sampling schemes that sample from a sliding window over a recent time interval; such windows are a popular and highly comprehensible method to model recency. In this setting, the main challenge is to guarantee an upper bound on the space consumption of the sample while using the allotted space efficiently at the same time. The difficulty arises from the fact that the number of items in the window is unknown in advance and may vary significantly over time, so that the sampling fraction has to be adjusted dynamically. We consider uniform sampling schemes, which produce each sample of the same size with equal probability, and stratified sampling schemes, in which the window is divide...
Rainer Gemulla, Wolfgang Lehner
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2008
Where SIGMOD
Authors Rainer Gemulla, Wolfgang Lehner
Comments (0)