Streaming Quantiles Algorithms with Small Space and Update Time.

Content Provider	Europe PMC
Author	Ivkin, Nikita Liberty, Edo Lang, Kevin Karnin, Zohar Braverman, Vladimir
Editor	Feldman, Dan
Copyright Year	2022
Abstract	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).
Journal	Sensors (Basel, Switzerland)
Volume Number	22
DOI	10.3390/s22249612
PubMed Central reference number	PMC9783260
Issue Number	24
PubMed reference number	36559998
e-ISSN	14248220
Language	English
Publisher	Molecular Diversity Preservation International (MDPI)
Publisher Date	2022-12-08
Access Restriction	Open
Subject Keyword	sketching quantiles streaming
Content Type	Text
Resource Type	Article
Subject	Biochemistry Instrumentation Information Systems Medicine Analytical Chemistry Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering