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2015 | OriginalPaper | Chapter

Weighted Random Sampling over Data Streams

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Author: Pavlos S. Efraimidis

Publisher: Springer International Publishing

Published in: Algorithms, Probability, Networks, and Games

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Abstract

In this work, we present a comprehensive treatment of weighted random sampling (WRS) over data streams. More precisely, we examine two natural interpretations of the item weights, describe an existing algorithm for each case [3, 8], discuss sampling with and without replacement and show adaptations of the algorithms for several WRS problems and evolving data streams.

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We say “supposed” because even though WRS is best described with a sequential sampling procedure, it is not inherently sequential. Algorithm A-ES [ 8] which we will use to solve WRS-W problems can be executed on sequential, parallel and distributed settings.

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Title

Weighted Random Sampling over Data Streams

Book

Algorithms, Probability, Networks, and Games

Print ISBN: 978-3-319-24023-7

Electronic ISBN: 978-3-319-24024-4

https://doi.org/10.1007/978-3-319-24024-4

DOI

https://doi.org/10.1007/978-3-319-24024-4_12

Author:

Pavlos S. Efraimidis

Publisher

Springer International Publishing

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