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-0.0.0.tar.gz
(11.6 kB
view hashes)
Built Distribution
sketchlib-0.0.0-py3-none-any.whl
(13.8 kB
view hashes)
Close
Hashes for sketchlib-0.0.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 30e48e1932e8a7fb78abaa3ceb66019c3ea65be4485d88f2afe0f3dbb8d5d62a |
|
MD5 | f04380cb3ba1c76b7a2de067f20aa62b |
|
BLAKE2b-256 | 0bd5da04060c25598916843c43b661dbdeeb7621ac810e105ddc89d0262ee316 |