Best of Data Structures — September 2024

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   Article

   PlanetScale·2y

   B-trees and database indexes

   B-trees and B+ trees are essential for efficient data lookups in database management systems like MySQL, Postgres, and MongoDB. They are structured to store key/value pairs in a way that optimizes search operations. MySQL's InnoDB engine relies heavily on B+ trees, where the choice of primary key significantly impacts performance. B-trees are well-suited for large data volumes that need persistent disk storage, and B+ trees offer advantages like storing all values at the leaf level and having linked lists for faster sequential access. Sequential keys generally improve performance over random or UUID keys.

   99

   2
2. 2
   Article

   Kirupa·2y

   Timsort: A Lightning Fast Hybrid Sorting Algorithm

   Timsort is a highly efficient hybrid sorting algorithm that combines the strengths of Merge sort and Insertion sort. It excels in real-world scenarios by effectively leveraging existing order in data. Timsort sorts data by dividing it into small chunks, sorting these chunks with Insertion sort, and then merging them using a Merge sort strategy. Key optimizations include identifying ascending/descending runs, galloping mode for faster merging, and adaptive merging strategies. These features make Timsort a robust choice for sorting operations, particularly when dealing with partially sorted data.

   76

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3. 3
   Article

   Real Python·2y

   Lists vs Tuples in Python – Real Python

   Learn about lists and tuples in Python, including how to create, access, and manipulate these sequence data types. Discover the core features that distinguish lists from tuples, such as mutability and use cases for homogeneous and heterogeneous data. Gain the essential skills to decide when to use each type in your Python code.

   36
4. 4
   Article

   Javarevisited·2y

   Review of Tree Data Structure using JAVA

   A tree data structure in Java is explored, detailing various types like full, perfect, and complete trees. The binary search tree (BST) is explained with its Big O complexities for insert, remove, and lookup operations being O(log n). Additionally, tree traversal techniques including Breadth First Search (BFS) and three types of Depth First Search (DFS)—Pre Order, Post Order, and In Order—are discussed.

   31
5. 5
   Video

   YouTube·2y

   how much DSA to learn?

   Understanding core data structures and algorithms is crucial for coding interviews. While advanced concepts like segment trees may not be frequently asked, focusing on essential data structures and techniques such as greedy algorithms, recursion, and dynamic programming is recommended. A specific list of nine core data structures and associated algorithms is available on instab.

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