streaming-percentiles
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About the Library
This is a cross-platform library with implementations of various
percentile algorithms on streams of data. These algorithms allow
you to calculate approximate percentiles (e.g. 50th percentile,
95th percentile) in a single pass over a data set.
They are particularly useful for calculating percentiles for
immense data sets, for extremely high-throughput systems, or
for near-real time use cases.
The library supports the following languages:
The library implements the following streaming percentile algorithms:
For more background on streaming
percentiles, see Calculating Percentiles on Streaming
Data.
Obtaining the Library
The current version of the library is 3.1.0, and it was released
March 28, 2019.
C++
You can download the latest release of the library from the
streaming-percentiles latest release
page.
JavaScript
If you use NPM, npm install streaming-percentiles
. Otherwise, download
the latest release of the library from the streaming-percentiles latest
release
page
page.
For convenience, you can also use the latest release JS directly
from sengelha.github.io
:
Source Code
You can download the latest release's source code from the
streaming-percentiles latest release
page.
See CONTRIBUTING.md for instructions on how to build the release from
source.
Historical Releases
Historical releases may be downloaded from the streaming-percentiles release page.
Using the Library
C++
Here's an example on how to use the Greenwald-Khanna streaming
percentile algorithm from C++:
#include <stmpct/gk.hpp>
double epsilon = 0.1;
stmpct::gk<double> g(epsilon);
for (int i = 0; i < 1000; ++i)
g.insert(rand());
double p50 = g.quantile(0.5);
double p95 = g.quantile(0.95);
JavaScript
Node.JS
Here's an example of how to use the library from Node.JS:
var sp = require('streaming-percentiles');
var epsilon = 0.1;
var g = new sp.GK(epsilon);
for (var i = 0; i < 1000; ++i)
g.insert(Math.random());
var p50 = g.quantile(0.5);
var p95 = g.quantile(0.95);
Browser
Here's an example of how to use the library from a browser. Note that the
default module name is streamingPercentiles
:
<script src="//sengelha.github.io/streaming-percentiles/streamingPercentiles.v1.min.js"></script>
<script>
var epsilon = 0.1;
var g = new streamingPercentiles.GK(epsilon);
for (var i = 0; i < 1000; ++i)
g.insert(Math.random());
var p50 = g.quantile(0.5);
</script>
API Reference
See doc/api_reference/ for detailed API reference documentation.
License
This project is licensed under the MIT License. See
LICENSE for more information.
Contributing
If you are interested in contributing to the library, please see
CONTRIBUTING.md.