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(bucket_count) erase operation. An O(1) pop_back()
and an O(1) unordered_erase()
functions are available. If ordered erase is often used, another data structure is recommended.
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.
- Header-only library, just add the 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. - 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 thanKey
(e.g. if you have a map that usesstd::unique_ptr<foo>
as key, you can use afoo*
or astd::uintptr_t
as key parameter tofind
without constructing astd::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 definingTSL_NO_EXCEPTIONS
).std::terminate
is used in replacement of thethrow
instruction when exceptions are disabled. - API closely similar to
std::unordered_map
andstd::unordered_set
.
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
andstd::deque
(see API for details). If you usestd::vector
asValueTypeContainer
, you can usereserve()
to preallocate some space and avoid the invalidation of the iterators on insert. - Slow
erase()
operation, it has a complexity of O(bucket_count). A faster O(1) versionunordered_erase()
exists, but it breaks the insertion order (see API for details). An O(1)pop_back()
is also available. - The equality operators
operator==
andoperator!=
are order dependent. Twotsl::ordered_map
with the same values but inserted in a different order don't compare equal. - For iterators,
operator*()
andoperator->()
return a reference and a pointer toconst std::pair<Key, T>
instead ofstd::pair<const Key, T>
making the valueT
not modifiable. To modify the value you have to call thevalue()
method of the iterator to get a mutable reference. Example:
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).
These differences also apply between std::unordered_set
and tsl::ordered_set
.
If not mentioned otherwise, functions have the strong exception guarantee, see details. We below list cases in which this guarantee is not provided.
The guarantee is only provided 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).
The tsl::ordered_map::erase_if
and tsl::ordered_set::erase_if
functions only have the guarantee under the preconditions listed in their documentation.
To use ordered-map, just add the 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 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
The API can be found here.
#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 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;
}
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);
}
}
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);
}
}
The code is licensed under the MIT license, see the LICENSE file for details.