This repo contains a simple implementation of a bloom filter in C 17.
A bloom filter is a probabilistic data structure that is used to test whether an element is a member of a set. False positives are possible, but false negatives are not. Elements can be added to the set, but not removed.
#include <dynamic_bloom.hpp>
struct my_article final
{
std::string title;
std::string author;
std::string content;
};
struct article_hash final
{
inline std::size_t operator()(my_article const& article) const noexcept
{
return std::hash<std::string>{}(article.title);
}
};
int main()
{
// Assume that the average user can read 1000 articles on average.
tnt::dynamic_bloom<my_article, article_hash> read_articles(1'000);
// Our user reads an article.
my_article article1{"The C Programming Language", "Bjarne Stroustrup", "The C Programming Language is a computer programming book first published in October 1985."};
read_articles.insert(article1);
std::vector<my_article> suggestions;
for (auto const &article : <list-of-all-articles>)
{
if (!read_articles.matches(article))
{
// Add non-read articles to the suggestions list.
suggestions.push_back(article);
}
}
}
This is a header-only library. You can use it by simply copying the files in the include
directory to your project. Then include one of the header files in your source code as following.
// for fixed-size bloom filter
#include <static_bloom.hpp> // tnt::static_bloom
// for dynamically-sized bloom filter
#include <dynamic_bloom.hpp> // tnt::dynamic_bloom
The library is written in C 17, so you need a compiler that supports at least C 17. However, the tests are written in C 20, so you need a compiler that supports at least C 20 to run the tests. Furthermore, you need CMake 3.14 or newer to build the tests.
To run the tests, you need to have CMake 3.14 or newer installed on your system. Then, you can run the following commands.
mkdir build
cd build
cmake ..
cmake --build . --target run_tests
Code is licensed under the MIT License - see the LICENSE file for details.