This article dissects the architecture of a 12306‑style ticket‑spiking service, explaining load‑balancing strategies, weighted Nginx routing, local and remote stock deduction using Go and Redis, and demonstrates performance testing that achieves thousands of requests per second while preventing oversell and undersell.
Echo is a full‑stack open‑source Java community system built with Spring Boot, MyBatis, MySQL, Redis, Kafka and Elasticsearch, offering modules like posts, comments and notifications, and the article provides its core tech stack, development environment, local setup steps, deployment architecture, demo screenshots and source code access.
This article details a comprehensive performance testing workflow—including requirement analysis, script recording with BlazeMeter, data construction, iterative optimization, and final results—targeting a web application that must handle over 5,000 TPS with 2 million database records, highlighting bottlenecks in Redis, MySQL, and code logic.
This article explains the need for distributed locks in multi‑node systems, describes their core characteristics, and compares popular implementation approaches such as database‑based optimistic and pessimistic locks, Redis atomic locks, and ZooKeeper sequential node locks, highlighting their principles and trade‑offs.
This article examines Redis List interview topics, covering FIFO misconceptions, underlying encodings across versions, ZIPLIST compression mechanics, backward traversal, and the time complexities of node count queries for both ZIPLIST and LINKEDLIST implementations.
Redis version 7.0.10 has been released, addressing a critical security vulnerability (CVE‑2023‑28425) in the MSETNX command, fixing several bugs including memory‑usage issues with large stream nodes and client reply handling, and providing updated release notes on GitHub.
This article explains how Redisson implements distributed locks on Redis, covering basic concepts, a simple lock with Lua scripts, reentrancy handling, automatic lock renewal via WatchDog, and the advanced fair lock mechanism that ensures FIFO ordering using Redis lists and sorted sets.
This article provides a comprehensive overview of rate limiting, covering basic concepts, common algorithms such as token bucket, leaky bucket, and sliding window, and practical implementation methods across Nginx, Tomcat, Guava, Redis, and Sentinel for distributed backend systems.
This article presents a comprehensive Netty TCP demo project, covering its architecture, module layout, business flow, detailed Java code for message queuing, client execution, handler implementation, testing endpoints, and deployment considerations, providing a practical learning resource for backend developers.
This article explains how to handle 2 GB video uploads by splitting files into chunks, using breakpoint resume and instant transfer techniques, and leveraging Java's RandomAccessFile together with Spring Boot and Redis to manage upload state, merge chunks, and store the final file.
This article explores various distributed ID generation strategies—including UUID, database auto‑increment, segment mode, Redis INCR, Snowflake, Meituan Leaf, Baidu UidGenerator, and Didi TinyID—detailing their principles, advantages, drawbacks, and Java code examples to help developers choose the right solution for high‑scale systems.
This article explains Redis's in‑memory database persistence mechanisms—including RDB snapshots and AOF logging—detailing configuration, automatic and manual triggers, advantages and drawbacks, as well as Redis transaction commands and pipeline usage, providing practical code examples to help developers master data durability and performance.
The article explains why distributed systems need globally unique identifiers, outlines strict generation rules and availability requirements, compares common approaches such as UUID, database auto‑increment and Redis, and provides a detailed overview and Java implementation of Twitter's Snowflake algorithm.
This article explains three Redis‑based rate‑limiting techniques—using SETNX, sorted sets, and a token‑bucket with lists—providing code examples, discussing their advantages and drawbacks, and showing how to integrate them into Java Spring applications to protect high‑concurrency services.
This article explores Redis’s evolution from its 2009 inception, outlines major version releases, examines its in‑memory design, efficient data structures, encoding schemes, single‑threaded event loop with epoll, and benchmark results, illustrating why Redis achieves exceptionally high throughput and low latency in real‑world deployments.
This article details the architecture, component‑based design, dynamic template generation, batch processing, activity management, and technical challenges such as custom component rendering, condition‑expression creation, and high‑concurrency coupon issuance for a scalable e‑commerce coupon platform.
This article outlines sixteen practical Redis usage scenarios—including caching, distributed sessions, locks, ID generation, counters, rate limiting, bitmaps, shopping carts, timelines, message queues, lotteries, likes, tags, filtering, follow relationships, and leaderboards—explaining each concept and providing example code snippets for implementation.
The article explains Redis master‑slave asynchronous replication, describes how repeated full‑sync requests from slaves can cause a replication storm that overloads CPU, memory and network, and offers practical solutions such as limiting data size, adjusting buffer limits, and redesigning deployment topology.
This article explains two technical solutions for keeping MySQL data in sync with Redis cache—using a MySQL trigger with a UDF function and parsing MySQL binlog events—while also reviewing the Canal open‑source tool and discussing their trade‑offs and implementation details.
This article explains the concepts of cache penetration, cache breakdown (stampede), and cache avalanche in Redis, and provides practical solutions such as parameter validation, null‑value caching, Bloom filters, mutex locks, hot‑data non‑expiration, and randomizing expiration times, accompanied by Java code examples.
This article introduces KeyDB, a high‑performance Redis fork that adds multithreading, a redesigned thread model, a spin‑lock fastlock mechanism, and active‑replica capabilities, while remaining fully compatible with Redis protocols and offering up to double the throughput on the same hardware.
The article presents a detailed guide on designing and implementing fine-grained permission control for microservices using Apache Shiro, Spring Boot, Dubbo, and Redis to share session data across services, including code examples, configuration steps, and testing of role‑based access.
This article explains how Redis ensures data durability by using two persistence strategies—Append Only File (AOF) and Redis Database (RDB) snapshots—detailing their operation, configuration options, trade‑offs, rewrite processes, and how they handle expired keys and recovery.
This article shares a practical, seven‑step methodology for tackling large open‑source projects like Redis, covering project mapping, prerequisite knowledge, starting with core modules, following the main execution path, handling complex functions, branching into secondary features, and finally filling knowledge gaps.
This article explains Redis's compressed list structures—ZIPLIST and its successor LISTPACK—detailing their layouts, encoding schemes, query and update complexities, and how LISTPACK resolves ZIPLIST's chain‑update performance issues to provide a more memory‑efficient list implementation.
This article provides a comprehensive guide to Redis Cluster, covering its sharding mechanism, hash slot mapping, replication and automatic failover, client data location, slot reassignment, MOVED/ASK redirection, communication overhead, and practical tuning tips for large‑scale deployments.
The article explains the classic cache consistency problem between MySQL and Redis, analyzes how inconsistencies arise, and details four cache‑update design patterns—delete‑then‑update, cache‑aside, read/write‑through, and write‑behind—highlighting their workflows, advantages, and drawbacks.
This article presents sixteen typical Redis use cases—including caching, distributed locks, global IDs, counters, rate limiting, bitmaps, shopping carts, timelines, message queues, lotteries, likes, product tags, filtering, follow relationships, and ranking—each explained with practical code snippets and command examples.
This tutorial explains how to achieve exactly‑once semantics when streaming data from Kafka to Redis using Apache Flink's TwoPhaseCommitSinkFunction, covering Redis transaction basics, utility classes, sink implementation, testing steps, and solutions to common connection and transaction bugs.
Redis uses key expiration commands, periodic scanning, and a combination of lazy and active deletion strategies, and when memory is full it applies one of eight eviction policies—including refined LRU and LFU algorithms with sampling and decay mechanisms—to decide which keys to discard.
This article introduces Redis List as a linked collection of strings, explains its size limits, common CRUD commands, read operations, and dives into the underlying encodings—ZIPLIST, LINKEDLIST, and the hybrid QUICKLIST—highlighting when each is used.
This article explains the concepts of Redis cache avalanche, penetration, and breakdown, illustrates real‑world incidents, and provides pre‑, during‑, and post‑failure strategies such as high‑availability setups, local caches with rate limiting, and defensive caching of empty values.
This article provides a comprehensive overview of Redis, covering why it is used as a cache, its single‑threaded efficiency, multithreading in version 6.0, common data structures and their use cases, pipeline advantages, persistence mechanisms, transactions, Bloom filter for massive URL checks, internal data organization, and incremental rehashing.
This article provides a comprehensive overview of Redis as a NoSQL in‑memory database, covering its core data structures, special types, transaction model, RDB and AOF persistence, publish/subscribe, master‑slave replication, Sentinel failover, and common cache pitfalls such as penetration, breakdown and avalanche, with practical mitigation strategies.
This article surveys eleven Java techniques for delayed task execution—including DelayQueue, Timer, ScheduledThreadPoolExecutor, RocketMQ, RabbitMQ, Redis key‑expiration, Redisson, Netty, Hutool, Quartz and simple polling—explaining their core principles, code examples, and when each approach is appropriate.
This article surveys eleven practical techniques for implementing delayed tasks in Java, covering JDK utilities like DelayQueue, Timer, and ScheduledThreadPoolExecutor, as well as message‑queue solutions such as RocketMQ, RabbitMQ, Redis key‑expiration, Redisson, Netty, Hutool, Quartz, and simple polling, with code demos and implementation principles.
This article provides a comprehensive overview of Redis, covering its role as an in‑memory data‑structure server, various deployment topologies such as single instances, high‑availability, Sentinel, replication, and clustering, as well as its persistence mechanisms including RDB, AOF, and fork‑based snapshots.
KeyDB is a high‑performance, multithreaded fork of Redis that retains full protocol compatibility while offering double the query throughput, reduced latency, and features like Active‑Replication, fastlock spin‑locks, and advanced client‑connection management, making it a compelling drop‑in replacement for Redis deployments.
This article explains Redis's three persistence options—Append‑Only File (AOF), Redis DataBase snapshots (RDB), and the hybrid mode—detailing their inner workings, configuration strategies, performance trade‑offs, and how to choose the most reliable solution for a given workload.
This article reviews essential Redis string concepts, covering typical interview questions, encoding types, the EMBSTR threshold, SDS structure, and memory allocation details to help readers solidify their understanding of Redis string implementation.
This article explains three practical Redis‑based rate‑limiting methods—using SETNX, ZSET sliding windows, and a token‑bucket algorithm with List—complete with Java code examples and a discussion of their advantages and drawbacks.
This article presents a comprehensive backend architecture for flash‑sale systems, covering Nginx static‑dynamic separation, Redis‑based rate limiting and distributed locks, MQ buffering, database sharding, safety protections, page optimization, and detailed Nginx configuration examples to handle massive concurrent traffic.
This article explains Redis eviction policies such as allkeys‑lru, volatile‑ttl, and others, discusses how the eviction process works, and provides practical solutions for cache penetration, breakdown (stampede), and avalanche, including Bloom filters, mutex locks, and randomized TTLs.
This article explains how to design an effective multi-level caching system in a microservice environment, covering client‑side browser caching, application‑layer CDN and Nginx caching, and service‑layer in‑process and distributed caches, along with consistency strategies and practical deployment examples.
This tutorial walks through the evolution from manual Redis calls to Spring Cache abstraction, explains AOP‑based proxying, details core annotations, demonstrates Caffeine and Redisson integration, explores list caching, and shows how to build a custom two‑level cache for high‑performance Java back‑ends.
This tutorial explains how to implement a like/unlike feature using Spring Boot, Redis caching, and periodic persistence to a database with Quartz, covering data modeling, key design, service layers, controller APIs, and scheduled synchronization.
This guide walks developers through transforming a single‑node Redis cache into a stable, high‑performance cluster by explaining data persistence options (RDB, AOF, hybrid), master‑slave replication, Sentinel‑driven automatic failover, and both client‑side and proxy‑based sharding for horizontal scalability.
This article explains why the Lettuce asynchronous Redis client, built on Netty, outperforms the traditional Jedis client for high‑concurrency caching, covering Redis client differences, Netty NIO fundamentals, Redis Cluster architecture, smart client redirection handling, and practical Java code examples.
This article compares two Redis‑based delayed‑queue approaches—listening to key‑space expiration events and using Redisson’s built‑in delayed queue—detailing their principles, Spring Boot demos, pitfalls, and why Redisson offers a more reliable solution for distributed applications.
This article explains the complete user login process, including mobile verification, token generation, token expiration policies, request‑rate limiting with Redis, anonymous request handling, blacklist management, and provides full Java Spring code examples for implementing these backend authentication mechanisms.
This article walks through installing Docker and Docker‑Compose, creating a project directory, writing a docker‑compose.yml that defines Redis, MySQL, Nginx, Java, and a file‑preview service, configuring each container, and using docker‑compose commands to build, start, monitor, and manage the full SpringBoot‑Vue application stack.
Tencent’s QQ reminder subscription push system combines push‑pull prefetching, heterogeneous MySQL/Redis storage, delayed‑queue triggers, Redis‑based rate‑limiting, task scattering, message‑queue decoupling, at‑least‑once delivery, and dual‑replica disaster recovery within a dispatcher‑worker architecture to ensure reliable, controllable, low‑latency mass notifications.
This article explains why Redis is essential for flash‑sale (秒杀) systems, detailing the load characteristics, the three sale phases, stock‑checking and decrement strategies, atomic operations, distributed locks, data modeling, and practical deployment recommendations for high‑concurrency back‑end services.
This article explains Redis's Append‑Only File (AOF) rewrite mechanism, detailing how the rewrite buffer is defined, the fork‑based background process, inter‑process pipe communication, and the advantages and drawbacks of AOF rewriting, accompanied by relevant source code snippets.
This article explains Redis's internal memory architecture, details the various memory components such as used_memory, object memory, client buffers, and fragmentation, and provides practical optimization techniques and real‑world case studies to reduce memory usage and improve performance.
This article explains the three main Redis cache anomalies—cache avalanche, cache penetration, and cache breakdown—detailing their symptoms, root causes, and practical mitigation strategies with Java code examples and architectural recommendations.
This article explains various methods to monitor Redis key changes—including using the MONITOR command, configuring keyspace event notifications, and parsing AOF files with optional timestamps—detailing their setup, advantages, limitations, and practical code examples for accurate change tracking in production environments.
This article examines a business requirement to filter and rank up to 100,000 records from a pool of tens of millions, presenting and evaluating four technical solutions—multithreaded ClickHouse pagination, Elasticsearch scroll‑scan deep paging, an ES‑HBase combined query, and a RediSearch + RedisJSON approach—along with performance data and code examples.
Redis version 7.0.8 has been released, addressing critical security vulnerabilities (CVE-2022-35977 and CVE-2023-22458) and fixing several bugs related to command handling, incremental rehashing, timeout blocking, and sentinel IP changes, with a full changelog available on GitHub.
RedisObject serves as a bridge between Redis's external data structures and internal implementations, enabling efficient storage and retrieval of data types like strings, lists, hashes, sets, and sorted sets through a unified object model.
This article explains two sliding‑window rate‑limiting methods for SMS sending—one based on IP address and another on phone number—and provides a complete PHP implementation using Redis sorted sets to enforce per‑minute, per‑10‑minute, and per‑hour limits.
This guide explains essential Redis monitoring metrics, the tools and commands for collecting performance, memory, activity, persistence, and error data, and shows how to use INFO, slowlog, and redis-benchmark to assess and improve database operations.
This comprehensive guide walks you through Spring Security fundamentals, setting up a Spring Boot project, configuring authentication with JWT and Redis, implementing RBAC permission management, customizing error handling, enabling CORS, and addressing CSRF, providing complete code examples and detailed explanations for secure backend development.
This guide explains how to install, configure, and run a lightweight Redis Monitor that visualizes connection count, QPS, memory usage and replication delay, supports standalone, sentinel and cluster modes, and provides email and WeChat alerts via simple PHP scripts.
This article analyzes the limitations of traditional HTTP session mechanisms in single‑server and clustered environments, explains why session sharing is essential for multi‑system products, and presents practical solutions such as session replication and centralized Redis storage, followed by a detailed walkthrough of CAS‑based single sign‑on implementation with Java Spring code examples and a comparison to OAuth2.
This article explains why Redis is essential for flash‑sale systems, detailing load characteristics, the three sale phases, Redis features such as high concurrency and atomic operations, and practical implementations using Lua scripts and distributed locks to ensure safe stock checking and deduction.
This article explains the fundamentals, characteristics, and use‑cases of distributed caching, compares Memcached and Redis, and provides a step‑by‑step Spring Boot implementation with code samples, testing guidance, and solutions to common cache pitfalls such as hot keys, penetration, and avalanche.
Facing a four‑hour coupon‑calculation bottleneck at eLong, I explored Storm’s stream‑processing model, identified the data‑extraction stage as the weak link, refactored the hotel‑pull service, leveraged RocketMQ for threading, and ultimately reduced full‑batch processing time to just over an hour.
This article explores sixteen practical Redis patterns—including caching, distributed sessions, locks, global IDs, counters, rate limiting, bitmaps, shopping carts, timelines, queues, lotteries, likes, tags, product filtering, follow relationships, and leaderboards—detailing their data types, commands, and code examples for building high‑performance systems.
This article explains how Redis implements the Pub/Sub messaging pattern by storing subscription relationships in hash‑based dictionaries, detailing the processing flow of SUBSCRIBE and PUBLISH commands, cluster propagation, and key limitations such as lack of persistence and client buffer constraints.
This article provides a comprehensive overview of Redis persistence mechanisms, detailing the concepts, features, advantages, disadvantages, trigger strategies, operational processes, configuration options, and troubleshooting steps for both RDB (snapshot) and AOF (append‑only file) approaches.
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.
This comprehensive guide covers Redis fundamentals, pipeline, pub/sub, expiration strategies, transactions, persistence mechanisms, distributed lock implementations, and the three clustering modes, while also addressing common cache problems and practical deployment steps.
This article explains how to replace manual cache handling with Spring Cache annotations, introduces the concepts of L1 (Caffeine) and L2 (Redis) caches, discusses design considerations for consistency, null handling, eviction, and provides practical Maven and configuration examples for Java backend applications.
This article explains how Redis achieves high performance by storing data in memory and using a variety of specialized data structures—such as SDS, quicklist, listpack, hash tables, and skip lists—to implement its key‑value store, covering their designs, trade‑offs, and evolution across Redis versions.
This article explains why modern internet products need caching to handle massive real‑time data, introduces Redis as an in‑memory database with persistence, master‑slave replication, and clustering, and demonstrates how these techniques dramatically improve performance, scalability, and reliability of web services.
This article explains Redis String data type usage, the Simple Dynamic String (SDS) implementation details, memory‑saving techniques, encoding options, and demonstrates a practical distributed ID generator built with Redis commands and persistence strategies.
This article clarifies the common misconception that Redis is purely single‑threaded by detailing its single‑threaded network I/O model, the evolution of multithreading support across versions, the client‑server request flow, and the underlying Reactor patterns that enable efficient concurrency.
This article details the requirements analysis, design approach, database schema, and step‑by‑step implementation of a follow/unfollow microservice using MySQL for persistence and Redis Sets for efficient set operations, including Maven dependencies, Spring Boot configuration, RedisTemplate setup, service, controller, and testing of common‑follow queries.
This article walks through the complete design and implementation of a friend‑follow microservice, covering requirement analysis, MySQL table schema, Redis set operations, Spring Boot dependencies, configuration, service and controller code, gateway routing, and end‑to‑end testing with concrete examples and performance insights.
This article explains why short-lived JWT tokens need automatic renewal, outlines a Redis‑based solution, and provides complete Spring interceptor and utility code to create, verify, and refresh tokens without forcing users to re‑login frequently.
This article compares three popular Java Redis clients—Jedis, Lettuce, and Redisson—detailing their advantages, drawbacks, and recommended usage scenarios, helping developers select the most suitable client based on performance, thread safety, and advanced Redis features such as clustering, sentinel, and distributed locks.
This comprehensive guide explores Redis fundamentals and advanced features, covering pipelines for reduced RTT, publish/subscribe messaging, key expiration strategies, transaction behavior, persistence mechanisms (RDB, AOF, hybrid), distributed locking techniques, sentinel high‑availability, and cluster sharding, with practical code examples and diagrams.
The article explains how to improve large file upload experiences by using instant (MD5‑based) upload, chunked upload, and resumable upload techniques, and provides complete Java backend implementations with Redis tracking, RandomAccessFile and MappedByteBuffer, plus practical deployment recommendations.
This article explains why a custom business rate‑limiting (risk‑control) component is needed for AI‑driven services, compares open‑source solutions, and provides a complete implementation using Redis+Lua scripts, Kotlin code, and Spring AOP annotations, including testing and deployment tips.
This article explains why a business needs its own risk‑control (rate‑limit) component, compares open‑source options, and provides a complete Kotlin/Spring implementation using Redis Lua scripts, annotations, and AOP to enforce real‑time adjustable limits.
This article explains common Redis caching issues—cache penetration, cache breakdown, and cache avalanche—detailing their causes and practical mitigation techniques such as parameter validation, null caching, Bloom filters, mutex locks, hot‑data strategies, and staggered expiration to ensure system stability.
This article analyzes the functional decomposition, data structures, system architecture, push‑pull mode selection, and message flow of a one‑to‑one instant messaging service, providing practical design guidelines and example Redis/MySQL schemas for building a scalable chat backend.
This article explains the concept of distributed locks, illustrates real‑world scenarios such as concurrent ATM transactions, and details how to implement reliable distributed locking with Redis using TTL keys, SETNX, Lua scripts, lock renewal, high‑availability considerations, and the RedLock algorithm.
This article breaks down the functional requirements, data models, layered architecture, push‑pull messaging choices, and message flow for building a robust one‑to‑one instant‑messaging service using Redis, MySQL and asynchronous queues.
This article explains three common Redis cache issues—penetration, breakdown, and avalanche—detailing their causes and offering practical solutions such as parameter validation, empty-value caching, Bloom filters, mutex locks, and staggered expiration to keep systems reliable under heavy load.
This guide details Alibaba Cloud Redis development standards, including readable key naming, value size limits, safe command usage, client connection pooling, eviction policies, useful tooling, and efficient big‑key deletion methods, helping engineers build high‑performance, reliable Redis services.
This article explains how to protect time‑consuming business operations using a Redis‑based distributed lock, detailing the annotation design, AOP pointcut, lock acquisition and release, timeout handling, and a scheduled renewal mechanism with sample Java code.
This article presents a comprehensive analysis and multiple design alternatives—including multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, ES+HBase hybrid, and RediSearch+RedisJSON—to efficiently filter, sort, and de‑duplicate up to 100,000 records from a pool of tens of millions, with detailed performance comparisons and code examples.
This article walks through the design and implementation of a friend‑follow microservice using MySQL for persistence, Redis Sets for fast set operations, and Spring Boot, covering requirement analysis, data modeling, dependency setup, configuration, service logic, and testing with concrete code examples and performance insights.
Learn how to efficiently store and query massive binary state data—such as user login status and daily sign‑in records—using Redis Bitmap, covering underlying structures, memory advantages, key design, and practical commands like SETBIT, GETBIT, BITCOUNT, BITPOS, and BITOP for real‑world analytics.
This article examines ten common traps when implementing Redis distributed locks—ranging from non‑atomic setnx/expire operations and missing expirations to lock release ordering, re‑entrancy, master‑slave replication issues, and the Redlock algorithm—providing concrete code examples, explanations, and best‑practice solutions.
This article analyzes the latency spikes observed in large‑scale Redis clusters after node expansion, identifies the CLUSTER SLOTS command and slot‑migration handling in hiredis‑vip and Jedis as the root cause, proposes a slot‑traversal optimization, and demonstrates a ten‑fold performance improvement with detailed benchmarks.
This article describes a Redis 5.0 memory leak scenario where 20 million keys with expiration caused memory not to be released, details the investigation steps, findings about the activeExpireCycle, and concludes that memory will eventually be freed, followed by a promotional announcement for a PHP online live class.
This article explains Redis's three clustering approaches—master‑slave replication, Sentinel, and native Cluster—detailing their architectures, replication mechanisms, advantages, disadvantages, and suitable scenarios for high‑availability and high‑concurrency database deployments.
