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QQ Music Frontend Team
QQ Music Frontend Team
Feb 15, 2022 · Databases

Mastering Redis: From Fundamentals to Advanced Features and Real‑World Use Cases

This comprehensive guide walks you through Redis basics, its data structures, commands, installation steps, high‑concurrency principles, persistence mechanisms, replication, caching strategies, Lua scripting, pipelines, distributed locks, and cluster concepts, providing practical examples and best‑practice recommendations for developers and operators.

Data StructuresLuaPersistence
0 likes · 70 min read
Mastering Redis: From Fundamentals to Advanced Features and Real‑World Use Cases
Python Programming Learning Circle
Python Programming Learning Circle
Feb 14, 2022 · Fundamentals

Python List vs Set: Performance Comparison and Underlying Implementation Details

This article compares the lookup speed of Python lists and sets on large datasets, presents benchmark code and results, and explains why sets are dramatically faster by examining the internal C‑level implementations of list (dynamic array) and set/dict (hash table) including resizing rules and collision‑resolution strategies.

Data StructuresListPython
0 likes · 13 min read
Python List vs Set: Performance Comparison and Underlying Implementation Details
MaGe Linux Operations
MaGe Linux Operations
Jan 29, 2022 · Fundamentals

Master Python’s Powerful Containers: Counter, defaultdict, OrderedDict, deque & ChainMap

This article introduces Python’s collections module as a versatile alternative to built‑in containers, detailing the purpose, key methods, and practical code examples for Counter, defaultdict, OrderedDict, namedtuple, deque, and ChainMap, helping developers choose the right specialized container for their tasks.

ChainMapCollectionsCounter
0 likes · 11 min read
Master Python’s Powerful Containers: Counter, defaultdict, OrderedDict, deque & ChainMap
IT Architects Alliance
IT Architects Alliance
Jan 28, 2022 · Databases

Why Is Redis So Fast? A Deep Dive into Its Data Structures and Architecture

This article explains why Redis achieves high query performance by leveraging in‑memory storage, specialized data structures such as SDS, linked lists, dictionaries, ziplists and skiplists, a single‑threaded event loop with I/O multiplexing, and various optimization techniques that avoid common bottlenecks.

Data StructuresI/O MultiplexingIn-Memory Database
0 likes · 18 min read
Why Is Redis So Fast? A Deep Dive into Its Data Structures and Architecture
Code Ape Tech Column
Code Ape Tech Column
Jan 19, 2022 · Databases

Choosing Appropriate Redis Data Structures for Large‑Scale Statistics: Cardinality, Sorting, and Aggregation

This article explains how to select Redis data structures such as Bitmap, HyperLogLog, Set, List, Sorted Set, and Hash to efficiently handle massive statistical scenarios like user login status, UV counting, ranking, and set aggregation, while providing concrete command examples and best‑practice recommendations.

BitmapCardinalityData Structures
0 likes · 11 min read
Choosing Appropriate Redis Data Structures for Large‑Scale Statistics: Cardinality, Sorting, and Aggregation
Top Architect
Top Architect
Dec 30, 2021 · Fundamentals

Understanding Bloom Filter, Counting Bloom Filter, and Cuckoo Filter: Principles, Issues, and Optimizations

This article explains the motivation behind using probabilistic filters to reduce I/O, describes how Bloom filters, Counting Bloom filters, and Cuckoo filters work, analyzes their false‑positive and deletion problems, and presents practical optimizations such as multiple hash functions and multi‑slot buckets.

Counting Bloom FilterCuckoo FilterData Structures
0 likes · 12 min read
Understanding Bloom Filter, Counting Bloom Filter, and Cuckoo Filter: Principles, Issues, and Optimizations
Java Interview Crash Guide
Java Interview Crash Guide
Dec 24, 2021 · Fundamentals

How Bloom, Counting, and Cuckoo Filters Optimize Database I/O

This article explains how Bloom filters, counting Bloom filters, and Cuckoo filters work, their advantages and limitations, and how they can be used to reduce unnecessary database I/O by efficiently testing element membership before querying the database.

Cuckoo FilterData StructuresDatabase Optimization
0 likes · 11 min read
How Bloom, Counting, and Cuckoo Filters Optimize Database I/O
IT Architects Alliance
IT Architects Alliance
Dec 15, 2021 · Databases

Comprehensive Redis Guide: Data Structures, Commands, Persistence, Performance Tuning, and Deployment Strategies

This article provides a thorough introduction to Redis, covering its core data structures and common commands, persistence options (RDB and AOF), memory‑management and eviction policies, pipelining, transactions and Lua scripting, performance optimization techniques, replication, Sentinel high‑availability, cluster sharding, and a comparison of popular Java clients.

ClusterData StructuresIn-Memory Database
0 likes · 40 min read
Comprehensive Redis Guide: Data Structures, Commands, Persistence, Performance Tuning, and Deployment Strategies
Java Tech Enthusiast
Java Tech Enthusiast
Dec 14, 2021 · Fundamentals

Analysis of Java HashMap put Method and Internal Mechanics

The article dissects Java’s HashMap put method, explaining how it computes a mixed hash, locates an index in a power‑of‑two table, inserts or replaces nodes in a linked‑list chain that may be converted to a red‑black tree, and triggers resizing when the load‑factor threshold is exceeded.

AlgorithmsCollectionsData Structures
0 likes · 13 min read
Analysis of Java HashMap put Method and Internal Mechanics
Python Programming Learning Circle
Python Programming Learning Circle
Dec 1, 2021 · Fundamentals

Introduction to NetworkX: Installation, Basic Usage, and Graph Operations in Python

This article introduces the Python NetworkX library, covering its installation via Anaconda, fundamental graph creation, node and edge manipulation, attribute handling, directed and multigraph features, built‑in generators, analysis functions, and visualization with Matplotlib, all illustrated with concrete code examples.

Data StructuresPythongraph theory
0 likes · 13 min read
Introduction to NetworkX: Installation, Basic Usage, and Graph Operations in Python
Architect
Architect
Nov 30, 2021 · Databases

Why Is Redis So Fast? Architecture, Data Structures, Persistence, Replication and Cluster

This article explains why Redis achieves extremely high performance by being an in‑memory key‑value store, using compact data structures, a single‑threaded command model with epoll‑based I/O multiplexing, efficient hash tables, progressive rehashing, various persistence options, master‑slave replication, Sentinel monitoring and a sharded Cluster architecture.

ClusterData StructuresIn-Memory Database
0 likes · 23 min read
Why Is Redis So Fast? Architecture, Data Structures, Persistence, Replication and Cluster
Top Architect
Top Architect
Oct 29, 2021 · Fundamentals

Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters

The article explains how Bloom filters, Counting Bloom filters, and Cuckoo filters work, their hash‑based bitmap mechanisms, advantages and limitations such as false positives and deletion issues, and presents practical improvements and hash functions for efficient cache and database query optimization.

Cuckoo FilterData StructuresHashing
0 likes · 12 min read
Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters
IT Architects Alliance
IT Architects Alliance
Oct 28, 2021 · Fundamentals

Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters

The article explains the principles, advantages, and limitations of Bloom filters, introduces Counting Bloom filters as an enhanced version, and then details Cuckoo filters and Cuckoo hashing, including their algorithms, performance trade‑offs, and practical improvements for reducing unnecessary I/O operations.

Counting Bloom FilterCuckoo FilterData Structures
0 likes · 11 min read
Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters
Architect's Tech Stack
Architect's Tech Stack
Oct 17, 2021 · Fundamentals

Understanding Why HashMap Uses a Load Factor of 0.75 and How It Resolves Collisions

This article explains the purpose of HashMap's load factor, the trade‑offs between space utilization and collision probability, describes common collision‑resolution techniques such as open addressing, rehashing and chaining, and shows why the default load factor of 0.75 is chosen based on Poisson‑distribution analysis.

Data StructuresHashMapJava
0 likes · 12 min read
Understanding Why HashMap Uses a Load Factor of 0.75 and How It Resolves Collisions
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Oct 14, 2021 · Fundamentals

Introduction to Data Structures and Algorithms: Basics, Sorting, and Advanced Structures

This article introduces the fundamentals of data structures and algorithms, covering basic structures such as arrays and linked lists, common sorting algorithms, advanced structures like B+ trees and red‑black trees, explains Big O notation, and provides Java code examples for dynamic arrays, linked lists, queues, and stacks.

AlgorithmsArraysBig O
0 likes · 15 min read
Introduction to Data Structures and Algorithms: Basics, Sorting, and Advanced Structures
Byte Quality Assurance Team
Byte Quality Assurance Team
Oct 13, 2021 · Fundamentals

Understanding Python Object Assignment, Mutable vs. Immutable Types, and Shallow vs. Deep Copying

This article provides a comprehensive guide to Python's memory management and object assignment mechanisms, clearly explaining the differences between mutable and immutable objects, direct assignment, shallow copying, and deep copying through practical code examples and visual diagrams.

Data StructuresImmutable ObjectsPython Programming
0 likes · 7 min read
Understanding Python Object Assignment, Mutable vs. Immutable Types, and Shallow vs. Deep Copying
Programmer DD
Programmer DD
Oct 3, 2021 · Fundamentals

Master Algorithm Interviews: Key Topics and Efficient Study Strategies

This guide breaks down algorithm interview essentials into data‑structure fundamentals, complexity analysis, and core algorithmic thinking, highlighting the most frequent topics and offering a structured learning path plus a recommended book to help candidates prepare efficiently and boost their offer chances.

Data Structuresalgorithm interviewcoding interview
0 likes · 6 min read
Master Algorithm Interviews: Key Topics and Efficient Study Strategies
Programmer DD
Programmer DD
Oct 2, 2021 · Fundamentals

Master Algorithm Interviews: Core Topics & Proven Study Plan

This guide breaks down the essential data structures, complexity analysis, and algorithmic thinking needed for software engineering interviews, highlights the 80% of topics that dominate most tests, and recommends a systematic study roadmap and a comprehensive book to boost interview success.

Data StructuresLeetCodealgorithm interview
0 likes · 6 min read
Master Algorithm Interviews: Core Topics & Proven Study Plan
Wukong Talks Architecture
Wukong Talks Architecture
Sep 30, 2021 · Backend Development

Understanding Bloom Filters for Preventing Cache Penetration

This article explains the cache‑penetration problem in high‑traffic systems, introduces Bloom filters as a space‑efficient solution, details their construction and usage with Java and Redis examples, and discusses ways to reduce false positives and handle deletions.

Data StructuresJavabloom-filter
0 likes · 8 min read
Understanding Bloom Filters for Preventing Cache Penetration
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Sep 29, 2021 · Databases

Redis Interview Questions and Core Concepts: Data Types, Performance, Persistence, High Availability, and Common Use Cases

This article provides a comprehensive overview of Redis, covering its definition, basic and special data structures, performance optimizations, expiration and eviction policies, common application scenarios, persistence mechanisms, high‑availability architectures, distributed lock implementations, transaction handling, and related algorithms such as Redlock and Bloom filters.

CacheData Structuresdistributed-lock
0 likes · 45 min read
Redis Interview Questions and Core Concepts: Data Types, Performance, Persistence, High Availability, and Common Use Cases
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Sep 25, 2021 · Fundamentals

Overview of Java Collection Framework and Core Concepts

This article provides a comprehensive overview of Java collections, covering the definition, characteristics, differences from arrays, advantages, common collection classes, underlying data structures, fail‑fast mechanism, detailed List, Set, Queue, and Map interfaces, as well as HashMap and ConcurrentHashMap implementations and best practices.

ArrayListCollectionsData Structures
0 likes · 30 min read
Overview of Java Collection Framework and Core Concepts
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Sep 22, 2021 · Databases

Common Redis Interview Questions and Answers

This article provides a comprehensive list of typical Redis interview questions covering its features, performance, data structures, supported data types, common use cases, eviction policies, persistence methods, clustering, high‑availability mechanisms, transaction handling, and comparisons with local caches like Guava and Caffeine.

CacheData StructuresPersistence
0 likes · 15 min read
Common Redis Interview Questions and Answers
Programmer DD
Programmer DD
Sep 22, 2021 · Fundamentals

10 Classic Algorithms That Shaped Modern Computing – From Sorting to Encryption

This article explains what an algorithm is, outlines its three essential properties, and introduces ten foundational computer algorithms—including sorting methods, Fourier transforms, Dijkstra's shortest‑path, RSA encryption, hash functions, factorization, link analysis, PID control, data compression, and random‑number generation—highlighting their historical origins and real‑world impact.

AlgorithmsData StructuresSorting
0 likes · 9 min read
10 Classic Algorithms That Shaped Modern Computing – From Sorting to Encryption
Python Programming Learning Circle
Python Programming Learning Circle
Sep 14, 2021 · Fundamentals

Python Code Snippets: Function Chaining, Default Argument Pitfalls, CSV I/O, List Operations, and More

This article presents a collection of Python programming examples covering function chaining, default‑argument traps, CSV file reading and writing, number‑base conversion, list flattening and merging, dictionary utilities, and common algorithmic patterns such as permutations and combinations.

AlgorithmsData StructuresPython
0 likes · 6 min read
Python Code Snippets: Function Chaining, Default Argument Pitfalls, CSV I/O, List Operations, and More
Su San Talks Tech
Su San Talks Tech
Aug 24, 2021 · Fundamentals

Master the Top 10 Sorting Algorithms in Java: From Bubble to Radix

This comprehensive guide walks Java programmers through the ten classic sorting algorithms—bubble, quick, insertion, shell, selection, heap, merge, bucket, counting, and radix—detailing their principles, stability, time and space complexities, and providing clear Java implementations for each.

Data StructuresSorting Algorithmsalgorithm analysis
0 likes · 21 min read
Master the Top 10 Sorting Algorithms in Java: From Bubble to Radix
Top Architect
Top Architect
Aug 21, 2021 · Fundamentals

Comprehensive Guide to Java Collections Framework: Lists, Sets, Queues, Maps and Their Implementations

This article provides an in-depth overview of Java's Collections Framework, detailing the structure, usage, and source code of core interfaces like List, Set, Queue, and Map, and their key implementations such as ArrayList, LinkedList, HashSet, TreeSet, PriorityQueue, ArrayDeque, HashMap, and Hashtable, while highlighting performance characteristics and thread-safety considerations.

Backend DevelopmentCollectionsData Structures
0 likes · 39 min read
Comprehensive Guide to Java Collections Framework: Lists, Sets, Queues, Maps and Their Implementations
Wukong Talks Architecture
Wukong Talks Architecture
Jul 21, 2021 · Fundamentals

Understanding Redis Simple Dynamic Strings (SDS): Structure, Benefits, and Memory Management

This article explains the Redis Simple Dynamic String (SDS) data structure, comparing it with traditional C strings, detailing its struct layout, O(1) length retrieval, pre‑allocation strategy, lazy space release, and provides code examples illustrating how SDS avoids buffer overflows and improves performance.

C stringsData StructuresMemory Management
0 likes · 11 min read
Understanding Redis Simple Dynamic Strings (SDS): Structure, Benefits, and Memory Management
Programmer DD
Programmer DD
Jul 19, 2021 · Backend Development

How Redis Ziplist Compresses Memory and When to Use It

This article explains Redis's ziplist compressed list structure, its internal fields, lookup algorithm, performance characteristics, configuration thresholds for Hash and List types, and demonstrates a real‑world use case with memory‑saving calculations and experimental results.

Data Structuresmemory compressionredis
0 likes · 11 min read
How Redis Ziplist Compresses Memory and When to Use It
Selected Java Interview Questions
Selected Java Interview Questions
Jul 5, 2021 · Fundamentals

Heap Sort: Theory, Steps, and Java Implementation

This article explains heap sort's time and space complexities, introduces max‑heap and min‑heap concepts, details the algorithmic steps for building and maintaining the heap, and provides a complete Java implementation with accompanying code examples.

Data StructuresJavaSorting
0 likes · 8 min read
Heap Sort: Theory, Steps, and Java Implementation
Sohu Tech Products
Sohu Tech Products
Jun 23, 2021 · Backend Development

Using Redis Data Structures for Efficient Large‑Scale Statistics: Cardinality, Sorting, and Aggregation

The article explains how to choose appropriate Redis data structures—such as Bitmap, HyperLogLog, Set, List, Hash, and Sorted Set—to efficiently handle massive statistical scenarios like UV counting, ranking, and set‑based aggregation, while providing concrete command examples and performance considerations.

Data StructuresHyperLogLogSorted Set
0 likes · 13 min read
Using Redis Data Structures for Efficient Large‑Scale Statistics: Cardinality, Sorting, and Aggregation
政采云技术
政采云技术
Jun 22, 2021 · Frontend Development

Understanding Immutable Data Structures and Their Use in React and Redux

This article explains what immutable data structures are, outlines their advantages such as reduced complexity, memory savings, easy state rollback, and functional programming benefits, and demonstrates practical usage of Immutable.js in React components and Redux integration with code examples and best‑practice tips.

Data StructuresImmutableReact
0 likes · 14 min read
Understanding Immutable Data Structures and Their Use in React and Redux
php Courses
php Courses
Jun 15, 2021 · Fundamentals

Comprehensive Technical Exam with Multiple‑Choice, Short Answer, and Programming Questions

The article provides a full‑length technical exam covering multiple‑choice questions on programming history, algorithms, networking and 5G, short answer queries about design patterns and tree operations, and coding challenges that ask participants to implement solutions for counting ways to eat bread, climb stairs, and analyze a C program that counts cycles in a permutation.

AlgorithmsData StructuresNetworking
0 likes · 6 min read
Comprehensive Technical Exam with Multiple‑Choice, Short Answer, and Programming Questions
FunTester
FunTester
Jun 11, 2021 · Fundamentals

Personal Reflections on Algorithms, Data Structures, and Complexity

This article shares the author’s personal insights on a book about algorithms, data structures, and complexity, explaining core concepts such as algorithm definition, common data structures, time and space complexity, and offering intuitive examples to aid understanding.

AlgorithmsData Structurescomplexity
0 likes · 12 min read
Personal Reflections on Algorithms, Data Structures, and Complexity
IT Architects Alliance
IT Architects Alliance
May 31, 2021 · Backend Development

Inside Nginx: Master/Worker Model, Async I/O, and Core Data Structures Explained

This article explains how Nginx runs as a daemon with a master process and multiple worker processes, why it prefers a multi‑process asynchronous non‑blocking architecture over threads, and details the key internal data structures such as connections, requests, arrays, queues, lists, strings, memory pools, hash tables, and red‑black trees that enable its high‑performance HTTP handling.

AsynchronousBackendData Structures
0 likes · 18 min read
Inside Nginx: Master/Worker Model, Async I/O, and Core Data Structures Explained
Intelligent Backend & Architecture
Intelligent Backend & Architecture
May 24, 2021 · Fundamentals

Master Data Structures & Algorithms: Comprehensive Guide with Visual Tools

This article provides a comprehensive overview of data structures and algorithms, covering fundamental concepts such as data, elements, objects, logical and storage structures, common structures like lists, stacks, queues, trees, graphs, algorithm design techniques, complexity analysis, and includes visual resources and code examples.

AlgorithmsData StructuresQueue
0 likes · 33 min read
Master Data Structures & Algorithms: Comprehensive Guide with Visual Tools
Programmer DD
Programmer DD
May 24, 2021 · Fundamentals

Master Red‑Black Trees: From 2‑3‑4 Trees to Practical Implementation

This article walks through the fundamentals of red‑black trees, explains their equivalence to 2‑3‑4 trees, details insertion and deletion rules, compares their performance to plain binary search trees, and shares practical debugging tips for implementing a balanced tree in code.

2-3-4 TreeData StructuresRed-Black Tree
0 likes · 12 min read
Master Red‑Black Trees: From 2‑3‑4 Trees to Practical Implementation
Python Crawling & Data Mining
Python Crawling & Data Mining
May 22, 2021 · Fundamentals

Master Python Lists: From Basics to Advanced Operations

This tutorial walks you through Python list syntax, common operations such as adding, modifying, searching, deleting, sorting, and nesting, complete with code examples and output screenshots, helping beginners and intermediate programmers deepen their understanding of list handling.

Data StructuresListOperations
0 likes · 8 min read
Master Python Lists: From Basics to Advanced Operations
Intelligent Backend & Architecture
Intelligent Backend & Architecture
May 14, 2021 · Fundamentals

Master Hash Tables, Heaps, and Graph Algorithms: From Basics to Dijkstra

This article introduces core data structures—hash tables, heaps, and graphs—explains their definitions, visual representations, and key operations, then delves into fundamental graph algorithms such as BFS, Dijkstra, Floyd, minimum spanning trees, and topological sorting, illustrating each with examples and code.

Data StructuresDijkstraHeap
0 likes · 16 min read
Master Hash Tables, Heaps, and Graph Algorithms: From Basics to Dijkstra
Intelligent Backend & Architecture
Intelligent Backend & Architecture
May 14, 2021 · Fundamentals

Mastering Algorithms: Definitions, Design Principles, and Complexity Explained

This article provides a comprehensive overview of algorithms, covering their definition, five essential characteristics, design principles, time and space complexity analysis, common complexity classes, and a variety of algorithmic strategies such as recursion, greedy, divide‑and‑conquer, and dynamic programming.

AlgorithmsBig OData Structures
0 likes · 25 min read
Mastering Algorithms: Definitions, Design Principles, and Complexity Explained
Intelligent Backend & Architecture
Intelligent Backend & Architecture
May 13, 2021 · Fundamentals

Mastering Data Structures: From Basics to Advanced Implementations

This comprehensive guide explains core data concepts, defines data, data objects, elements and types, explores logical and physical structures, details sequential, linked, indexed and hash storage, and provides Java code examples for arrays, linked lists, stacks, queues, trees, binary search trees, AVL and red‑black trees, illustrating how to choose and implement appropriate structures for real‑world problems.

AlgorithmsData StructuresJava
0 likes · 24 min read
Mastering Data Structures: From Basics to Advanced Implementations
Full-Stack Internet Architecture
Full-Stack Internet Architecture
May 13, 2021 · Fundamentals

Understanding Trees, Binary Trees, AVL Trees, and Red-Black Trees: Concepts, Properties, and Operations

This article explains the fundamentals of tree data structures—including general trees, binary trees, AVL balanced trees, and red‑black trees—covering their definitions, node types, properties, rotation techniques, and insertion and deletion algorithms with illustrative code examples.

AlgorithmsData StructuresRed-Black Tree
0 likes · 17 min read
Understanding Trees, Binary Trees, AVL Trees, and Red-Black Trees: Concepts, Properties, and Operations
Python Programming Learning Circle
Python Programming Learning Circle
Apr 29, 2021 · Fundamentals

Python Basics: Variables, Control Flow, Data Structures, and Object‑Oriented Programming

This tutorial introduces Python fundamentals, covering why to learn the language, variable assignment, conditional statements, loops, lists, dictionaries, iteration techniques, and core object‑oriented concepts such as classes, getters/setters, encapsulation, and inheritance, all illustrated with clear code examples.

Control FlowData StructuresInheritance
0 likes · 20 min read
Python Basics: Variables, Control Flow, Data Structures, and Object‑Oriented Programming
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Apr 27, 2021 · Databases

Why Redis Is Fast: Core Principles and Internal Data Structures

This article explains why Redis achieves extremely high performance by leveraging pure in‑memory operations, a global O(1) hash table, efficient data structures such as SDS, ziplist, quicklist and skiplist, a single‑threaded event loop with non‑blocking I/O multiplexing, and adaptive encoding strategies.

Data StructuresIn-MemorySingle‑threaded
0 likes · 20 min read
Why Redis Is Fast: Core Principles and Internal Data Structures
Open Source Tech Hub
Open Source Tech Hub
Apr 22, 2021 · Databases

Why MySQL Indexes Use B‑Tree, Not Hash: Understanding Index Data Structures

The article explains how MySQL indexes rely on ordered data structures—binary trees, red‑black trees, hash tables, and especially B‑Trees—to accelerate queries, compares their performance characteristics, illustrates how tree height affects I/O operations, and shows why B‑Tree is preferred for range searches.

B+TreeData Structuresindex
0 likes · 5 min read
Why MySQL Indexes Use B‑Tree, Not Hash: Understanding Index Data Structures
Tencent Cloud Developer
Tencent Cloud Developer
Apr 20, 2021 · Databases

Advanced Guide to Redis: Data Structures, Usage, Internals, Performance Issues, and Security

This comprehensive Redis guide explains core data structures like strings, lists, sets, hashes and sorted sets, explores advanced features such as Bloom filters, distributed locks and clustering, details internal mechanisms, performance bottlenecks, and provides essential security best practices for safe, high‑performance deployment.

Data StructuresSecurityperformance
0 likes · 13 min read
Advanced Guide to Redis: Data Structures, Usage, Internals, Performance Issues, and Security
Intelligent Backend & Architecture
Intelligent Backend & Architecture
Apr 2, 2021 · Fundamentals

Master Java Collections: From ArrayList to ConcurrentHashMap Explained

This article provides a comprehensive overview of Java's collection framework, detailing the roles of interfaces, implementations, and algorithms, comparing collections with arrays, describing common List, Set, and Map classes, their underlying data structures, thread‑safety characteristics, and best practices for iteration and usage.

CollectionsConcurrentHashMapData Structures
0 likes · 48 min read
Master Java Collections: From ArrayList to ConcurrentHashMap Explained
Sohu Tech Products
Sohu Tech Products
Mar 31, 2021 · Databases

Why Redis Is Fast: Core Principles, Data Structures, and Architecture

This article explains why Redis achieves exceptionally high performance by combining pure in‑memory operations, a global hash table with O(1) lookups, efficient data structures such as SDS, ziplist, quicklist and skiplist, a single‑threaded event loop with non‑blocking I/O multiplexing, and adaptive encoding strategies.

Data StructuresIO MultiplexingIn-Memory Database
0 likes · 20 min read
Why Redis Is Fast: Core Principles, Data Structures, and Architecture
Python Crawling & Data Mining
Python Crawling & Data Mining
Mar 30, 2021 · Fundamentals

Boost Your Python Skills with a Free Exam Simulation Tool

This article introduces a free Python certification exam simulator, explains how to download, install, and crack the software, and shows how to use its diverse question sets to assess and improve your Python fundamentals, data‑structure knowledge, and overall coding confidence.

Data StructuresExam PreparationPython
0 likes · 7 min read
Boost Your Python Skills with a Free Exam Simulation Tool
dbaplus Community
dbaplus Community
Mar 28, 2021 · Databases

Why Redis Is So Fast: Inside Its Core Architecture

This article explains why Redis achieves exceptional speed by examining its memory‑only architecture, single‑threaded event loop, and the specialized data structures—global hash tables, SDS strings, ziplist, quicklist, skiplist, and intset—that provide O(1) or O(log N) operations, along with non‑blocking I/O multiplexing.

Data StructuresI/O MultiplexingIn-Memory Database
0 likes · 20 min read
Why Redis Is So Fast: Inside Its Core Architecture
Top Architect
Top Architect
Mar 22, 2021 · Fundamentals

Understanding Red‑Black Trees and Related Balanced Tree Structures

This article explains the concepts, properties, and operations of binary trees, binary search trees, AVL trees, 2‑3 and 2‑3‑4 trees, B‑trees, and especially red‑black trees, illustrating how they maintain balance through rotations and why they are widely used in ordered data storage.

AlgorithmsBalanced TreesBinary Search Tree
0 likes · 12 min read
Understanding Red‑Black Trees and Related Balanced Tree Structures
Top Architect
Top Architect
Mar 15, 2021 · Fundamentals

Analysis of JDK 1.8 HashMap Implementation Compared to JDK 1.7

This article explains the major differences between JDK 1.8 and JDK 1.7 HashMap implementations, detailing the initialization process, the putVal algorithm steps, how collisions are handled with linked lists and red‑black trees, and the changes in resizing behavior.

CollectionsData StructuresHashMap
0 likes · 5 min read
Analysis of JDK 1.8 HashMap Implementation Compared to JDK 1.7
Liangxu Linux
Liangxu Linux
Mar 14, 2021 · Fundamentals

Master Red-Black Trees with Illustrated Comics: From Basics to Insertion & Deletion

An illustrated guide walks readers through the fundamentals of red‑black trees, explaining binary search tree basics, their limitations, and the red‑black tree’s balancing operations—including node rotations, insertion, and deletion cases—while providing complete source code tested with massive random operations.

AlgorithmsBinary Search TreeData Structures
0 likes · 5 min read
Master Red-Black Trees with Illustrated Comics: From Basics to Insertion & Deletion
Open Source Linux
Open Source Linux
Mar 12, 2021 · Backend Development

Redis vs Memcached: Which In‑Memory Database Wins for Your Projects?

This article compares Redis and Memcached across thread model, data structures, eviction policies, pipelining, persistence, high availability, and clustering, helping developers choose the most suitable in‑memory database for their specific performance and feature requirements.

Data StructuresIn-Memory DatabaseMemcached
0 likes · 9 min read
Redis vs Memcached: Which In‑Memory Database Wins for Your Projects?
21CTO
21CTO
Mar 11, 2021 · Fundamentals

14 Essential Coding Interview Patterns Every Developer Should Master

This article outlines fourteen common algorithmic patterns that appear in programming interviews, explains how to recognize each pattern, and provides example problems for each, helping developers focus their preparation and solve interview questions more efficiently without endless brute‑force practice.

Data StructuresSoftware Engineeringalgorithm patterns
0 likes · 17 min read
14 Essential Coding Interview Patterns Every Developer Should Master
Practical DevOps Architecture
Practical DevOps Architecture
Mar 11, 2021 · Fundamentals

Python Dictionary and Set Basics

This article introduces Python's built‑in dictionary and set types, explaining their characteristics, common operations, and providing example code to demonstrate creation, element access, and membership testing, while also highlighting key differences such as mutability of values and the use of hashable elements as keys.

Data StructuresPythonSet
0 likes · 5 min read
Python Dictionary and Set Basics
58 Tech
58 Tech
Mar 8, 2021 · Fundamentals

Real‑Time Inverted Index Update Techniques in the 58 Search Engine

This article explains how the 58 search engine achieves millisecond‑level real‑time inverted‑index updates by redesigning the underlying data structures, combining static and dynamic indexing, using a chain‑array hybrid, segment merging strategies, and lock‑free read‑write concurrency while maintaining search performance.

Data StructuresReal-Time UpdateSegment Merging
0 likes · 18 min read
Real‑Time Inverted Index Update Techniques in the 58 Search Engine
Python Programming Learning Circle
Python Programming Learning Circle
Mar 2, 2021 · Fundamentals

30 Minimal Python Tasks and Code Snippets for Beginners

This article presents 30 concise Python tasks, each demonstrating a specific technique such as duplicate detection, memory usage, string manipulation, list chunking, dictionary merging, and more, allowing beginners to practice and developers to discover useful code patterns.

AlgorithmsCoding ExercisesData Structures
0 likes · 13 min read
30 Minimal Python Tasks and Code Snippets for Beginners
Baidu Geek Talk
Baidu Geek Talk
Feb 22, 2021 · Fundamentals

Can Embracing Hash Collisions Boost Performance? Inside B16 Hash Table

This article revisits traditional hash table design, then introduces a novel approach that deliberately leverages a controlled probability of hash collisions combined with SIMD parallelism, presenting the B16 and B16Compact hash tables, their structures, algorithms, and experimental results showing superior speed and space efficiency compared to unordered_map and F14.

B16CData Structures
0 likes · 17 min read
Can Embracing Hash Collisions Boost Performance? Inside B16 Hash Table
Python Crawling & Data Mining
Python Crawling & Data Mining
Feb 20, 2021 · Fundamentals

Unlock Python’s Speed: Master dict and set for Fast Data Lookup

This article explains Python’s built-in dict and set structures, comparing them with lists, demonstrating their fast key-value lookups, handling missing keys, and common operations like insertion, deletion, and set algebra, while providing clear code examples and practical tips for effective use.

Data StructuresImmutable ObjectsPython
0 likes · 9 min read
Unlock Python’s Speed: Master dict and set for Fast Data Lookup
Architect
Architect
Feb 12, 2021 · Backend Development

Understanding Nginx Architecture: Daemon Processes, Workers, Connections, and Core Data Structures

This article explains Nginx's high‑performance architecture, covering its daemon mode with master and worker processes, the thundering‑herd problem, advantages of process‑based concurrency, asynchronous non‑blocking I/O, connection handling, keep‑alive and pipeline techniques, as well as key internal data structures such as arrays, queues, lists, strings, memory pools, hash tables, and red‑black trees.

Backend DevelopmentConnection PoolingData Structures
0 likes · 18 min read
Understanding Nginx Architecture: Daemon Processes, Workers, Connections, and Core Data Structures
Efficient Ops
Efficient Ops
Feb 3, 2021 · Databases

Master Redis: Core Data Types, Commands, and Advanced Features Explained

This article introduces Redis as an open‑source, in‑memory data‑structure store, explains its role as a NoSQL database, details its five fundamental data types, common commands, expiration handling, pipelines, and transactions, and shows how it fits into modern scaling architectures.

Data StructuresNoSQLTransactions
0 likes · 14 min read
Master Redis: Core Data Types, Commands, and Advanced Features Explained
Programmer DD
Programmer DD
Jan 31, 2021 · Fundamentals

Understanding Git Internals: How the Version Control System Works Under the Hood

This article delves into Git’s core architecture, explaining its fast, distributed nature, immutable objects, porcelain and plumbing commands, the content‑addressable version database, and how init, add, and commit manipulate the working directory, index, and repository to create snapshots of project history.

Data StructuresGitVersion Control
0 likes · 12 min read
Understanding Git Internals: How the Version Control System Works Under the Hood
IT Xianyu
IT Xianyu
Dec 30, 2020 · Fundamentals

Quick Introduction to 8 Common Data Structures

This article provides a concise overview of eight essential data structures—arrays, linked lists, stacks, queues, hash tables, trees, heaps, and graphs—explaining their definitions, core operations, and typical applications in software development and computer science.

AlgorithmsArraysData Structures
0 likes · 12 min read
Quick Introduction to 8 Common Data Structures
DataFunTalk
DataFunTalk
Dec 25, 2020 · Fundamentals

Curated Collection of Algorithm and Data Structure Problems with Solution Articles

This article compiles a comprehensive list of over 400 algorithm and data‑structure problem solutions—including dynamic programming, backtracking, DFS/BFS, binary‑tree, linked‑list, stack, sorting, searching and classic puzzles—organized by topic and linked to detailed explanations for easy reference.

AlgorithmsBacktrackingData Structures
0 likes · 9 min read
Curated Collection of Algorithm and Data Structure Problems with Solution Articles
Architecture Digest
Architecture Digest
Dec 23, 2020 · Databases

Understanding Redis Object Types and Their Underlying Data Structures

This article explains the five core Redis object types—strings, lists, hashes, sets, and sorted sets—their possible encodings, and the underlying data structures such as SDS, linked lists, hash tables, ziplists, intsets, and skiplists, including details of the redisObject layout and rehash mechanisms.

Data Structuresdatabasesencoding
0 likes · 22 min read
Understanding Redis Object Types and Their Underlying Data Structures