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Title: Streaming Quantiles Algorithms with Small Space and Update Time
Approximating quantiles and distributions over streaming data has been studied for roughly two decades now. Recently, Karnin, Lang, and Liberty proposed the first asymptotically optimal algorithm for doing so. This manuscript complements their theoretical result by providing a practical variants of their algorithm with improved constants. For a given sketch size, our techniques provably reduce the upper bound on the sketch error by a factor of two. These improvements are verified experimentally. Our modified quantile sketch improves the latency as well by reducing the worst-case update time from O(1ε) down to O(log1ε).  more » « less
Award ID(s):
2244899 2107239 2333887
NSF-PAR ID:
10396505
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Sensors
Volume:
22
Issue:
24
ISSN:
1424-8220
Page Range / eLocation ID:
9612
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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