consistent hashing

Lobster Programming

Jun 11, 2024 · Fundamentals

Why Consistent Hashing Matters: Solving Cache Distribution and Scaling Issues

Consistent hashing replaces simple modulo‑based distribution to efficiently locate cached data across changing numbers of servers, using a hash ring and virtual nodes to ensure balanced load, minimize data movement, and improve reliability in distributed caching, load balancing, and database sharding scenarios.

Load BalancingShardingconsistent hashing

0 likes · 6 min read

Why Consistent Hashing Matters: Solving Cache Distribution and Scaling Issues

Architect's Guide

Jun 26, 2023 · Fundamentals

Consistent Hashing Algorithm: Principles, Virtual Nodes, and Practical Applications

This article explains the consistent hashing algorithm, its hash‑ring model, how it overcomes the limitations of simple modulo hashing in distributed caches, the role of virtual nodes for load balancing, and common use cases such as memcached, Redis clusters, and load‑balancing routers.

Load Balancingcachingconsistent hashing

0 likes · 10 min read

Consistent Hashing Algorithm: Principles, Virtual Nodes, and Practical Applications

Aikesheng Open Source Community

Dec 1, 2022 · Databases

Understanding Redis Cluster Architecture: High Availability, Data Partitioning, and Proxy Strategies

This article explains the fundamental concepts of Redis cluster architecture, covering high‑availability with Sentinel, data partitioning methods, proxy‑based sharding techniques, the mechanics of Redis Cluster without a central node, and practical considerations for multi‑key operations in a distributed environment.

ClusterData PartitioningHigh Availability

0 likes · 9 min read

Understanding Redis Cluster Architecture: High Availability, Data Partitioning, and Proxy Strategies

Architect's Guide

Oct 10, 2022 · Operations

Common Load Balancing Algorithms and Their Java Implementations

This article introduces fundamental load balancing concepts and examines several static and dynamic algorithms—including round‑robin, weighted, smooth weighted round‑robin, consistent hashing, least‑active, and optimal‑response—providing Java code examples and discussing their advantages, disadvantages, and suitable use cases.

AlgorithmsJavaLoad Balancing

0 likes · 33 min read

Common Load Balancing Algorithms and Their Java Implementations

Architect's Guide

Sep 23, 2022 · Fundamentals

Key Distributed System Design Patterns and Concepts

This article introduces essential distributed system design patterns such as Bloom filters, consistent hashing, quorum, leader‑follower architecture, heartbeat, fencing, write‑ahead logs, segmented logs, high‑water marks, leases, gossip protocol, Phi failure detection, split‑brain handling, checksums, CAP and PACELC theorems, hinted handoff, read repair, and Merkle trees, explaining their purpose and operation.

Bloom FilterCAP theoremLeader Election

0 likes · 13 min read

Key Distributed System Design Patterns and Concepts

IT Architects Alliance

Sep 2, 2022 · Fundamentals

Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More

This article introduces essential distributed‑system concepts—including Bloom filters, consistent hashing, quorum, leader/follower roles, heartbeats, fencing, WAL, segment logs, high‑water marks, leases, gossip protocol, Phi failure detection, CAP and PACELC theorems, hinted handoff, read repair, and Merkle trees—explaining their purpose and how they are applied in systems such as BigTable, Cassandra, Dynamo, and Kafka.

Bloom FilterCAP theoremLeader Election

0 likes · 12 min read

Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More

IT Architects Alliance

Aug 21, 2022 · Backend Development

Consistent Hashing Algorithm: Principles, Java Implementation, and Optimizations for Distributed Cache Load Balancing

This article explains the fundamentals of consistent hashing, its application in load‑balancing distributed caches, analyzes common issues such as data skew and cache avalanche, introduces virtual nodes for uniform distribution, provides Java code examples, and compares it with Redis's HashSlot approach.

JavaLoad Balancingalgorithm

0 likes · 20 min read

Consistent Hashing Algorithm: Principles, Java Implementation, and Optimizations for Distributed Cache Load Balancing

IT Architects Alliance

Jul 14, 2022 · Operations

Common Load Balancing Algorithms and Their Java Implementations

This article reviews common load balancing strategies—including round-robin, random, weighted, smooth weighted round-robin, consistent hashing, least-active and optimal-response algorithms—explains their advantages and drawbacks, and provides complete Java code examples for each method.

AlgorithmsJavaLoad Balancing

0 likes · 33 min read

Architecture Digest

Jul 14, 2022 · Fundamentals

Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More

This article explains essential distributed‑system concepts such as Bloom filters, consistent hashing, quorum, leader/follower roles, heartbeats, fencing, write‑ahead logs, segmented logs, high‑water marks, leases, gossip protocols, Phi accrual failure detection, split‑brain handling, checksums, the CAP and PACELC theorems, hinted handoff, read repair, and Merkle trees, illustrating each with practical examples and diagrams.

Bloom FilterCAP theoremLeader Election

0 likes · 12 min read

Architect

Jul 12, 2022 · Backend Development

Load Balancing Algorithms: Round Robin, Random, Weighted, Smooth Weighted, Consistent Hashing, Least Active and Optimal Response

This article explains common load‑balancing strategies—including basic round‑robin, random, weighted and smooth weighted algorithms, as well as consistent hashing, least‑active and optimal‑response methods—provides Java implementations for each, discusses their advantages, disadvantages, and suitable scenarios, and concludes with practical recommendations.

AlgorithmsJavaLoad Balancing

0 likes · 34 min read

Load Balancing Algorithms: Round Robin, Random, Weighted, Smooth Weighted, Consistent Hashing, Least Active and Optimal Response

Sanyou's Java Diary

Jun 30, 2022 · Databases

Mastering Redis High Availability: Sharding, Consistent Hashing, and Sentinel Explained

This article explains Redis high‑availability strategies, covering basic hash sharding, the advantages of consistent hashing, client‑side versus proxy‑based partitioning, master‑slave replication, and the Sentinel failover mechanism, with diagrams illustrating node addition, removal, and failover decision processes.

DatabaseHigh AvailabilityRedis

0 likes · 10 min read

Mastering Redis High Availability: Sharding, Consistent Hashing, and Sentinel Explained

Code Ape Tech Column

Apr 10, 2022 · Backend Development

Implementing Distributed WebSocket Clusters with Spring Cloud, Consistent Hashing, and Gateway

This article explores practical approaches for building a distributed WebSocket cluster in a Spring Cloud environment, covering session handling, Netty versus Spring WebSocket implementations, session broadcasting, consistent‑hash routing, gateway configuration, Ribbon limitations, and provides code examples for each solution.

JavaSpring CloudWebSocket

0 likes · 17 min read

Implementing Distributed WebSocket Clusters with Spring Cloud, Consistent Hashing, and Gateway

IT Services Circle

Mar 25, 2022 · Fundamentals

Consistent Hashing Algorithm: Principles, Advantages, and Applications

Consistent hashing maps both servers and keys onto a virtual hash ring, allowing keys to be assigned to the nearest clockwise server, which minimizes data movement during node addition or removal, improves load distribution with virtual nodes, and is widely used in distributed caching and load balancing systems.

CacheLoad Balancingconsistent hashing

0 likes · 11 min read

Consistent Hashing Algorithm: Principles, Advantages, and Applications

Tencent Cloud Developer

Mar 14, 2022 · Backend Development

Consistent Hashing Algorithm: Theory, Go Implementation, and Load-Balanced Extension

The article explains consistent hashing—using a circular 2^32 hash ring with virtual nodes to evenly distribute keys across dynamic cache servers—provides a complete Go implementation including host registration, key lookup, and a bounded‑load extension that tracks server load, demonstrates a proxy‑cache setup, and discusses practical testing and production‑grade enhancements.

Load Balancingalgorithmcaching

0 likes · 27 min read

Consistent Hashing Algorithm: Theory, Go Implementation, and Load-Balanced Extension

HelloTech

Feb 21, 2022 · Databases

Database Sharding: Partitioning Strategies, Consistent Hashing, SQL Rewrite, and Merge Engine

Database sharding improves performance by partitioning tables vertically or horizontally and routing rows with consistent hashing, while ShardingJDBC rewrites SQL for physical tables, adds missing columns, corrects pagination, splits batch inserts, and merges results using sorting, grouping, aggregation, and pagination engines.

MERGE EngineSQL Rewriteconsistent hashing

0 likes · 15 min read

Database Sharding: Partitioning Strategies, Consistent Hashing, SQL Rewrite, and Merge Engine

Baidu Geek Talk

Nov 15, 2021 · Backend Development

Baidu Short Video Push System: Architecture Design and Billion-Level Data Optimization Practice

Baidu’s Short Video Push System is a distributed platform serving hundreds of millions of users across multiple apps, delivering personalized, real‑time notifications via a modular architecture that includes material and user centers, recall, preprocessing, and delivery services, while optimizations such as activity‑based scheduling, bitmap‑based user segmentation, consistent‑hash frequency control, and protobuf compression boost click‑through rates, scalability, and resource efficiency.

BaiduProtobufPush Notification

0 likes · 15 min read

Baidu Short Video Push System: Architecture Design and Billion-Level Data Optimization Practice

High Availability Architecture

Oct 26, 2021 · Databases

Practical Guide to Horizontal Database Sharding: Design Principles, Common Schemes, and Expansion Strategies

This article explains the background, design criteria, and practical implementations of horizontal database sharding—including range, hash, gene, routing‑table, and consistent‑hash methods—while discussing common pitfalls, data‑skew mitigation, and both doubling and consistent‑hash expansion techniques for MySQL clusters.

Database ScalingMySQLSharding

0 likes · 24 min read

Practical Guide to Horizontal Database Sharding: Design Principles, Common Schemes, and Expansion Strategies

vivo Internet Technology

Oct 20, 2021 · Databases

Database Sharding Strategies: Common Approaches, Pitfalls, and Best Practices

Effective MySQL sharding requires sustainable, low‑skew designs, favoring hash‑based methods with proper coprime counts, two‑stage partitioning, routing tables, or consistent hashing, while supporting expansion via doubling or flexible consistent‑hash growth to avoid hot spots and uneven data distribution.

Data PartitioningHash ShardingMySQL

0 likes · 23 min read

Database Sharding Strategies: Common Approaches, Pitfalls, and Best Practices

Tencent Cloud Developer

Jun 16, 2021 · Backend Development

Comparison of Four Consistent Hashing Algorithms: Ketama, Rendezvous, Jump Consistent Hash, and Maglev

The article compares four consistent‑hashing algorithms—Ketama’s ring with virtual nodes, Rendezvous’s highest‑random‑weight method, Google’s Jump Consistent Hash, and Maglev’s lookup‑table approach—evaluating their balance, monotonicity, stability, scalability, and time complexity, and concludes that Ketama and Jump offer the best overall trade‑off.

Algorithm ComparisonLoad Balancingconsistent hashing

0 likes · 23 min read

Comparison of Four Consistent Hashing Algorithms: Ketama, Rendezvous, Jump Consistent Hash, and Maglev

Ctrip Technology

May 20, 2021 · Backend Development

Evolution and Architecture of Ctrip's Service Registry (Artemis)

This article reviews the seven‑year evolution of Ctrip's microservice service‑registry from manual data maintenance through an etcd‑based solution to the self‑developed Artemis system, detailing its architecture, consistent‑hash data partitioning, high‑availability design, and second‑level instance up/down mechanisms.

Service Registrycloud nativeconsistent hashing

0 likes · 16 min read

Evolution and Architecture of Ctrip's Service Registry (Artemis)