Finding frequent items in data streams

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Finding frequent items in data streams (2002)

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by Moses Charikar , Kevin Chen , Martin Farach-colton

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@INPROCEEDINGS{Charikar02findingfrequent,
    author = {Moses Charikar and Kevin Chen and Martin Farach-colton},
    title = {Finding frequent items in data streams},
    booktitle = {},
    year = {2002},
    pages = {693--703}
}

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Abstract

Abstract. We present a 1-pass algorithm for estimating the most frequent items in a data stream using very limited storage space. Our method relies on a novel data structure called a count sketch, which allows us to estimate the frequencies of all the items in the stream. Our algorithm achieves better space bounds than the previous best known algorithms for this problem for many natural distributions on the item frequencies. In addition, our algorithm leads directly to a 2-pass algorithm for the problem of estimating the items with the largest (absolute) change in frequency between two data streams. To our knowledge, this problem has not been previously studied in the literature. 1

Keyphrases

data stream frequent item limited storage space count sketch novel data structure space bound item frequency many natural distribution 1-pass algorithm 2-pass algorithm method relies

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