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Optimal tracking of distributed heavy hitters and quantiles
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Symposium on Principles of Database Systems archive
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems table of contents
Providence, Rhode Island, USA
SESSION: Stream processing table of contents
Pages 167-174  
Year of Publication: 2009
ISBN:978-1-60558-553-6
Authors
Ke Yi  HKUST, Hong Kong, China
Qin Zhang  HKUST, Hong Kong, China
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGMOD: ACM Special Interest Group on Management of Data
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

We consider the 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 ⋅ log n) 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.


REFERENCES

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