ordered-map

C++ hash map and hash set which preserve the order of insertion

Description

The ordered-map library provides a hash map and a hash set which preserve the order of insertion in a way similar to Python's OrderedDict. When iterating over the map, the values will be returned in the same order as they were inserted.

The values are stored contiguously in an underlying structure, no holes in-between values even after an erase operation. By default a std::deque is used for this structure, but it's also possible to use a std::vector. This structure is directly accessible through the values_container() method and if the structure is a std::vector, a data() method is also provided to easily interact with C APIs.

To resolve collisions on hashes, the library uses robin hood probing with backward shift deletion.

The library provides a behaviour similar to a std::deque/std::vector with unique values but with an average search complexity of O(1). This comes at the price of a little higher memory footprint (8 bytes per entry if the load factor is 1, around 16 bytes per entry for a 0.5 load factor).

Two classes are provided: tsl::ordered_map and tsl::ordered_set.

Code Quality Rank: L4

Programming language: C++

License: MIT License

Tags: Containers     Data Structures     Ordered Map     Map     Set     Utilities    

Latest version: v1.0.0

README

C++ hash map and hash set which preserves the order of insertion

The ordered-map library provides a hash map and a hash set which preserve the order of insertion in a way similar to Python's OrderedDict. When iterating over the map, the values will be returned in the same order as they were inserted.

The values are stored contiguously in an underlying structure, no holes in-between values even after an erase operation. By default a std::deque is used for this structure, but it's also possible to use a std::vector. This structure is directly accessible through the values_container() method and if the structure is a std::vector, a data() method is also provided to easily interact with C APIs. This provides fast iteration but with the drawback of an O(n) erase operation. An O(1) pop_back() and an O(1) unordered_erase() functions are available.

To resolve collisions on hashes, the library uses linear robin hood probing with backward shift deletion.

The library provides a behaviour similar to a std::deque/std::vector with unique values but with an average time complexity of O(1) for lookups and an amortised time complexity of O(1) for insertions. This comes at the price of a little higher memory footprint (8 bytes per bucket by default).

Two classes are provided: tsl::ordered_map and tsl::ordered_set.

Note: The library uses a power of two for the size of its buckets array to take advantage of the fast modulo. For good performances, it requires the hash table to have a well-distributed hash function. If you encounter performance issues check your hash function.

Key features

• Header-only library, just add the [include](include/) directory to your include path and you are ready to go. If you use CMake, you can also use the tsl::ordered_map exported target from the [CMakeLists.txt](CMakeLists.txt).
• Values are stored in the same order as the insertion order. The library provides a direct access to the underlying structure which stores the values.
• O(1) average time complexity for lookups with performances similar to std::unordered_map but with faster insertions and reduced memory usage (see benchmark for details).
• Provide random access iterators and also reverse iterators.
• Support for heterogeneous lookups allowing the usage of find with a type different than Key (e.g. if you have a map that uses std::unique_ptr<foo> as key, you can use a foo* or a std::uintptr_t as key parameter to find without constructing a std::unique_ptr<foo>, see example).
• If the hash is known before a lookup, it is possible to pass it as parameter to speed-up the lookup (see precalculated_hash parameter in API).
• Support for efficient serialization and deserialization (see example and the serialize/deserialize methods in the API for details).
• The library can be used with exceptions disabled (through -fno-exceptions option on Clang and GCC, without an /EH option on MSVC or simply by defining TSL_NO_EXCEPTIONS). std::terminate is used in replacement of the throw instruction when exceptions are disabled.
• API closely similar to std::unordered_map and std::unordered_set.

Differences compared to std::unordered_map

tsl::ordered_map tries to have an interface similar to std::unordered_map, but some differences exist.

• The iterators are RandomAccessIterator.
• Iterator invalidation behaves in a way closer to std::vector and std::deque (see API for details). If you use std::vector as ValueTypeContainer, you can use reserve() to preallocate some space and avoid the invalidation of the iterators on insert.
• Slow erase() operation, it has a complexity of O(n). A faster O(1) version unordered_erase() exists, but it breaks the insertion order (see API for details). An O(1) pop_back() is also available.
• The equality operators operator== and operator!= are order dependent. Two tsl::ordered_map with the same values but inserted in a different order don't compare equal.
• For iterators, operator*() and operator->() return a reference and a pointer to const std::pair<Key, T> instead of std::pair<const Key, T> making the value T not modifiable. To modify the value you have to call the value() method of the iterator to get a mutable reference. Example: c++ tsl::ordered_map<int, int> map = {{1, 1}, {2, 1}, {3, 1}}; for(auto it = map.begin(); it != map.end(); ++it) { //it->second = 2; // Illegal it.value() = 2; // Ok }
• By default the map can only hold up to 232 - 1 values, that is 4 294 967 295 values. This can be raised through the IndexType class template parameter, check the API for details.
• No support for some bucket related methods (like bucket_size, bucket, ...).

Thread-safety guarantee is the same as std::unordered_map (i.e. possible to have multiple concurrent readers with no writer).

Concerning the strong exception guarantee, it holds only if ValueContainer::emplace_back has the strong exception guarantee (which is true for std::vector and std::deque as long as the type T is not a move-only type with a move constructor that may throw an exception, see details).

These differences also apply between std::unordered_set and tsl::ordered_set.

Installation

To use ordered-map, just add the [include](include/) directory to your include path. It is a header-only library.

If you use CMake, you can also use the tsl::ordered_map exported target from the [CMakeLists.txt](CMakeLists.txt) with target_link_libraries.

# Example where the ordered-map project is stored in a third-party directory
add_subdirectory(third-party/ordered-map)
target_link_libraries(your_target PRIVATE tsl::ordered_map)  

If the project has been installed through make install, you can also use find_package(tsl-ordered-map REQUIRED) instead of add_subdirectory.

The code should work with any C++11 standard-compliant compiler and has been tested with GCC 4.8.4, Clang 3.5.0 and Visual Studio 2015.

To run the tests you will need the Boost Test library and CMake.

git clone https://github.com/Tessil/ordered-map.git
cd ordered-map/tests
mkdir build
cd build
cmake ..
cmake --build .
./tsl_ordered_map_tests 

Usage

The API can be found here.

Example

#include <iostream>
#include <string>
#include <cstdlib>
#include <tsl/ordered_map.h>
#include <tsl/ordered_set.h>

int main() {
    tsl::ordered_map<char, int> map = {{'d', 1}, {'a', 2}, {'g', 3}};
    map.insert({'b', 4});
    map['h'] = 5;
    map['e'] = 6;

    map.erase('a');


    // {d, 1} {g, 3} {b, 4} {h, 5} {e, 6}
    for(const auto& key_value : map) {
        std::cout << "{" << key_value.first << ", " << key_value.second << "}" << std::endl;
    }


    map.unordered_erase('b');

    // Break order: {d, 1} {g, 3} {e, 6} {h, 5}
    for(const auto& key_value : map) {
        std::cout << "{" << key_value.first << ", " << key_value.second << "}" << std::endl;
    }


    for(auto it = map.begin(); it != map.end(); ++it) {
        //it->second += 2; // Not valid.
        it.value() += 2;
    }


    if(map.find('d') != map.end()) {
        std::cout << "Found 'd'." << std::endl;
    }

    const std::size_t precalculated_hash = std::hash<char>()('d');
    // If we already know the hash beforehand, we can pass it as argument to speed-up the lookup.
    if(map.find('d', precalculated_hash) != map.end()) {
        std::cout << "Found 'd' with hash " << precalculated_hash << "." << std::endl;
    }


    tsl::ordered_set<char, std::hash<char>, std::equal_to<char>,
                     std::allocator<char>, std::vector<char>> set;
    set.reserve(6);

    set = {'3', '4', '9', '2'};
    set.erase('2');
    set.insert('1');
    set.insert('\0');

    set.pop_back();
    set.insert({'0', '\0'});

    // Get raw buffer for C API: 34910
    std::cout << atoi(set.data()) << std::endl;
}

Heterogeneous lookup

Heterogeneous overloads allow the usage of other types than Key for lookup and erase operations as long as the used types are hashable and comparable to Key.

To activate the heterogeneous overloads in tsl::ordered_map/set, the qualified-id KeyEqual::is_transparent must be valid. It works the same way as for std::map::find. You can either use std::equal_to<> or define your own function object.

Both KeyEqual and Hash will need to be able to deal with the different types.

#include <functional>
#include <iostream>
#include <string>
#include <tsl/ordered_map.h>



struct employee {
    employee(int id, std::string name) : m_id(id), m_name(std::move(name)) {
    }

    // Either we include the comparators in the class and we use `std::equal_to<>`...
    friend bool operator==(const employee& empl, int empl_id) {
        return empl.m_id == empl_id;
    }

    friend bool operator==(int empl_id, const employee& empl) {
        return empl_id == empl.m_id;
    }

    friend bool operator==(const employee& empl1, const employee& empl2) {
        return empl1.m_id == empl2.m_id;
    }


    int m_id;
    std::string m_name;
};

// ... or we implement a separate class to compare employees.
struct equal_employee {
    using is_transparent = void;

    bool operator()(const employee& empl, int empl_id) const {
        return empl.m_id == empl_id;
    }

    bool operator()(int empl_id, const employee& empl) const {
        return empl_id == empl.m_id;
    }

    bool operator()(const employee& empl1, const employee& empl2) const {
        return empl1.m_id == empl2.m_id;
    }
};

struct hash_employee {
    std::size_t operator()(const employee& empl) const {
        return std::hash<int>()(empl.m_id);
    }

    std::size_t operator()(int id) const {
        return std::hash<int>()(id);
    }
};


int main() {
    // Use std::equal_to<> which will automatically deduce and forward the parameters
    tsl::ordered_map<employee, int, hash_employee, std::equal_to<>> map; 
    map.insert({employee(1, "John Doe"), 2001});
    map.insert({employee(2, "Jane Doe"), 2002});
    map.insert({employee(3, "John Smith"), 2003});

    // John Smith 2003
    auto it = map.find(3);
    if(it != map.end()) {
        std::cout << it->first.m_name << " " << it->second << std::endl;
    }

    map.erase(1);



    // Use a custom KeyEqual which has an is_transparent member type
    tsl::ordered_map<employee, int, hash_employee, equal_employee> map2;
    map2.insert({employee(4, "Johnny Doe"), 2004});

    // 2004
    std::cout << map2.at(4) << std::endl;
} 

Serialization

The library provides an efficient way to serialize and deserialize a map or a set so that it can be saved to a file or send through the network. To do so, it requires the user to provide a function object for both serialization and deserialization.

struct serializer {
    // Must support the following types for U: std::uint64_t, float 
    // and std::pair<Key, T> if a map is used or Key for a set.
    template<typename U>
    void operator()(const U& value);
};

struct deserializer {
    // Must support the following types for U: std::uint64_t, float 
    // and std::pair<Key, T> if a map is used or Key for a set.
    template<typename U>
    U operator()();
};

Note that the implementation leaves binary compatibility (endianness, float binary representation, size of int, ...) of the types it serializes/deserializes in the hands of the provided function objects if compatibility is required.

More details regarding the serialize and deserialize methods can be found in the API.

#include <cassert>
#include <cstdint>
#include <fstream>
#include <type_traits>
#include <tsl/ordered_map.h>


class serializer {
public:
    explicit serializer(const char* file_name) {
        m_ostream.exceptions(m_ostream.badbit | m_ostream.failbit);
        m_ostream.open(file_name, std::ios::binary);
    }

    template<class T,
             typename std::enable_if<std::is_arithmetic<T>::value>::type* = nullptr>
    void operator()(const T& value) {
        m_ostream.write(reinterpret_cast<const char*>(&value), sizeof(T));
    }

    void operator()(const std::pair<std::int64_t, std::int64_t>& value) {
        (*this)(value.first);
        (*this)(value.second);
    }

private:
    std::ofstream m_ostream;
};

class deserializer {
public:
    explicit deserializer(const char* file_name) {
        m_istream.exceptions(m_istream.badbit | m_istream.failbit | m_istream.eofbit);
        m_istream.open(file_name, std::ios::binary);
    }

    template<class T>
    T operator()() {
        T value;
        deserialize(value);

        return value;
    }

private:
    template<class T,
             typename std::enable_if<std::is_arithmetic<T>::value>::type* = nullptr>
    void deserialize(T& value) {
        m_istream.read(reinterpret_cast<char*>(&value), sizeof(T));
    }

    void deserialize(std::pair<std::int64_t, std::int64_t>& value) {
        deserialize(value.first);
        deserialize(value.second);
    }

private:
    std::ifstream m_istream;
};


int main() {
    const tsl::ordered_map<std::int64_t, std::int64_t> map = {{1, -1}, {2, -2}, {3, -3}, {4, -4}};


    const char* file_name = "ordered_map.data";
    {
        serializer serial(file_name);
        map.serialize(serial);
    }

    {
        deserializer dserial(file_name);
        auto map_deserialized = tsl::ordered_map<std::int64_t, std::int64_t>::deserialize(dserial);

        assert(map == map_deserialized);
    }

    {
        deserializer dserial(file_name);

        /**
         * If the serialized and deserialized map are hash compatibles (see conditions in API), 
         * setting the argument to true speed-up the deserialization process as we don't have 
         * to recalculate the hash of each key. We also know how much space each bucket needs.
         */
        const bool hash_compatible = true;
        auto map_deserialized = 
            tsl::ordered_map<std::int64_t, std::int64_t>::deserialize(dserial, hash_compatible);

        assert(map == map_deserialized);
    }
} 

Serialization with Boost Serialization and compression with zlib

It's possible to use a serialization library to avoid the boilerplate.

The following example uses Boost Serialization with the Boost zlib compression stream to reduce the size of the resulting serialized file. The example requires C++20 due to the usage of the template parameter list syntax in lambdas, but it can be adapted to less recent versions.

#include <boost/archive/binary_iarchive.hpp>
#include <boost/archive/binary_oarchive.hpp>
#include <boost/iostreams/filter/zlib.hpp>
#include <boost/iostreams/filtering_stream.hpp>
#include <boost/serialization/split_free.hpp>
#include <boost/serialization/utility.hpp>
#include <cassert>
#include <cstdint>
#include <fstream>
#include <tsl/ordered_map.h>


namespace boost { namespace serialization {
    template<class Archive, class Key, class T>
    void serialize(Archive & ar, tsl::ordered_map<Key, T>& map, const unsigned int version) {
        split_free(ar, map, version); 
    }

    template<class Archive, class Key, class T>
    void save(Archive & ar, const tsl::ordered_map<Key, T>& map, const unsigned int /*version*/) {
        auto serializer = [&ar](const auto& v) { ar & v; };
        map.serialize(serializer);
    }

    template<class Archive, class Key, class T>
    void load(Archive & ar, tsl::ordered_map<Key, T>& map, const unsigned int /*version*/) {
        auto deserializer = [&ar]<typename U>() { U u; ar & u; return u; };
        map = tsl::ordered_map<Key, T>::deserialize(deserializer);
    }
}}


int main() {
    tsl::ordered_map<std::int64_t, std::int64_t> map = {{1, -1}, {2, -2}, {3, -3}, {4, -4}};


    const char* file_name = "ordered_map.data";
    {
        std::ofstream ofs;
        ofs.exceptions(ofs.badbit | ofs.failbit);
        ofs.open(file_name, std::ios::binary);

        boost::iostreams::filtering_ostream fo;
        fo.push(boost::iostreams::zlib_compressor());
        fo.push(ofs);

        boost::archive::binary_oarchive oa(fo);

        oa << map;
    }

    {
        std::ifstream ifs;
        ifs.exceptions(ifs.badbit | ifs.failbit | ifs.eofbit);
        ifs.open(file_name, std::ios::binary);

        boost::iostreams::filtering_istream fi;
        fi.push(boost::iostreams::zlib_decompressor());
        fi.push(ifs);

        boost::archive::binary_iarchive ia(fi);

        tsl::ordered_map<std::int64_t, std::int64_t> map_deserialized;   
        ia >> map_deserialized;

        assert(map == map_deserialized);
    }
}

License

The code is licensed under the MIT license, see the [LICENSE file](LICENSE) for details.