Hash tree (persistent data structure)

In computer science, a hash tree (or hash trie) is a persistent data structure that can be used to implement sets and maps, intended to replace hash tables in purely functional programming. In its basic form, a hash tree stores the hashes of its keys, regarded as strings of bits, in a trie, with the actual keys and (optional) values stored at the trie's "final" nodes.^[1]

Hash array mapped tries and Ctries are refined versions of this data structure, using particular type of trie implementations.^[1]

References

↑ 1.0 1.1 Phil Bagwell (2000). Ideal Hash Trees (PDF) (Report). Infoscience Department, École Polytechnique Fédérale de Lausanne.

Tree data structures

Search trees (dynamic sets/associative arrays)	2–3 2–3–4 AA (a,b) AVL B B+ B* B^x (Optimal) Binary search Dancing HTree Interval Order statistic (Left-leaning) Red-black Scapegoat Splay T Treap UB Weight-balanced

Heaps	Binary Binomial Fibonacci Leftist Pairing Skew Van Emde Boas

Tries	Hash Radix Suffix Ternary search X-fast Y-fast

Spatial data partitioning trees	BK BSP Cartesian Hilbert R k-d (implicit k-d) M Metric MVP Octree Priority R Quad R R+ R* Segment VP X

Other trees	Cover Exponential Fenwick Finger Fusion Hash calendar iDistance K-ary Left-child right-sibling Link/cut Log-structured merge Merkle PQ Range SPQR Top

Data structures

Types	Collection Container

Abstract	Associative array Double-ended priority queue Double-ended queue List Map Multimap Priority queue Queue Set multiset Disjoint Sets Stack

Arrays	Bit array Circular buffer Dynamic array Hash table Hashed array tree Sparse array

Linked	Association list Linked list Skip list Unrolled linked list XOR linked list

Trees	B-tree Binary search tree AA AVL red-black self-balancing splay Heap binary binomial Fibonacci R-tree R* R+ Hilbert Trie Hash tree

Graphs	Binary decision diagram Directed acyclic graph Directed acyclic word graph

List of data structures