This article explains how to correctly implement a Redis-based distributed lock in Java, covering essential reliability requirements, step‑by‑step code for acquiring and releasing locks, and detailed analyses of common flawed approaches, ensuring atomicity and proper ownership handling.
This article explains ZooKeeper's distributed coordination architecture, the ZAB consensus protocol, server roles, write and read workflows, FastLeaderElection mechanics, configurable election algorithms, and how ZooKeeper can be used to implement reliable distributed locks and leader election.
This article analyzes a real Alibaba internal financial‑system incident where a one‑cent accounting error arose from concurrent database writes after a distributed‑lock timeout, details the root‑cause investigation, and presents two remediation strategies—adjusting timeout settings and strengthening idempotent controls—to prevent similar issues.
A tiny 0.01‑yuan discrepancy in an Alibaba product revealed duplicate settlement records, exposing a distributed‑lock timeout and concurrency issue that led to double commits, and the article walks through the root‑cause analysis, reverse engineering of the process, and two remediation strategies focusing on timeout adjustments and idempotency controls.
This article explains how to build reliable distributed locks with Redis, covering essential commands, common pitfalls, improvements using GETSET, Lua scripting for atomicity, and complete Java code examples that address deadlock and unlock vulnerabilities.
This article provides a comprehensive overview of ZooKeeper, covering its purpose, design goals, architecture, key features, data flow, components, and common application scenarios such as service naming, configuration management, cluster coordination, distributed locks, and queues.
The article describes how JD Daojia's inventory system serves millions of stores by using health‑monitoring platforms, pre‑allocation policies, idempotent order processing, distributed locks, and rollback mechanisms to ensure stability, prevent overselling, and handle high‑concurrency scenarios such as flash‑sales.
This article explains how to replace Redis‑based lock with Curator's InterProcessMutex, detailing its re‑entrant design, node creation, lock acquisition logic, waiting mechanisms, and release process, while highlighting advantages over traditional Thread.sleep approaches in multithreaded resource access.
The article provides a comprehensive overview of TXSQL, Tencent's heavily customized MySQL kernel, detailing its motivations, version choices, performance improvements such as read‑view and redo‑log optimizations, added functionalities like multi‑mode operation and distributed locks, stability testing, financial‑grade features, benchmark results against official MySQL releases, upcoming support for MySQL 5.7, and future development directions.
This article explores the challenges of mutual exclusion and idempotency in distributed environments, explains the underlying principles of locks in multi‑threaded and multi‑process contexts, and presents practical implementations using Zookeeper, Redis, Tair, and the Cerberus and GTIS frameworks to ensure reliable, scalable operations.
To prevent duplicate operations such as repeated inserts, updates, or message sends in high‑traffic applications, this article explains the concept of idempotency and outlines practical techniques—including read‑only APIs, MVCC with optimistic locking, deduplication tables, distributed locks, safe deletes, unique indexes, UUID‑based request tracking, and state‑machine safeguards.
An in‑depth review of the heated debate between Redis creator antirez and distributed‑systems expert Martin Kleppmann over the safety of Redis’s Redlock algorithm, covering single‑node lock pitfalls, failover issues, timing assumptions, fencing tokens, and practical recommendations for when to use Redlock versus simpler locks.
This article reviews the evolution of distributed locking—from simple MySQL table locks to Redis cache locks and the Redlock algorithm—examines expert criticisms of Redlock’s correctness, presents the Redis author’s rebuttal, and ultimately recommends Zookeeper as a more reliable solution for high‑availability distributed locks.
The article examines how distributed systems face mutual‑exclusion and idempotency challenges, explains traditional thread and process synchronization, then details distributed‑lock techniques (e.g., Zookeeper, Redis, Tair, Cerberus) and global‑ID‑based idempotent services, emphasizing the importance of external storage, fault‑tolerance, and proper lock granularity for reliable high‑throughput applications.
Distributed locks prevent concurrent conflicts over shared resources in distributed systems, and this article explains ZooKeeper’s approach using ordered sequential nodes, illustrating the lock acquisition and release process with command-line examples and a complete Java implementation.
This article introduces the Alicom‑Frame library from Alibaba’s Telecom Billing Refactor project, detailing its modular utilities such as flexible DAO with sharding support, method‑level caching, Diamond‑based configuration tools, distributed locks, and various helper classes, illustrating how they simplify backend development.
This article explains how to build reliable distributed locks using Redis, introduces the official RedLock algorithm, discusses safety properties, compares it with simple failover approaches, and provides implementation details, performance considerations, and lock‑extension techniques.
The discussion explores various backend techniques—SQL conditional updates, scheduled tasks, cache flags, database and Redis locks, queues, and token‑based idempotency—to reliably manage e‑commerce inventory and avoid overselling under different traffic loads.
