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Optimal Tracking of Distributed Heavy Hitters and Quantiles

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Abstract

We consider the problem of tracking heavy hitters and quantiles in the distributed streaming model. The heavy hitters and quantiles are two important statistics for characterizing a data distribution. Let A be a multiset of elements, drawn from the universe U={1,…,u}. For a given 0≤ϕ≤1, the ϕ-heavy hitters are those elements of A whose frequency in A is at least ϕ|A|; the ϕ-quantile of A is an element x of U such that at most ϕ|A| elements of A are smaller than A and at most (1−ϕ)|A| elements of A are greater than x. Suppose the elements of A are received at k remote sites over time, and each of the sites has a two-way communication channel to a designated coordinator, whose goal is to track the set of ϕ-heavy hitters and the ϕ-quantile of A approximately at all times with minimum communication. We give tracking algorithms with worst-case communication cost O(k/ϵ⋅logn) for both problems, where n is the total number of items in A, and ϵ is the approximation error. This substantially improves upon the previous known algorithms. We also give matching lower bounds on the communication costs for both problems, showing that our algorithms are optimal. We also consider a more general version of the problem where we simultaneously track the ϕ-quantiles for all 0≤ϕ≤1.

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Correspondence to Qin Zhang.

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A preliminary version of this article was presented at the ACM Symposium on Principles of Database Systems (PODS), 2009.

Ke Yi supported in part by a DAG and an RPC grant from HKUST, and a Google Faculty Research Award.

Most of this work was done while Qin Zhang was a Ph.D. student at HKUST.

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Yi, K., Zhang, Q. Optimal Tracking of Distributed Heavy Hitters and Quantiles. Algorithmica 65, 206–223 (2013). https://doi.org/10.1007/s00453-011-9584-4

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