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# PGM-index | ||
<img src="https://gvinciguerra.github.io/PGM-index/images/logo.svg" alt="The PGM-index" style="width: 565px"> | ||
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The Piecewise Geometric Model index (PGM-index) is a data structure that enables fast point and range searches in arrays of billions of items using orders of magnitude less space than traditional indexes. | ||
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[Website](https://gvinciguerra.github.io/PGM-index) | ||
| [Documentation](https://gvinciguerra.github.io/PGM-index/docs) | ||
| [Paper](https://arxiv.org/abs/1910.06169) | ||
| [A³ Lab](http://acube.di.unipi.it) | ||
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[![Travis (.org)](https://img.shields.io/travis/gvinciguerra/PGM-index)](https://travis-ci.org/gvinciguerra/PGM-index) | ||
[![License](https://img.shields.io/github/license/gvinciguerra/PGM-index)](https://github.com/gvinciguerra/PGM-index/blob/master/LICENSE) | ||
[![GitHub stars](https://img.shields.io/github/stars/gvinciguerra/PGM-index)](https://github.com/gvinciguerra/PGM-index/stargazers) | ||
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## Building the code | ||
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To download and build the library use the following commands: | ||
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```bash | ||
git clone https://github.com/gvinciguerra/PGM-index.git | ||
cd PGM-index | ||
git submodule update --init --recursive | ||
cmake . -DCMAKE_BUILD_TYPE=Release | ||
make -j8 | ||
``` | ||
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Now you can run the unit tests via: | ||
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``` | ||
./test/tests | ||
``` | ||
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## Minimal example | ||
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```cpp | ||
#include <vector> | ||
#include <cstdlib> | ||
#include <iostream> | ||
#include <algorithm> | ||
#include "pgm_index.hpp" | ||
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int main(int argc, char **argv) { | ||
// Generate some random data | ||
std::vector<int> dataset(1000000); | ||
std::generate(dataset.begin(), dataset.end(), std::rand); | ||
dataset.push_back(42); | ||
std::sort(dataset.begin(), dataset.end()); | ||
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// Construct the PGM-index | ||
const int error = 128; | ||
PGMIndex<int, error> index(dataset); | ||
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// Query the PGM-index | ||
auto q = 42; | ||
auto approx_range = index.find_approximate_position(q); | ||
auto lo = dataset.cbegin() + approx_range.lo; | ||
auto hi = dataset.cbegin() + approx_range.hi; | ||
std::cout << *std::lower_bound(lo, hi, q); | ||
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return 0; | ||
} | ||
``` | ||
## License | ||
This project is licensed under the terms of the GNU General Public License v3.0. | ||
If you use the library please put a link to the [website](https://gvinciguerra.github.io/PGM-index) and cite the following paper: | ||
```tex | ||
@misc{FerraginaVinciguerra:2019, | ||
Archiveprefix = {arXiv}, | ||
Author = {Paolo Ferragina and Giorgio Vinciguerra}, | ||
Day = {14}, | ||
Eprint = {1910.06169}, | ||
Month = {10}, | ||
Primaryclass = {cs.DS}, | ||
Title = {The PGM-index: a multicriteria, compressed and learned approach to data indexing}, | ||
Url = {https://arxiv.org/abs/1910.06169}, | ||
Year = {2019}} | ||
``` |