Disjoint Set Neil Tang 02232010 CS 223 Advanced
- Slides: 20
Disjoint Set Neil Tang 02/23/2010 CS 223 Advanced Data Structures and Algorithms 1
Class Overview Ø Disjoint Set and An Application Ø Basic Operations Ø Linked-list Implementation Ø Array Implementation Ø Union-by-Size and Union-by-Height(Rank) Ø Find with Path Compression Ø Worst-Case Time Complexity CS 223 Advanced Data Structures and Algorithms 2
Disjoint Set Ø Given a set of elements, we can have a collection S = {S 1, S 2, . . . Sk} of disjoint dynamic (sub) sets. Ø Representative of a set: We choose one element of a set to identify the set, e. g. , we use the root of a tree to identify a tree, or the head element of a linked list to access the linked list. Ø Usually, we want to find out if two elements belong to the same set. CS 223 Advanced Data Structures and Algorithms 3
An Application Ø Given an undirected graph G = (V, E) Ø We may want to find all connected components, whether the graph is connected or whether two given nodes belong to the same connected component. a d f h e g i c b CS 223 Advanced Data Structures and Algorithms 4
Basic Operations Ø find(x): find which disjoint set x belongs to Ø Union(x, y): Union set x and set y. CS 223 Advanced Data Structures and Algorithms 5
Linked-list Implementation head f nil tail a b find(b) union(f, b) a b CS 223 Advanced Data Structures and Algorithms c nil c tail f nil tail 6
Array Implementation Ø Assume that all the elements are numbered sequentially from 0 to N-1. CS 223 Advanced Data Structures and Algorithms 7
Array Implementation CS 223 Advanced Data Structures and Algorithms 8
Array Implementation CS 223 Advanced Data Structures and Algorithms 9
Union Operation Time complexity: O(1) CS 223 Advanced Data Structures and Algorithms 10
Find Operation Time complexity: O(N) CS 223 Advanced Data Structures and Algorithms 11
Union-by-Size Ø Make the smaller tree a subtree of the larger and break ties arbitrarily. CS 223 Advanced Data Structures and Algorithms 12
Union-by-Height (Rank) Ø Make the shallow tree a subtree of the deeper and break ties arbitrarily. CS 223 Advanced Data Structures and Algorithms 13
Size and Height -1 -1 -1 4 -5 4 4 6 0 1 2 3 4 5 6 7 -1 -1 -1 4 -3 4 4 6 CS 223 Advanced Data Structures and Algorithms 14
Union-by-Height (Rank) Time complexity: O(1) CS 223 Advanced Data Structures and Algorithms 15
Worst-Case Tree CS 223 Advanced Data Structures and Algorithms 16
Find(14) with Path Compression CS 223 Advanced Data Structures and Algorithms 17
Find with Path Compression CS 223 Advanced Data Structures and Algorithms 18
Find with Path Compression Ø Fully compatible with union-by-size. Ø Not compatible with union-by-height. Ø Union-by-size is usually as efficient as union-by-height. CS 223 Advanced Data Structures and Algorithms 19
Worst-Case Time Complexity Ø If both union-by-size and path compression heuristics are used, the worst-case running time for any sequence of M union/find operations is O(M * (M, N)) Ø (M, N) is the inverse Ackermann function which grows even slower than log. N. CS 223 Advanced Data Structures and Algorithms 20
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