Relative Error Streaming Quantiles-Reference-Cited by-同舟云学术

Relative Error Streaming Quantiles

Published:2022-05-31 Issue:1 Volume:51 Page:69-76
ISSN:0163-5808
Container-title:ACM SIGMOD Record
language:en
Short-container-title:SIGMOD Rec.

Author:

Cormode Graham¹,Karnin Zohar²,Liberty Edo³,Thaler Justin⁴,Vesely Pavel⁵

Affiliation:

1. University of Warwick Coventry, UK

2. Amazon, USA

3. Pinecone San Mateo, CA, USA

4. Georgetown University Washington, D.C., USA

5. Charles University Prague, Czech Republic

Abstract

Estimating ranks, quantiles, and distributions over streaming data is a central task in data analysis and monitoring. Given a stream of n items from a data universe equipped with a total order, the task is to compute a sketch (data structure) of size polylogarithmic in n. Given the sketch and a query item y, one should be able to approximate its rank in the stream, i.e., the number of stream elements smaller than or equal to y.

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems,Software

Link

https://dl.acm.org/doi/pdf/10.1145/3542700.3542717

Reference29 articles.

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4. G. Cormode , Z. Karnin , E. Liberty , J. Thaler , and P. Vesel´y . Relative error streaming quantiles. arXiv preprint arXiv:2004.01668 , 2020 . G. Cormode, Z. Karnin, E. Liberty, J. Thaler, and P. Vesel´y. Relative error streaming quantiles. arXiv preprint arXiv:2004.01668, 2020.

5. Effective Computation of Biased Quantiles over Data Streams