quantile-alg

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Best quantile algorithms for data streams

GK and Random are available. implemented by Lu Wang [email protected]

To build the code, you need the Boost C++ Library and a compiler which supports C++11

Part of the work "Quantile over Data Streams: An Experimental Study"

Slides of the work can be found here, which describes a (much) simplified version of the algorithm.

All the source code are released under the MIT license.

If you use the code, please cite our work:

@inproceedings{Wang:2013:QOD:2463676.2465312,
 author = {Wang, Lu and Luo, Ge and Yi, Ke and Cormode, Graham},
 title = {Quantiles over data streams: an experimental study},
 booktitle = {Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data},
 series = {SIGMOD '13},
 year = {2013},
 isbn = {978-1-4503-2037-5},
 location = {New York, New York, USA},
 pages = {737--748},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/2463676.2465312},
 doi = {10.1145/2463676.2465312},
 acmid = {2465312},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {data stream algorithms, quantiles},
}