A collection of multi-dimensional data structure and indexing algorithm.
This library implements the following data structures:
- segment_tree
- flat_segment_tree
- point_quad_tree
- multi_type_vector
- multi_type_matrix
- sorted_string_map
- trie_map
- packed_trie_map
- rtree
Segment tree is a balanced-binary-tree based data structure efficient
for detecting all intervals (or segments) that contain a given point.
The segments may overlap with each other. The end points of stored
segments are not inclusive, that is, when an interval spans from 2 to
6, an arbitrary point x within that interval can take a value of 2 <=
x < 6.
Flat segment tree is a variant of segment tree that is designed to store a collection of non-overlapping segments. This structure is efficient when you need to store values associated with 1 dimensional segments that never overlap with each other. Like segment tree, stored segments' end points are non-inclusive.
Point quad tree stores 2-dimensional points and provides an efficient way to query all points within specified rectangular region.
Multi-type vector allows storage of unspecified number of types in a single logical array such that contiguous elements of identical type are stored in contiguous segment in memory space.
Multi-type matrix is a matrix structure that allows storage of four different element types: numeric, string, boolean and empty. It uses multi-type vector as its underlying storage.
Sorted string map is a simple data structure that takes a pre-sorted list of key-value pairs that are known at compile time, and allows efficient lookup. It does not allocate memory to duplicate its content, as it directly uses the pre-sorted list provided by the caller.
Trie map is an associative container that stores multiple key-value pairs where keys are stored in a trie structure to optimize for prefix searches.
Packed trie map is nearly identical to the trie map counterpart except that this one is immutable. It packs all its content in a contiguous array for optimum storage and lookup efficiency. This implementation is based on the paper titled Tightly Packed Tries: How to Fit Large Models into Memory, and Make them Load Fast, Too by Ulrich Germann, Eric Joanis, and Samuel Larkin.
R-tree is a tree-based data structure designed to store multi-dimensional geometric data with bounding boxes and provide optimal performance on region- or point-based queries. The one implemented in this library is a variant of R-tree known as R*-tree.
Official API documentation for general users of the library.
Please see the Releases page for source package downloads.
If you need old packages, please find them here.
Please refer to the CONTRIBUTING.md file for build and installation instructions.
mdds is free software. You may copy, distribute, and modify it under the terms of the License contained in the file COPYING distributed with this package. This license is the same as the MIT/X Consortium license.
These are the projects that are known to use mdds.
If you use mdds and would like your project to be included in the above list, please let us know.
