Library of streaming algorithms for processing massive data.
Project description
SketchLib
This package contains various streaming algorithms that are useful for processing massive scale data. For example, for calculating heavy-hitters in a data stream, implementations of the Misra-Gries and Count-Min algorithms are available. The problems that can be solved using this package include F0 and F2 estimation as well as set-membership inquiries (Bloom Filter).
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sketchlib-0.0.1.tar.gz
(11.3 kB
view hashes)
Built Distribution
sketchlib-0.0.1-py3-none-any.whl
(13.3 kB
view hashes)
Close
Hashes for sketchlib-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3516304dfed152b47ba005d55baf4e64f948ad206d856c5f570db770febf03da |
|
MD5 | 776ea13c7c45bceacc4e9d057b6a8909 |
|
BLAKE2b-256 | 08683dc7c7346808a68e2074ba427e148c8bfa3efe4b2ca034c19bb192f7f381 |