This library implements a general-purpose header-only STL-like B-Tree in C++, including supports for using it for memory-mapped disk files and fixed-size allocators.
A B-Tree is a self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. Unlike other self-balancing binary search trees, the B-tree is well suited for storage systems that read and write relatively large blocks of data, such as databases and file systems
Just like ordered associative containers in the C++ standard library, key-value pairs can be supported and duplicates can be allowed.
There are four specialized B-Tree classes: frozenca::BTreeSet, frozenca::BTreeMultiSet, frozenca::BTreeMap and frozenca::BTreeMultiMap, which corresponds to std::set, std::multiset, std::map and std::multimap respectively.
This library is header-only, so no additional setup process is required beyond including the headers.
Or
For cmake projects:
Install one of package BTree..rpm or BTree..deb or include this project into yours and then
find_package(BTree)
#...
target_link_libraries(${your_target} PRIVATE BTree::BTree)This library aggressively uses C++20 features, and verified to work in gcc 11.2 and MSVC 19.32.
POSIX and Windows operating systems are supported in order to use the memory-mapped disk file interface.
There are currently no plans to support C++17 and earlier.
Usage is very similar to the C++ standard library ordered associative containers (i.e. std::set and its friends)
#include "fc/btree.h"
#include <iostream>
#include <string>
int main() {
namespace fc = frozenca;
fc::BTreeSet<int> btree;
btree.insert(3);
btree.insert(4);
btree.insert(2);
btree.insert(1);
btree.insert(5);
// 1 2 3 4 5
for (auto num : btree) {
std::cout << num << ' ';
}
std::cout << '\n';
fc::BTreeMap<std::string, int> strtree;
strtree["asd"] = 3;
strtree["a"] = 6;
strtree["bbb"] = 9;
strtree["asdf"] = 8;
for (const auto &[k, v] : strtree) {
std::cout << k << ' ' << v << '\n';
}
strtree["asdf"] = 333;
// 333
std::cout << strtree["asdf"] << '\n';
strtree.emplace("asdfgh", 200);
for (const auto &[k, v] : strtree) {
std::cout << k << ' ' << v << '\n';
}
}You can refer more example usages in test/unittest.cpp.
Users can specify a fanout parameter for B-tree: the default is 64.
// btree with fanout 128
fc::BTreeSet<int, 128> btree;The smallest possible value for fanout is 2, where a B-Tree boils down to an 2-3-4 tree
Other than regular operations supported by std::set and its friends (lower_bound(), upper_bound(), equal_range() and etc), the following operations are supported.
tree.count(const key_type& key) : Returns the number of elements in the tree for their key is equivalent to key. Time complexity: O(log n)
tree.kth(std::ptrdiff_t k) : Returns the k-th element in the tree as 0-based index. Time complexity: O(log n)
tree.order(const_iterator_type iter) : Returns the rank of the element in the iterator in the tree as 0-based index. Time complexity: O(log n)
tree.enumerate(const key_type& a, const key_type& b) : Range query. Returns the range of values for their key in [a, b]. Time complexity: O(log n)
tree.insert_range(ForwardIter first, ForwardIter last) : Inserts the elements in [first, last). The range version also exists. Time complexity: O(k log k + log n) if all of elements in the range can be fit between two elements in the tree, otherwise O(k log n)
tree.erase_range(const key_type& a, const key_type&) : Erases the elements for their key in [a, b]. Time complexity: O(log n) + O(k) (NOT O(k log n))
frozenca::join(Tree&& tree1, Tree&& tree2) : Joins two trees to a single tree. The largest key in tree1 should be less than or equal to the smallest key in tree2. Time complexity: O(log n)
frozenca::join(Tree&& tree1, value_type val, Tree&& tree2) : Joins two trees to a single tree. The largest key in tree1 should be less than or equal to the key of val and the smallest key in tree2 should be greater than or equal to the key of val. Time complexity: O(1 + diff_height)
frozenca::split(Tree&& tree, key_type key) : Splits a tree to two trees, so that the first tree contains keys less than key, and the second tree contains keys greater than key. Time complexity: O(log n)
frozenca::split(Tree&& tree, key_type key1, key_type key2) : Splits a tree to two trees, so that the first tree contains keys less than key1, and the second tree contains keys greater than key2. key2 must be greater than or equal to key1. Time complexity: O(log n) + O(k)
STL compatible iterators are fully supported. (both const and non-const) However, unlike std::set and its friends, all insert and erase operations can invalidate iterators. This is because std::set and its friends are node-based containers where a single node can only have a single key, but a node in B-Trees can have multiple keys.
Currently, thread safety is not guaranteed. Lock-free support is the first TODO, but contributions are welcome if you're interested.
The core operation for B-Tree is a search in the sorted key array of each node. For small arrays with primitive key types that have relatively cheap comparisons, linear search is often better than binary search. This threshold may vary by compiler by a big margin.
If you use Clang, I recommend that you set this variable to 1. For gcc users, it seems better not to change the variable (may be changed by future gcc optimizations) https://github.com/frozenca/BTree/blob/7083e8034b5905552cc6a3b8277452c56c05d587/fc_btree.h#L22
When keys are signed integers or floating point types, if your machine supports AVX-512, you can activate SIMD intrinsics to speed up B-Tree operations, by setting this variable to 1: https://github.com/frozenca/BTree/blob/3498a53e75e916015561008cf91fecc3f7df69d1/fc_btree.h#L4 (Inspired from: Static B-Trees)
You can use a specialized variant that utilizes memory-mapped disk files and an associated fixed-size allocator. You have to include fc_disk_btree.h, fc_disk_fixed_alloc.h and fc_mmfile.h to use it.
For this variant, supported types have stricter type constraints: it should satisfy std::trivially_copyable_v, and its alignment should at least be the alignment of the pointer type in the machine (for both key type and value type for key-value pairs).
The following code initializes a frozenca::DiskBTreeSet, which generates a memory-mapped disk file database.bin and uses it, with an initial byte size of 32 megabytes. If the third argument is true, it will destroy the existing file and create a new one (default is false). You can't extend the pool size of the memory-mapped disk file once you initialized (doing so invalidates all pointers in the associated allocator).
fc::DiskBTreeSet<std::int64_t, 128> btree("database.bin", 1UL << 25UL, true);Serialization/deserialization of B-Trees via byte streams using operator<< and operator>> is also supported when key types (and value types, if present) meet the above requirements for disk B-Tree. You can refer how to do serialization/deserialization in test/rwtest.cpp.
Using a performance test code similar with test/perftest.cpp, that inserts/retrieves/erases 1 million std::int64_t in random order, I see the following results in my machine (gcc 11.2, -O3, 200 times repeated per each target), compared to std::set and Google's B-Tree implementation(https://code.google.com/archive/p/cpp-btree/):
Balanced tree test
Warming up complete...
frozenca::BTreeSet test (fanout 64 - default, SIMD)
Time to insert 1000000 elements: Average : 175.547ms, Stdev : 8.65575ms, 95% : 189.553ms,
Time to lookup 1000000 elements: Average : 197.75ms, Stdev : 7.75456ms, 95% : 208.783ms,
Time to erase 1000000 elements: Average : 211.274ms, Stdev : 10.3499ms, 95% : 225.221ms,
frozenca::BTreeSet test (fanout 96, SIMD)
Time to insert 1000000 elements: Average : 176.432ms, Stdev : 9.12931ms, 95% : 192.688ms,
Time to lookup 1000000 elements: Average : 194.997ms, Stdev : 11.3563ms, 95% : 205.048ms,
Time to erase 1000000 elements: Average : 212.86ms, Stdev : 11.3598ms, 95% : 228.145ms,
frozenca::DiskBTreeSet test (fanout 128, SIMD)
Time to insert 1000000 elements: Average : 187.797ms, Stdev : 8.69872ms, 95% : 202.318ms,
Time to lookup 1000000 elements: Average : 200.799ms, Stdev : 7.10905ms, 95% : 211.436ms,
Time to erase 1000000 elements: Average : 216.105ms, Stdev : 6.83771ms, 95% : 228.9ms,
frozenca::BTreeSet test (fanout 128, SIMD)
Time to insert 1000000 elements: Average : 189.536ms, Stdev : 15.3073ms, 95% : 221.393ms,
Time to lookup 1000000 elements: Average : 204.741ms, Stdev : 17.8811ms, 95% : 232.494ms,
Time to erase 1000000 elements: Average : 219.17ms, Stdev : 20.6449ms, 95% : 244.232ms,
frozenca::BTreeSet test (fanout 64, uint64, don't use SIMD)
Time to insert 1000000 elements: Average : 204.187ms, Stdev : 57.3915ms, 95% : 222.939ms,
Time to lookup 1000000 elements: Average : 221.049ms, Stdev : 25.3429ms, 95% : 245.708ms,
Time to erase 1000000 elements: Average : 249.832ms, Stdev : 52.1106ms, 95% : 288.095ms,
std::set test
Time to insert 1000000 elements: Average : 907.104ms, Stdev : 43.7566ms, 95% : 966.12ms,
Time to lookup 1000000 elements: Average : 961.859ms, Stdev : 30.1132ms, 95% : 1019.59ms,
Time to erase 1000000 elements: Average : 990.027ms, Stdev : 37.1807ms, 95% : 1049.58ms,
Google btree::btree_set test (fanout 64)
Time to insert 1000000 elements: Average : 425.071ms, Stdev : 13.117ms, 95% : 434.819ms,
Time to lookup 1000000 elements: Average : 377.009ms, Stdev : 15.2407ms, 95% : 385.736ms,
Time to erase 1000000 elements: Average : 421.514ms, Stdev : 17.3882ms, 95% : 432.955ms,
Google btree::btree_set test (fanout 256 - default value)
Time to insert 1000000 elements: Average : 251.597ms, Stdev : 14.3492ms, 95% : 289.579ms,
Time to lookup 1000000 elements: Average : 235.204ms, Stdev : 11.8999ms, 95% : 255.495ms,
Time to erase 1000000 elements: Average : 250.782ms, Stdev : 12.1752ms, 95% : 270.575ms,
For 1 million std::strings with length 1~50, I see the following results in my machine:
frozenca::BTreeSet test (fanout 64 - default, std::string)
Time to insert 1000000 elements: Average : 1519.62ms, Stdev : 81.3793ms, 95% : 1685.13ms,
Time to lookup 1000000 elements: Average : 1188.33ms, Stdev : 83.8154ms, 95% : 1392.47ms,
Time to erase 1000000 elements: Average : 1570.44ms, Stdev : 93.771ms, 95% : 1747.73ms,
frozenca::BTreeSet test (fanout 128, std::string)
Time to insert 1000000 elements: Average : 1774.12ms, Stdev : 41.601ms, 95% : 1812.62ms,
Time to lookup 1000000 elements: Average : 1089.02ms, Stdev : 22.8206ms, 95% : 1127.83ms,
Time to erase 1000000 elements: Average : 1670.09ms, Stdev : 24.2791ms, 95% : 1711.33ms,
std::set test (std::string)
Time to insert 1000000 elements: Average : 1662.92ms, Stdev : 178.644ms, 95% : 1861.37ms,
Time to lookup 1000000 elements: Average : 1666.16ms, Stdev : 127.095ms, 95% : 1845.49ms,
Time to erase 1000000 elements: Average : 1639.79ms, Stdev : 82.7256ms, 95% : 1770.9ms,
If you want to contribute and test the code, pay attention and use macro _CONTROL_IN_TEST, which will do full sanity checks on the entire tree:
https://github.com/frozenca/BTree/blob/adf3c3309f45a65010d767df674c232c12f5c00a/fc_btree.h#L350 https://github.com/frozenca/BTree/blob/adf3c3309f45a65010d767df674c232c12f5c00a/fc_btree.h#L531-#L532
and by running test/unittest.cpp you can verify basic operations.
This library is licensed under either of Apache License Version 2.0 with LLVM Exceptions (LICENSE-Apache2-LLVM or https://llvm.org/foundation/relicensing/LICENSE.txt) or Boost Software License Version 1.0 (LICENSE-Boost or https://www.boost.org/LICENSE_1_0.txt).