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streaming-percentiles
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streaming-percentiles - npm Package Compare versions
Comparing version 2.3.0 to 3.0.0
| { | ||
| "name": "streaming-percentiles", | ||
| "version": "2.3.0", | ||
| "version": "3.0.0", | ||
| "description": "Implementations of various streaming percentile algorithms", | ||
@@ -19,6 +19,6 @@ "keywords": [ | ||
| "type": "git", | ||
| "url": "git+https://github.com/sengelha/streaming-percentiles-cpp.git" | ||
| "url": "git+https://github.com/sengelha/streaming-percentiles.git" | ||
| }, | ||
| "bugs": { | ||
| "url": "https://github.com/sengelha/streaming-percentiles-cpp/issues" | ||
| "url": "https://github.com/sengelha/streaming-percentiles/issues" | ||
| }, | ||
@@ -25,0 +25,0 @@ "scripts": { |
215
README.md
| # streaming-percentiles | ||
| ## Build Status: | ||
| Develop branch: [](https://travis-ci.org/sengelha/streaming-percentiles-cpp) | ||
| Master branch: [](https://travis-ci.org/sengelha/streaming-percentiles-cpp) | ||
| ## Build Status | ||
| | Develop Branch | Master Branch | | ||
| | -------------- | ------------- | | ||
| | [](https://travis-ci.org/sengelha/streaming-percentiles-cpp) | [](https://travis-ci.org/sengelha/streaming-percentiles-cpp) | | ||
| ## About the Library | ||
| This is a cross-pltaform library with implementations of various | ||
| percentile algorithms on streams of data. For more on streaming | ||
| percentiles, see [Calculating Percentiles on Streaming | ||
| Data](//stevenengelhardt.com/post-series/calculating-percentiles-on-streaming-data-2018/). | ||
| 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: | ||
| - C++ | ||
| - JavaScript | ||
| The library implements the following streaming percentile algorithms: | ||
| - [Greenwald-Khanna](doc/methodology/GK01.pdf) | ||
| - [Cormode-Korn-Muthukrishnan-Srivastava](doc/methodology/CKMS05.pdf) for high-biased, low-biased, uniform, and targeted quantiles | ||
| For more background on streaming | ||
| percentiles, see [Calculating Percentiles on Streaming | ||
| Data](//www.stevenengelhardt.com/postseries/calculating-percentiles-on-streaming-data/). | ||
| ## Obtaining the Library | ||
@@ -20,3 +37,3 @@ | ||
| You can download pre-built binaries of the library from the | ||
| You can download the latest release of the library from the | ||
| [streaming-percentiles latest release | ||
@@ -28,3 +45,3 @@ page](//github.com/sengelha/streaming-percentiles-cpp/releases/latest). | ||
| If you use NPM, `npm install streaming-percentiles`. Otherwise, download | ||
| pre-built binaries of the library from the [streaming-percentiles latest | ||
| the latest release of the library from the [streaming-percentiles latest | ||
| release | ||
@@ -46,6 +63,6 @@ page](//github.com/sengelha/streaming-percentiles-cpp/releases/latest) | ||
| See `CONTRIBUTING.md` for instructions on how to build the release from | ||
| See [CONTRIBUTING.md](CONTRIBUTING.md) for instructions on how to build the release from | ||
| source. | ||
| ## Usage Example | ||
| ## Using the Library | ||
@@ -60,6 +77,4 @@ ### C++ | ||
| using namespace stmpct; | ||
| double epsilon = 0.1; | ||
| gk g(epsilon); | ||
| stmpct::gk<double> g(epsilon); | ||
| for (int i = 0; i < 1000; ++i) | ||
@@ -75,3 +90,3 @@ g.insert(rand()); | ||
| Here's how to use the library from Node.JS: | ||
| Here's an example of how to use the library from Node.JS: | ||
| ```javascript | ||
@@ -90,4 +105,4 @@ var sp = require('streaming-percentiles'); | ||
| Here's how to use the library from a browser. Note that the | ||
| default module name is streamingPercentiles: | ||
| Here's an example of how to use the library from a browser. Note that the | ||
| default module name is `streamingPercentiles`: | ||
| ```html | ||
@@ -97,3 +112,3 @@ <script src="//sengelha.github.io/streaming-percentiles/streamingPercentiles.v1.min.js"></script> | ||
| var epsilon = 0.1; | ||
| var gk = new streamingPercentiles.GK(epsilon); | ||
| var g = new streamingPercentiles.GK(epsilon); | ||
| for (var i = 0; i < 1000; ++i) | ||
@@ -107,168 +122,4 @@ g.insert(Math.random()); | ||
| ### Usage Notes | ||
| See [doc/api_reference/](doc/api_reference/index.md) for detailed API reference documentation. | ||
| - Every algorithm inherits from the interface `stmpct_alg` | ||
| which defines two methods: `void insert(double value)` | ||
| and `double quantile(double phi) const`. | ||
| #### C++ | ||
| - All include files are in the directory `stmpct/` | ||
| - All classes are in the `stmpct` namespace. | ||
| #### JavaScript | ||
| - For backwards-compatibility reasons, all class names are | ||
| capitalized. | ||
| ### interface stmpct_alg | ||
| Defines the interface that all streaming percentile algorithms | ||
| must implement. | ||
| ### void *stmpct_alg*.insert(double *value*) | ||
| Logs the observation of a value. | ||
| #### C++ Example | ||
| ```cpp | ||
| stmpct_alg* alg = ...; | ||
| alg->insert(rand()); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var alg = ...; | ||
| alg.insert(Math.random()); | ||
| ``` | ||
| ### double *stmpct_alg*.quantile(double *phi*) const | ||
| Compute the approximate quantile at *phi*. For example, the 95th | ||
| percentile corresponds to *phi* = 0.95. | ||
| #### C++ Example | ||
| ```cpp | ||
| stmpct_alg* alg = ...; | ||
| var p50 = alg->quantile(0.5); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var alg = ...; | ||
| var p50 = alg.quantile(0.5); | ||
| ``` | ||
| ### class gk(double *epsilon*) | ||
| Implements the Greenwald-Khanna streaming percentile algorithm | ||
| with allowable error *epsilon*. | ||
| #### C++ Example | ||
| ```cpp | ||
| #include <stmpct/gk.hpp> | ||
| stmpct::gk g(0.1); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var sp = require('streaming-percentiles'); | ||
| var gk = new sp.GK(0.1); | ||
| ``` | ||
| ### class ckms_uq(double *epsilon*) | ||
| Implements the Cormode-Korn-Muthukrishnan-Srivastava algorithm | ||
| for uniform percentiles with allowable error *epsilon*. | ||
| #### C++ Example | ||
| ```cpp | ||
| #include <stmpct/ckms_uq.hpp> | ||
| stmpct::ckms_uq c(0.1); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var sp = require('streaming-percentiles'); | ||
| var gk = new sp.CKMS_UQ(0.1); | ||
| ``` | ||
| ### class ckms_lbq(double *epsilon*) | ||
| Implements the Cormode-Korn-Muthukrishnan-Srivastava algorithm | ||
| for low-biased quantiles with allowable error *epsilon*. | ||
| #### C++ Example | ||
| ```cpp | ||
| #include <stmpct/ckms_lbq.hpp> | ||
| stmpct::ckms_lbq c(0.1); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var sp = require('streaming-percentiles'); | ||
| var gk = new sp.CKMS_LBQ(0.1); | ||
| ``` | ||
| ### class ckms_hbq(double *epsilon*) | ||
| Implements the Cormode-Korn-Muthukrishnan-Srivastava algorithm | ||
| for high-biased quantiles with allowable error *epsilon*. | ||
| #### C++ Example | ||
| ```cpp | ||
| #include <stmpct/ckms_hbq.hpp> | ||
| stmpct::ckms_hbq c(0.1); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var sp = require('streaming-percentiles'); | ||
| var gk = new sp.CKMS_HBQ(0.1); | ||
| ``` | ||
| ### class ckms_tq(vector<targeted_quantile> *tqs*) | ||
| Implements the Cormode-Korn-Muthukrishnan-Srivastava algorithm | ||
| for the provided set of targeted quantiles *tqs*. Each | ||
| targeted quantile is the combination of a quantile *phi* and | ||
| allowable error *epsilon*. | ||
| #### C++ Example | ||
| ```cpp | ||
| #include <stmpct/ckms_tq.hpp> | ||
| std::vector<targeted_quantile> tqs; | ||
| tqs.emplace_back(0.125, 0.02); | ||
| tqs.emplace_back(0.375, 0.02); | ||
| tqs.emplace_back(0.75, 0.04); | ||
| tqs.emplace_back(0.875, 0.01); | ||
| ckms_tq c(tqs); | ||
| ``` | ||
| #### JavaScript Example | ||
| ```javascript | ||
| var sp = require('streaming-percentiles'); | ||
| var tqs = [ | ||
| { phi: 0.125, epsilon: 0.02 }, | ||
| { phi: 0.375, epsilon: 0.02 }, | ||
| { phi: 0.75, epsilon: 0.04 }, | ||
| { phi: 0.875, epsilon: 0.01 } | ||
| ]; | ||
| var c = new sp.CKMS_TQ(tqs); | ||
| ``` | ||
| ## License | ||
@@ -275,0 +126,0 @@ |
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Worsened metrics
- Total package byte prevSize
- decreased by-2.04%
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- Lines of code
- decreased by-0.34%
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- Number of lines in readme file
- decreased by-54.18%
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