An accurate estimation algorithm for big data streams

An accurate estimation algorithm for big data streams Sketch is a memory-efficient data structure, and is used to store and query the frequency of any item in a given multiset. As it can achieve fast query and update, it has been applied to various fields. Different sketches have different advantages and disadvantages. Sketches are originally proposed for estimation of flow size in network measurement. The key factor of sketches for network measurement is the insertion speed and accuracy. In this paper, we propose a new sketch, which can significantly improve the insertion speed while improving the accuracy. Our key methods include on-chip/off-chip separation and partial update algorithm. Extensive experimental results show that our sketch significantly outperforms the state-of-the-art both in terms of accuracy and speed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Distributed and Parallel Databases Springer Journals

An accurate estimation algorithm for big data streams

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Computer Science; Database Management; Data Structures; Information Systems Applications (incl.Internet); Operating Systems; Memory Structures
ISSN
0926-8782
eISSN
1573-7578
D.O.I.
10.1007/s10619-018-7225-5
Publisher site
See Article on Publisher Site

Abstract

Sketch is a memory-efficient data structure, and is used to store and query the frequency of any item in a given multiset. As it can achieve fast query and update, it has been applied to various fields. Different sketches have different advantages and disadvantages. Sketches are originally proposed for estimation of flow size in network measurement. The key factor of sketches for network measurement is the insertion speed and accuracy. In this paper, we propose a new sketch, which can significantly improve the insertion speed while improving the accuracy. Our key methods include on-chip/off-chip separation and partial update algorithm. Extensive experimental results show that our sketch significantly outperforms the state-of-the-art both in terms of accuracy and speed.

Journal

Distributed and Parallel DatabasesSpringer Journals

Published: May 23, 2018

References

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