Sparse Tables

Sparse Tables answer range min/max in O(1) after O(n log n) prep. Ideal for static data.

35 lessons
161 min

Lessons

1. Intro

Why Sparse Tables matter

2m

2. Power-of-2 Ranges

The building blocks

3m

3. Building the Table

DP construction

3m

4. The Overlap Trick

Idempotent operations

3m

5. Precomputing Log Values

Avoiding log calls

2m

6. Problem - Range Minimum Query

The classic RMQ problem

2m1 problems

7. Sparse Table RMQ Solution

Complete implementation

4m

8. RMQ Solution

Implement your solution

12m1 problems

9. Idempotent Operations

When overlap trick works

3m

10. Non-Idempotent Queries

O(log n) fallback

3m

11. Problem - Range GCD Queries

GCD is idempotent

2m

12. Range GCD Solution

Implement your solution

10m

13. LCA with Sparse Table

Euler tour + RMQ

4m

14. Euler Tour Construction

Building the tour

3m

15. Problem - LCA Queries

O(1) LCA with preprocessing

3m1 problems

16. LCA Solution

Implement your solution

20m1 problems

17. Range Max with Index

Returning position, not value

3m

18. 2D Sparse Table

Rectangle min/max queries

4m

19. Sparse Table vs Others

Choosing the right tool

3m

20. Problem - Static Range Min

Many queries, no updates

2m1 problems

21. Static RMQ Solution

Implement your solution

12m1 problems

22. Second Minimum Query

Storing more information

3m

23. Min with Index

Tracking position

3m

24. Disjoint Sparse Tables

For non-idempotent operations

4m

25. Sparse Table for Matrices

2D rectangle queries

4m

26. Problem - Range Xor Queries

XOR is not idempotent

3m1 problems

27. Range XOR Solution

Prefix XOR approach

8m1 problems

28. Problem - Forest Queries

2D static queries

3m1 problems

29. Forest Queries Solution

2D prefix sums

10m1 problems

30. Common Sparse Table Mistakes

Debugging tips

3m

31. Space Optimization

When memory matters

3m

32. RMQ to LCA Reduction

The reverse direction

3m

33. Challenge: Multiple Values

Top-k in a range

3m

34. Quiz: Sparse Tables

Test your understanding

5m1 problems

35. Section Recap

What you learned

3m

Practice Problems

1.

Perfect introduction to sparse tables with classic RMQ on static array. Standard O(n log n) preprocessing with O(1) queries for learning fundamentals.

2.

Combines LCA with sparse table and tree distance calculations. Teaches how to find equidistant nodes using binary lifting.

3.
Fools and RoadsCodeforcesmedium

Classic LCA problem using sparse table with path queries on trees. Introduces difference arrays on trees combined with LCA.

4.

Demonstrates sparse table for range GCD queries combined with binary search. Shows how GCD is idempotent and perfect for sparse tables.

5.
Integers Have FriendsCodeforcesmedium

Creative range GCD with difference arrays. Transforms finding longest subarray with GCD > 1, teaching problem transformation with sparse tables.

6.
Duff in the ArmyCodeforceshard

Advanced sparse table on trees storing multiple values per node. Combines LCA with binary lifting while maintaining top-k elements.

7.
Blood CousinsCodeforceshard

Uses binary jumping (sparse table) for ancestor queries on trees. Teaches DSU on tree combined with sparse table for counting relatives.

8.

Combines MST with LCA using sparse table to find maximum edge on paths. Shows range maximum queries for tree path optimization.

9.
R2D2 and Droid ArmyCodeforcesmedium

Sliding window with sparse table for range maximum queries. Demonstrates two-pointer technique with O(1) RMQ in dynamic windows.

10.

Range frequency queries with Mo's algorithm and sparse table optimizations. Great for understanding offline query processing.

11.

Uses monotonic stack to find previous/next smaller elements (related to RMQ). Teaches how range minimum concepts apply to optimization.

12.

Tree DP with rerooting technique using binary lifting concepts. Shows how sparse table principles extend to DP on trees.

13.

Pure binary lifting implementation, the foundation of sparse tables on trees. Perfect for O(n log n) preprocessing with O(log n) queries.

14.

Classic range maximum solvable with sparse table for O(1) per query. Alternative to deque approach for fixed-size sliding windows.

15.

Offline queries with range operations requiring sorted processing. Demonstrates when sparse table preprocessing concepts apply.

16.

Perfect example of prefix operations for associative functions. Shows when sparse table is overkill versus prefix arrays.

17.

RMQ application finding next smaller elements. Fundamental problem showing how range minimum concepts solve optimization problems.

18.

Range minimum with constraint optimization. Teaches practical RMQ where minimum value in range determines score.

19.

Offline queries with sorted processing (similar to sparse table philosophy). Shows preprocessing for efficient bitwise query answering.

20.

Advanced range query with negative numbers requiring monotonic deque. Demonstrates when simple sparse table fails for non-idempotent operations.

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