This article examines the functional requirements for likes, comments, and favorites in apps and compares MySQL and Redis based database designs, discussing schemas, queries, scalability challenges, and consistency considerations for handling moderate to massive data volumes.
This article explains how loop‑based database queries degrade performance and demonstrates three concrete optimizations—using IN clauses in MySQL, aggregation pipelines in MongoDB, and Redis pipelines—to replace repetitive queries with bulk operations, improving speed and maintainability.
This guide walks you through installing Supervisor on CentOS 7.6, configuring its core settings, creating process definitions for Tomcat and Redis, and using supervisorctl and systemd to start, stop, and monitor these services, ensuring automatic recovery on failure.
This page compiles a chronological list of 100 WeChat articles covering Java interview topics, including core language concepts, data structures, concurrency, Spring, MySQL, Redis, and system design, providing readers with direct links to each issue for comprehensive preparation.
This article compares Memcached and Redis, covering their installation, shared features such as sub‑millisecond latency and language support, and key differences in data structures, persistence, replication, transactions, pub/sub, geospatial commands, scripting, and memory efficiency to help you choose the right cache solution.
This article recounts how Salvatore Sanfilippo, despite a decade of experience in traditional relational databases, abandoned conventional design principles to create Redis, an open‑source in‑memory NoSQL system that now powers major services worldwide.
This article explains how to extend Redis beyond single‑node limits by using partitioning, master‑slave replication, Sentinel for automatic failover, and Redis Cluster with hash slots, detailing their usage, advantages, drawbacks, and configuration examples for building high‑availability and scalable in‑memory data stores.
This article provides an in‑depth guide to Redis, covering its core data types, internal data structures, common usage scenarios, differences from Memcached, key expiration, eviction policies, persistence mechanisms, transactions, event handling, replication, Sentinel, sharding, and a practical forum system example.
Redis is a high‑performance, open‑source key‑value store offering persistence, rich data structures, replication, pub/sub, transactions, and clustering; this guide explains its fundamentals, data types (string, hash, list, set, sorted set), essential commands, and advanced features such as persistence options, replication, Sentinel, and sharding.
This article reviews common unique identifier generation techniques—including database auto‑increment, UUID, Redis counters, Snowflake, Zookeeper, and MongoDB ObjectId—detailing their advantages, drawbacks, and practical implementation examples with C# code snippets.
This guide explores Redis key expiration policies—including active, lazy, and periodic expiration—memory eviction strategies, resource consumption, thread model, and transaction mechanisms, providing practical insights on configuring TTL, optimizing memory usage, and understanding Redis’s single‑threaded architecture for reliable data handling.
This comprehensive guide explains Redis’s architecture, performance advantages, data types, common use cases, persistence options, and scaling strategies, helping developers decide when and how to leverage this high‑speed in‑memory database for caching, session management, and more.
This article explains the complete technical workflow of QR‑code login, covering the generation of UUIDs, Redis storage, browser polling, mobile‑side verification, token handling, and detailed implementations in Taobao and WeChat, while also providing code snippets and diagrams for reference.
This article demonstrates how to integrate Redisson with Spring Boot to create Redis‑based distributed locks, covering Maven dependencies, YAML configuration, a Redisson configuration class, utility methods for locking and unlocking, and a sample controller that simulates concurrent access to verify lock behavior.
This article explains how to configure Redis's maximum memory usage, describes the various eviction strategies such as noeviction, allkeys‑lru, volatile‑lru, and introduces both LRU and LFU algorithms with Java examples and practical configuration commands.
This article analyzes why Redis service nodes may experience massive TimeoutException errors, covering external influences such as CPU and memory contention, network resource exhaustion, and internal Redis usage issues like slow queries, persistence overhead, and configuration pitfalls, and provides concrete diagnostic commands and mitigation steps.
This article explains how Redis uses memory, covering memory fragmentation analysis, object and buffer memory consumption, sub‑process memory overhead, and practical configuration of maxmemory limits and eviction policies to optimize performance and prevent out‑of‑memory failures.
This article explains the concepts, advantages, and drawbacks of MySQL pessimistic and optimistic locks, shows how to implement each with SQL and PHP code, compares their suitability for different traffic patterns, and demonstrates a Redis‑based optimistic lock for high‑concurrency flash‑sale scenarios.
This article explains how to configure Redis's maximum memory usage, describes the various eviction strategies including noeviction, allkeys‑lru, volatile‑lru, random and ttl policies, shows how to query and set these policies via configuration files or commands, and provides Java code for a simple LRU cache while discussing Redis's approximate LRU and LFU algorithms.
Static business data in microservice systems, such as vehicle models and user profiles, change rarely yet demand high accuracy and real‑time access; this article proposes a universal caching architecture using a business service, persistent queue, Redis cache, and consistency checks to achieve scalable, reliable reads.
This tutorial walks through compiling the php‑redis extension, installing Laravel, configuring Redis as a cache and database driver, setting up a Redis cluster, and provides sample PHP code for read/write operations, offering a comprehensive guide for backend developers.
This article details the background, initial ECS‑based deployment, performance bottlenecks during rapid user growth, and the comprehensive cloud‑native migration—including DNS load balancing, managed Kubernetes, CDN acceleration, RDS/Redis replacement, and NAS/OSS storage—resulting in significant scalability and operational improvements for the Smart Citizen Pass mini‑program.
This guide walks through preparing three CentOS 7 servers, installing Redis 6.0.3, configuring master‑slave replication, handling common compilation errors, setting up system startup, adjusting firewall and Redis settings, and finally enabling Sentinel for high‑availability monitoring.
The article explains Reddit's large‑scale page‑view counting system, detailing its real‑time requirements, the challenges of naive hash‑set storage, and how a hybrid approach using linear probability and HyperLogLog algorithms together with Kafka, Redis, and Cassandra achieves accurate, low‑memory, near‑real‑time analytics.
This article explains the end‑to‑end implementation of QR‑code login, covering how a web page requests a QR image, how the server stores a UUID in Redis, how a mobile app scans the code and validates the user, and how the browser finally receives a token to complete authentication.
During a full‑chain load test, latency spikes were traced to a slow G1GC pause caused by single‑threaded reference processing of many Finalizer objects, which originated from an over‑aggressive Jedis connection pool; enabling the JVM flag -XX:+ParallelRefProcEnabled eliminated the bottleneck and restored performance.
This article explains how a large car‑IoT platform built a comprehensive Redis monitoring solution using Elastic‑Stack, covering server‑side metrics, application‑side instrumentation, joint analysis, implementation details, findings, and future optimization recommendations.
This article explores multiple backend strategies for implementing a location‑based “nearby users” service, covering pure MySQL queries, MySQL combined with GeoHash, Redis Geo commands, and MongoDB geospatial indexes, explaining design principles, pros and cons, and providing complete code examples for each approach.
This article explains the QR code login process, detailing how a web page requests a QR code, how the mobile app scans it, exchanges tokens via Redis, and ultimately authenticates the user across web and mobile platforms.
This article details CTrip's evolution of Redis management—from early single‑instance deployments and custom CRedis client, through automated scaling, containerization with Kubernetes, secondary scheduling algorithms, Intel Optane integration, and hybrid‑cloud deployment—highlighting operational challenges, solutions, and performance outcomes.
This article provides a comprehensive tutorial on Redis Cluster, covering its architecture, data partitioning and redundancy, step‑by‑step instructions for downloading, compiling, and installing Redis on CentOS, as well as detailed procedures for manually or automatically creating a six‑node cluster with master‑slave replication and slot allocation.
This article explains Redis's two persistence mechanisms—RDB snapshot files and AOF append‑only logs—including their operation, configuration commands, advantages, disadvantages, recovery procedures, and performance recommendations for choosing between them.
Redis 6.0.0 GA, the biggest release to date, adds a redesigned client cache, ACL improvements, faster RDB loading, a new STRALGO command, and optional multithreaded I/O that can double network performance, while urging careful testing before production use.
The author reflects on recent campus recruitment interviews, sharing personal anecdotes, common pitfalls in Java fundamentals, collections, concurrency, and Redis, and offers practical advice on how candidates can improve their technical depth and interview performance.
This comprehensive guide explains what Redis is, its advantages and drawbacks, why it excels as a high‑performance cache, the supported data structures, persistence mechanisms, memory eviction policies, threading model, transaction handling, clustering and sharding options, distributed locking, common cache pitfalls, and useful tooling for Java developers.
Redis 6.0.0 stable release brings major updates such as redesigned client‑side caching, immediate RDB deletion for replication, enhanced ACL logging, faster PSYNC2 partial resynchronization, decimal timeout support, up to 30% faster RDB loading, and a new STRALGO command for string algorithms.
This article explores various strategies for controlling execution timing in Java backend services, comparing Thread.sleep, Timer, and Redis-based expiration techniques, and provides practical code examples and configuration steps for integrating Redis with Spring Boot to achieve reliable delayed processing.
This article explains the technical principles and step‑by‑step implementation of QR code login used by major platforms like WeChat and Taobao, covering server‑side UUID generation, Redis storage, token exchange, client polling, JSONP handling, and concrete code examples.
This guide presents ten practical Redis best‑practice tips—including avoiding KEYS *, using SCAN, analyzing command stats, leveraging hashes, setting expirations, choosing eviction policies, handling errors, scaling with clusters, understanding threading limits, and configuring Sentinel for high availability—to help you run Redis efficiently and safely.
This article explains Ctrip's high‑availability designs for SQL Server, MySQL, and Redis, describing multi‑replica strategies, evolution from legacy mirroring to AlwaysOn, multi‑node MHA management, and Redis sentinel‑based failover, while emphasizing fault‑tolerance across data centers.
This article introduces Redis as an open‑source in‑memory data‑structure store, explains its role as a NoSQL database, covers fundamental data types, common commands, expiration handling, and advanced features like pipelines and transactions, providing a comprehensive guide for developers.
This article explains what Redis Cluster is, how it partitions data and provides redundancy, and walks through installing Redis on CentOS, configuring multiple nodes, and creating a functional cluster using both manual commands and the built‑in cluster management tool.
This article examines common failure scenarios of Redis‑based distributed locks, compares a simple lock implementation with the Redlock algorithm, and provides practical solutions for single‑point failures, lock expiration issues, clock drift, and high‑concurrency pitfalls.
This article walks through seven practical Laravel techniques—including view composers for reusable sidebars, route naming for maintainable URLs, dynamic key‑value settings, concise database query shortcuts, polymorphic relationships, caching best practices, and separating Redis connections—to help developers write cleaner, more scalable backend code.
This article explains the three Redis expiration‑key deletion strategies—timed, lazy, and periodic—their advantages and disadvantages, how Redis implements lazy and periodic deletion, and how persistence mechanisms such as RDB, AOF, and replication handle expired keys.
This tutorial explains Redis bitmap operations, covering SETBIT, GETBIT, BITCOUNT, and BITOP commands, their syntax, underlying SDS structure, time‑complexity analysis, memory‑size calculations, and practical scenarios such as user sign‑in tracking and online‑user statistics.
Learn how to dramatically boost Redis speed by shortening key/value sizes, enabling lazy free, setting expirations, disabling costly commands, using slowlog, pipelines, avoiding mass expirations, optimizing clients, limiting memory, running on physical servers, tweaking persistence, disabling THP, and adopting distributed architectures.
This guide walks you through configuring Kibana visualizations, customizing Nginx and Apache logs in JSON, setting up Logstash pipelines, integrating Redis as a buffering queue, and deploying a production-ready ELK stack for efficient log management and analysis.
This article explains how to implement automatic idempotency for Spring Boot APIs using Redis, a custom @AutoIdempotent annotation, token generation and verification, and an interceptor, providing step‑by‑step code examples and a testing workflow to prevent duplicate operations.
This article explains how Redis implements two persistence mechanisms—RDB snapshots and AOF logs—covering their triggers, execution flows, advantages, drawbacks, differences, restart recovery procedures, and practical ways to mitigate performance overhead caused by fork operations.
This article explains the design of Redis Cluster, the challenges of migrating clients, and how the Camellia-Redis-Proxy middleware—built with Netty—provides transparent proxying, sharding, dual‑write, plugin support, and performance optimizations such as multithreading, async I/O, pipelining, and robust error handling.
This guide explains how to install Redis clients, configure single and clustered connections, customize Predis and PhpRedis options, and use Laravel's Redis facade for basic commands, pipelining, multiple connections, and publish/subscribe messaging, all with clear code examples.
This article explains how to build a highly available Redis service by analyzing failure scenarios, comparing single‑instance, master‑slave with one or multiple Sentinel processes, and finally presenting a three‑Sentinel architecture that ensures continuous service despite node or network outages.
This article explains the principles, design considerations, and code implementation of Redisson's distributed lock, covering mutual exclusion, deadlock prevention, performance, reentrancy, watchdog auto‑extension, Lua scripting, and potential pitfalls in Redis sentinel setups.
This article explains how to implement automatic API idempotency in Spring Boot using Redis for token storage, custom annotations, and interceptor configuration, covering token generation, validation, Redis service utilities, and testing with Postman to prevent duplicate operations and ensure data consistency.
This tutorial walks through pulling the Redis Docker image, creating configuration files, running the container, connecting with redis-cli, testing commands, enabling persistence, and installing a visual management tool, providing complete step‑by‑step instructions for Docker‑based Redis deployment.
Learn how to dramatically improve Redis performance by shortening key-value sizes, enabling lazy free, setting expirations, disabling costly commands, using slowlog, leveraging pipeline, preventing mass expirations, optimizing client connections, limiting memory, running on physical servers, configuring persistence, disabling THP, and adopting distributed architectures.
This article explains why Redis performance matters for high‑traffic services and provides a comprehensive set of practical optimizations—including network latency reduction, command pipelining, avoiding slow commands, tuning persistence, OS/hardware settings, and scaling with sharding—to help you keep Redis fast and reliable.
This guide walks you through setting up a six-node Redis cluster using Docker Compose, configuring the necessary redis.conf settings, deploying the containers, initializing the cluster, and then integrating the cluster into a SpringBoot application via appropriate application.yml configurations and connection commands.
This article explains how to design and implement a Redis‑driven, second‑level scheduled‑task cluster that reliably pushes millions of coupon notifications in real time, addressing latency, throughput, and single‑point‑failure challenges.
This article explains why cache penetration occurs in high‑dimensional data scenarios, introduces Bloom Filters as a solution, outlines suitable use cases such as database lookups, cache outages, web request filtering, malicious URL detection and Bitcoin sync, and details practical Redis‑based implementations, advantages, drawbacks, and advanced counting filter techniques.
This article explains Redis's memory model by describing how to query memory usage, the roles of used_memory, used_memory_rss, mem_fragmentation_ratio, and mem_allocator, and then dives into the internal structures such as redisObject, SDS, jemalloc, and the encoding strategies for strings, lists, hashes, sets, and sorted sets.
This article provides a comprehensive guide to Redis, covering atomic transactions, command pipelining, publish/subscribe messaging, data replication, high‑availability with Sentinel, and the distributed architecture of Redis Cluster, complete with code examples and configuration steps.
This guide explains how to use Zabbix's auto‑discovery feature to automatically find Redis instances on a server, create shell or Python scripts for port detection, configure Zabbix agent keys, set up server‑side templates, discovery rules, item prototypes, graphs, and triggers, and finally apply the template to monitored hosts.
This article explores the design of a high‑performance short‑link system, covering its benefits, redirection mechanics, hash‑based and auto‑increment generation methods, database schema, Bloom filter optimization, and a scalable OpenResty‑based architecture for handling massive traffic.
This article presents ten practical Redis best‑practice guidelines—from avoiding the costly KEYS * command and leveraging SCAN, to using INFO for command statistics, employing hashes, setting expirations, selecting eviction policies, handling errors, scaling with clusters, understanding threading limits, and configuring Sentinel for high availability.
Learn how to resolve performance bottlenecks in a Spring‑based mall project by caching user and permission data in Redis, adding cache logic with RedisTemplate, and using AOP to gracefully handle Redis failures, ensuring stable authentication even when the cache is unavailable.
This article walks through the evolution of a Redis‑based cache layer for multi‑data‑center deployments, addressing consistency, safety, performance, disk‑space, data loops, timestamp versioning, master‑slave failover, and global numeric aggregation, and culminates in a ready‑to‑use middleware solution.
This article explains the internal implementations of Redis’s five major data structures—simple dynamic strings (SDS), linked lists, dictionaries, skiplists, integer sets, and ziplists—detailing their definitions, memory layouts, key characteristics, and how Redis leverages them for high‑performance storage and retrieval.
This comprehensive guide walks you through installing Redis on Linux and Windows, configuring Spring Cache annotations, setting up JSON serialization with RedisTemplate, using connection pools, and implementing a flexible RedisService with controller examples, providing all the essential steps to integrate Redis into your Spring Boot applications.
The article reviews a Tencent Cloud TVP closed‑door forum where experts compared MySQL 8.0, PostgreSQL, Redis and the cloud‑native CynosDB, highlighting each product’s technical strengths, ecosystem support, and the broader industry trend toward cloud‑native, multi‑database solutions as the future of data management.
The Redis website experienced an unexpected outage caused by an OOM error due to insufficient memory on a low‑cost DigitalOcean droplet, and the maintainer quickly fixed it by upgrading the instance and limiting allkeys‑lru usage, revealing surprising details about the site’s infrastructure.
On March 12 the Redis website experienced an unusual outage caused by an out‑of‑memory error from a Try‑Redis session leak on a low‑cost DigitalOcean droplet, prompting a rapid upgrade and configuration changes to restore service.
The article explains Redis's custom Simple Dynamic String (SDS) implementation, its memory layout, dynamic resizing rules, and performance benefits such as O(1) length retrieval, buffer‑overflow protection, and reduced allocation overhead through pre‑allocation and lazy reclamation.
This article examines common failures of Redis‑based distributed locks, explains the limitations of simple implementations, introduces the Redlock algorithm, and provides practical solutions for high‑concurrency, node failures, TTL overruns, and system clock drift.
This article explains how to implement automatic API idempotency in Spring Boot by using Redis for token storage, a custom @AutoIdempotent annotation, and a request interceptor, providing code examples and test steps to ensure duplicate requests are rejected.
This article details the design, installation, and modular integration of Flume, Kafka, Storm, Drools, and Redis to build a real‑time log analysis pipeline for ETL systems, discussing architecture, configuration, code examples, and practical considerations for scalability and fault tolerance.
This article details the architectural redesign, fault‑tolerance mechanisms, performance optimizations, and monitoring strategies employed in JD.com’s PC homepage, illustrating how backend technologies such as OpenResty, Lua, Redis, and NGINX are orchestrated to achieve high availability and sub‑30 ms page loads.
Learn how to ensure API idempotency in Spring Boot applications by leveraging Redis for token management, creating a custom @AutoIdempotent annotation, configuring interceptors, and handling token creation and validation to prevent duplicate submissions and maintain data integrity.
This article presents ten practical Redis best‑practice tips—from avoiding the costly KEYS * command to using hashes, setting appropriate expiration, choosing the right eviction policy, and ensuring high availability—helping developers optimize performance and reliability of their in‑memory data stores.
This article explores Redis, a high‑performance in‑memory key‑value store, detailing its core data types—String, List, Hash, Set, ZSet—the underlying structures such as SDS, quicklist, hashtable, and intset, and demonstrates practical usage patterns like caching, rate limiting, and inventory control.
This article explains the LRU caching principle, compares naive O(n) implementations, and shows how to achieve true O(1) insert and eviction using a HashMap combined with a doubly linked list, including practical Java code and an overview of Redis's approximate LRU algorithm.
Redis employs distinct memory reclamation mechanisms—expiration policies (timed, lazy, periodic) and eviction strategies triggered when maxmemory is reached—each with trade-offs in CPU and memory usage, and offers configurable policies such as allkeys‑lru, volatile‑ttl, and noeviction to manage cache data effectively.
This guide explains how to install Redis, configure it within a Spring Boot application, define custom Redis helper interfaces and implementations, and demonstrates testing and practical usage of caching annotations for efficient data retrieval.
This article explains the technical workflow of QR code login, covering the generation of UUIDs, QR images, server‑side Redis storage, mobile‑side token verification, long‑polling mechanisms, and the concrete implementations used by WeChat and Taobao, providing a complete reference for developers building similar authentication features.
Learn how to compile Redis from source and install it on an ARM-based system running Euler OS 2.8, covering environment setup, dependency building, configuration, service startup, and basic testing with redis-cli, demonstrating that the process mirrors standard installations.
This article walks through a complete performance‑testing setup for a VIP purchase callback API, detailing the request flow, distributed‑lock handling with Redis, parameter generation using AtomicInteger, Java implementation, and pitfalls to ensure accurate, high‑concurrency testing.
This article explains how to implement a Redis-based distributed lock using Jedis in Java, covering lock creation with SETNX, lock expiration, safe lock release via Lua scripts, and demonstrates the approach by simulating a 100,000-user concurrent order‑grabbing scenario.
This article explains common delayed‑queue scenarios, demonstrates how to implement a delay queue using Redis Zset with atomic Lua scripts, and shows how to deploy and use Beanstalkd—including Java client setup and sample producer/consumer code—while offering extensions and best‑practice tips.
This article explains the technical principles behind QR code login, detailing the client‑server interaction, UUID generation, Redis storage, long‑polling, and token handling, and illustrates the implementation with real‑world examples from Taobao and WeChat, including code snippets and flow diagrams.
This article explores the challenges of massive ticket‑buying spikes during holidays, explains the multi‑layer load‑balancing architecture, presents Go and Nginx configurations for weighted routing, demonstrates Redis‑based pre‑deduction of stock with Lua scripts, and shares stress‑test results showing thousands of requests per second on a single node.
This article explains the technical principles behind QR‑code login, detailing the end‑to‑end workflow between browsers, mobile apps and servers, and provides concrete implementations from Taobao and WeChat, including code snippets, polling mechanisms, Redis usage, and error handling.
This article explains how to build a simple two‑level caching solution in Java, covering generic cache interfaces, FIFO/LRU/LFU algorithms, implementing local Guava cache and distributed Redis cache, configuring Spring Boot, handling expiration, and providing a unified cache builder for seamless use.
This article provides an in‑depth overview of Redis, covering why it is used for performance and concurrency, its single‑threaded architecture, core data structures and their scenarios, expiration policies, memory eviction strategies, consistency challenges, and practical solutions for cache penetration, snowballing, and concurrent key updates.
This article explains the step‑by‑step process Redis follows to launch, from executing the redis‑server binary, initializing the server struct, loading configuration files, setting up data structures, restoring persistence, to entering the event loop.
During a performance test a query API failed on the second request because the Redis cache was written before asynchronous tasks finished, causing missing fields; the article explains the root cause, shows the original and fixed code, and details the debugging process.
This article explains why a Redis instance creates 16 default databases, how they function as simple namespaces rather than separate applications, how to configure their number, and why Redis clusters support only a single database.
This article details how JD.com’s engineering team designed, implemented, and optimized a user‑generated‑content platform that went from concept to production in 60 days, covering project background, system architecture, data storage with JimDB, messaging decoupling, asynchronous I/O, performance testing, and future improvements.
This article provides a comprehensive introduction to Redis, covering its key features, supported data structures, core commands, persistence mechanisms, replication, sentinel monitoring, sharding strategies, and transaction handling with practical code examples.
This guide provides a comprehensive walkthrough of Redis configuration options, covering memory unit notation, include templates, module loading, security settings, networking, persistence mechanisms, replication, clustering, Docker deployment, monitoring, and advanced memory and performance tuning.
