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2007
IEEE

A Fast Algorithm for Approximate Quantiles in High Speed Data Streams

10 years 4 days ago
A Fast Algorithm for Approximate Quantiles in High Speed Data Streams
We present a fast algorithm for computing approximate quantiles in high speed data streams with deterministic error bounds. For data streams of size N where N is unknown in advance, our algorithm partitions the stream into sub-streams of exponentially increasing size as they arrive. For each sub-stream which has a fixed size, we compute and maintain a multi-level summary structure using a novel algorithm. In order to achieve high speed performance, the algorithm uses simple block-wise merge and sample operations. Overall, our algorithms for fixed-size streams and arbitrary-size streams have a computational cost of O(N log(1 log N)) and an average per-element update cost of O(log log N) if is fixed.
Qi Zhang, Wei Wang 0010
Added 04 Jun 2010
Updated 04 Jun 2010
Type Conference
Year 2007
Where SSDBM
Authors Qi Zhang, Wei Wang 0010
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