Advanced Data Structures Handbook: The JavaScript Edition
Advanced Data Structures Handbook: The JavaScript Edition
Simplifying Complexity for Real-World Applications
About the Book
"Advanced Data Structures Handbook: The JavaScript Edition" is a practical, accessible guide for JavaScript developers looking to master advanced data structures with real-world applications. Moving beyond basic arrays and hashmaps, this book introduces foundational concepts and provides step-by-step implementations of advanced structures such as B-Trees, Tries, and Red-Black Trees. It highlights their practical use in critical areas like file systems, caching, and database management.
Delving deeper, the book explores probabilistic data structures, including Bloom Filters and Count-Min Sketches, to demonstrate how these tools can efficiently manage large datasets with scalability in mind. Each chapter combines clear explanations with JavaScript-based code snippets and practical scenarios, empowering readers to understand the strengths of each structure and when to apply them—whether for prefix matching, optimizing memory usage, or approximate data analysis.
Whether you're an aspiring developer or a seasoned engineer tackling complex challenges, this handbook equips you with the knowledge and tools to enhance your problem-solving skills and make informed decisions when working with advanced data structures.
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About the Author
Table of Contents
- Introduction
- Chapter 1: Understanding the Importance of Big O Notation
- What is Big O Notation?
- Why is Big O Important?
- Practical Applications
- Optimization Strategies
- Chapter 2: The Limitations of Basic Data Structures
- Challenges with Arrays
- Challenges with HashMaps
- Challenges with LinkedList and DoublyLinkedList
- Chapter 3: Tree and Related Data Structures
- Binary Search Tree (BST)
- AVL Trees
- Red-Black Trees
- B-Trees
- Tries (Prefix Trees)
- Binary Heaps
- Summary of Tree Data Structures
- Chapter 4: Cloud Data Structures
- Bloom Filters
- HyperLogLog
- Count-Min Sketch
- t-digest
- SimHash
- Min-Hash
- Merkle Trees
- Chapter 5: Cache Eviction Strategies
- Least Recently Used (LRU)
- Least Frequently Used (LFU)
- Chapter 6: Hands-on Designing a File System Desktop Application
- Features
- File Structure
- Implementation
- Conclusion
- Appendices
- Appendix A: BinarySearchTree.ts
- Appendix B: AVLTree.ts
- Appendix C: RedBlackTree.ts
- Appendix D: Trie.ts
- Appendix E: BTree.ts
- Appendix F: MaxHeap.ts
- Appendix G: MinHeap.ts
- Appendix H: LFUCache.ts
- Appendix I: LRUCache.ts
- Appendix J: Probabilistic Data Structures
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