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Opening your learning path
Progress is saved as you study.
The Union-Find (Disjoint Set Union - DSU) pattern applies when you need the Union-Find (Disjoint Set Union - DSU) technique within the Graph Traversal Patterns (DFS & BFS) pattern. Its time complexity is O(α(n)) per operation and space complexity O(n). It is used in 10 problems on Thita, including Accounts Merge, Graph Valid Tree and Largest Component Size by Common Factor. Common variations are Graph DFS - Cycle Detection (Directed Graph) and Deep Copy / Cloning.
Master Union-Find data structure with path compression and union by rank for connectivity problems.
Union-Find (Disjoint Set Union - DSU) is one of the 12 subpatterns of the Graph Traversal Patterns (DFS & BFS) pattern, which covers dFS/BFS traversal, topological sort, shortest paths, Union-Find, and MST. The whole pattern is about 5 hours of study. This subpattern is a depth topic for once the core techniques are automatic.
Master graph algorithms including DFS/BFS traversal, topological sort, shortest paths (Dijkstra, Bellman-Ford), Union-Find, and advanced graph concepts. Problems in this subpattern are usually searched for as Union-Find, disjoint set, DSU, path compression, union by rank, redundant connection.
Read the theory for Union-Find (Disjoint Set Union - DSU), then work the problems attached to it in the browser editor. Your solution runs against the problem's test cases, and the AI coach offers a hint about the technique you are missing rather than a finished solution. Progress is tracked per subpattern, so the Graph Traversal Patterns (DFS & BFS) tracker shows this one as covered once you have solved its problems.
Union-Find (Disjoint Set Union - DSU) is one lesson in a 16-pattern DSA course. If you are preparing end to end, work the interview-critical patterns first and use the pattern sheet as the checklist; if you are here for one technique, the Graph Traversal Patterns (DFS & BFS) guide is the shortest path back to the rest of it.