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Distributed Locks

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Zhuanzhuan Tech
Zhuanzhuan Tech
Jun 4, 2025 · Backend Development

A Comprehensive Guide to Redisson Distributed Locks in Java

This article explains Redisson's various distributed lock mechanisms—including watchdog, reentrant lock, multi‑lock, read‑write lock, semaphore, RedLock, and CountDownLatch—detailing their principles, usage patterns, code examples, and best‑practice recommendations for robust backend concurrency control.

Distributed LocksJavaRedis
0 likes · 16 min read
A Comprehensive Guide to Redisson Distributed Locks in Java
Architect
Architect
Jan 16, 2023 · Databases

Redis Fundamentals: Pipelines, Pub/Sub, Expiration, Transactions, Persistence, Distributed Locks and Clustering

This article provides a comprehensive overview of Redis, covering basic concepts, pipeline optimization, publish/subscribe messaging, key expiration strategies, transaction behavior, persistence mechanisms (RDB, AOF, hybrid), distributed locking techniques, Redisson and Redlock algorithms, as well as high‑availability setups using replication, Sentinel and Cluster modes.

ClusteringDistributed LocksPersistence
0 likes · 32 min read
Redis Fundamentals: Pipelines, Pub/Sub, Expiration, Transactions, Persistence, Distributed Locks and Clustering
Code Ape Tech Column
Code Ape Tech Column
Dec 29, 2021 · Backend Development

Comprehensive Interview Questions and Answers on Backend Development Topics

This article presents a collection of interview questions covering backend fundamentals such as linked‑list sorting, encryption differences, TCP reliability, IO models, Hystrix, delayed tasks, HTTPS flow, transaction isolation, index pitfalls, virtual memory, Redis leaderboards, distributed locks, zero‑copy techniques, Java synchronized, and Snowflake ID generation.

Distributed LocksEncryptionHystrix
0 likes · 30 min read
Comprehensive Interview Questions and Answers on Backend Development Topics
High Availability Architecture
High Availability Architecture
Oct 16, 2021 · Backend Development

Ensuring Data Consistency Between MySQL and Redis: Strategies for Single‑Threaded and Multi‑Threaded Scenarios

This article explains what data consistency means for MySQL and Redis, analyzes inconsistency cases in both single‑threaded and concurrent environments, and proposes practical strategies—including read‑only and read‑write cache handling, message‑queue retries, binlog subscription, delayed double‑delete, and distributed locking—to achieve eventual or strong consistency.

Distributed LocksMessage QueueMySQL
0 likes · 16 min read
Ensuring Data Consistency Between MySQL and Redis: Strategies for Single‑Threaded and Multi‑Threaded Scenarios
Efficient Ops
Efficient Ops
May 2, 2017 · Big Data

Mastering ZooKeeper: Core Concepts and Real-World Big Data Applications

This article introduces ZooKeeper’s fundamental architecture, explains its key concepts such as cluster roles, sessions, ZNodes, watches, and ACLs, and then details how it powers essential distributed coordination tasks—including configuration management, naming services, master election, and distributed locks—in large‑scale Hadoop and HBase ecosystems.

Big DataDistributed CoordinationDistributed Locks
0 likes · 25 min read
Mastering ZooKeeper: Core Concepts and Real-World Big Data Applications
Qunar Tech Salon
Qunar Tech Salon
Dec 30, 2014 · Fundamentals

Learning ZooKeeper with Curator: Comprehensive Examples and Recipes

This guide offers a complete collection of practical examples that demonstrate Curator's usage for Apache ZooKeeper, covering leader election, distributed locks, barriers, counters, caches, queues, and transaction handling, with each chapter independent and source code available on GitHub.

CuratorDistributed CoordinationDistributed Locks
0 likes · 3 min read
Learning ZooKeeper with Curator: Comprehensive Examples and Recipes