This guide demonstrates how to use Spring Boot 2.7 with Redis 6.2 to implement Pub/Sub messaging, transactional operations, pipelined commands, and Lua‑based distributed locks, providing code examples, configuration details, and explanations of each feature’s advantages and limitations.
This article explains the relationship between MySQL and Redis, the classic cache‑consistency problem, and compares four common cache‑update patterns—delete‑then‑update, update‑then‑invalidate, read/write‑through, and write‑behind—detailing their workflows, advantages, and drawbacks.
This course offers an in‑depth exploration of process concepts, TCP/IP and Socket communication, Nginx‑FASTCGI integration, host‑to‑network byte order conversion, and Redis fundamentals, targeting backend developers, system administrators, and network engineers seeking comprehensive backend skill enhancement.
This article explains the concept of idempotency, identifies which API requests are naturally idempotent, discusses why idempotency is essential for retries, asynchronous callbacks, and message queues, and provides a step‑by‑step Java Spring implementation using custom annotations, AOP, and Redis for token management.
This article explains the problems of traditional session management in multi‑service environments, introduces session replication and centralized storage (using Redis), and demonstrates a complete CAS‑based single sign‑on solution with Java code examples for user, controller, filter, and configuration components.
This article details the design and implementation of a highly available membership system that handles billions of users and peak traffic of over 20,000 TPS, covering Elasticsearch dual‑center master‑slave clusters, traffic‑isolated three‑cluster architecture, Redis caching with distributed locks, and dual‑center MySQL partitioning.
This guide introduces Lock4j, a versatile distributed‑lock component for Java that works with Spring AOP and supports RedisTemplate, Redisson, and Zookeeper, and walks through its features, configuration, annotation attributes, basic usage, and advanced customization options.
This article introduces KeyDB, a high‑performance multithreaded fork of Redis, explaining its architecture, thread model, connection management, fastlock mechanism, and active‑replica features, while providing code examples and performance comparisons, and highlighting their impact on throughput and latency.
This guide explains Redis's three clustering modes—master‑slave, Sentinel, and Cluster—detailing their architectures, failover mechanisms, PSYNC replication, configuration files, Spring Boot integration, and step‑by‑step testing to achieve high availability and scalability.
Bloom filters are space‑efficient probabilistic structures that test set membership using multiple hash functions, offering fast, low‑memory checks with a controllable false‑positive rate, and can be implemented manually in Java, via Guava’s library, or deployed at scale with RedisBloom for distributed applications.
The article shows how to build a reliable Redis‑based distributed lock in a Spring Boot 2.7 application by storing a unique UUID token, acquiring the lock with SET NX PX, releasing it atomically via a Lua script, and providing a clean Lock interface, factory component, and JUnit example.
This article provides a comprehensive technical overview of Redis, covering its high‑performance in‑memory design, rich data structures, persistence options, transaction support, eviction policies, common caching patterns, distributed locking techniques, and high‑availability solutions such as Sentinel and Cluster, while also comparing it with alternatives like Memcached, Tair, Guava, EVCache and ETCD.
This article explores high‑performance cache design, illustrating concepts with real‑world analogies, detailing traditional and multi‑level caching architectures, and providing practical implementations using Redis, Caffeine JVM cache, OpenResty Nginx local cache, and synchronization strategies such as double‑write, async notifications, and Canal‑based data replication.
This article explains why cache inconsistency occurs between MySQL and Redis, then walks through four concrete design patterns—delete‑then‑update, update‑then‑invalidate, read/write‑through, and write‑behind—detailing each step, trade‑offs, and failure scenarios to help engineers choose the most suitable approach.
This article explains how to build a TCC‑style distributed transaction layer for Redis using Go, detailing the two‑phase commit workflow, handling of prepare, commit, and rollback phases, the associated consistency challenges, and providing full code examples.
This article explains why request debounce is essential for preventing duplicate submissions, outlines which APIs need protection, and walks through two distributed‑lock solutions—shared Redis cache and Redisson—showing concrete annotations, key‑generation logic, and Spring‑AOP code with full test results.
This article demonstrates how to implement API request throttling in a Spring Boot application using a custom Interceptor and Redis, covering basic principles, configuration, custom annotations, reflection for per‑endpoint limits, handling path parameters, and addressing timing logic nuances.
This article explains the relationship between MySQL and Redis, discusses why cache consistency is challenging, and details four cache update design patterns—delete‑then‑update, update‑then‑invalidate, read/write‑through, and write‑behind—along with their advantages, drawbacks, and typical execution flows.
This article demonstrates how to build a Spring‑based API rate‑limiting solution using an Interceptor and Redis, covering the basic principle, project setup, code implementation, custom annotation with reflection for flexible limits, handling path‑parameter keys, real‑IP acquisition, and practical considerations for production use.
This article walks through creating a functional Redis service called EasyRedis, focusing on implementing a distributed cluster with a consistent‑hash algorithm in Go, including detailed code examples, node mapping, command routing, and relay mechanisms.
This article walks through the design and Go implementation of a reusable Redis connection pool, covering the pool data structure, object acquisition and release logic, handling of active limits and waiting queues, and an extended per‑IP socket pool for distributed Redis clusters.
This article provides a comprehensive tutorial on installing RedisInsight, configuring its environment variables, running it as a service or in Kubernetes, and using its GUI features to monitor and manage Redis instances, complete with code examples and deployment YAML.
Redis distributed locks require unique identifiers, atomic Lua releases, and TTL refreshes to avoid deadlocks, while the Redlock algorithm adds majority quorum but remains vulnerable to clock drift and client pauses, so critical systems should combine it with fencing tokens or version checks for true safety.
This article walks through building a functional Redis server in Go, focusing on transaction support (MULTI, EXEC, WATCH, UNWATCH, DISCARD), using locks for atomicity, version tracking for watch, and an undo‑log mechanism for rollback, with code examples and demo screenshots.
This guide walks through implementing a two‑level cache in Spring Boot 2.7 using Lettuce’s CacheFrontend together with Caffeine, covering dependency setup, configuration, custom CacheAccessor, bean definitions, and sample endpoints that demonstrate automatic synchronization and eviction between local JVM cache and Redis.
The article explains how to use Redis Sorted Sets for efficient pagination, employ Hashes with HSCAN for multi‑condition fuzzy matching, combine both techniques into a unified solution, and apply expiration‑based optimizations to keep the cache lightweight and responsive.
This article demonstrates how to replace heavyweight Spring Security with the lightweight Sa-Token framework by configuring token generation, session storage in Redis, service discovery via Nacos, and permission checks in a Spring Cloud Gateway micro‑service architecture, complete with code examples and deployment settings.
This article explains Lua fundamentals, why Lua is advantageous inside Redis, common use‑cases such as cache updates and distributed locks, and provides step‑by‑step guidance for integrating and executing Lua scripts in a Spring Boot application to improve performance and ensure atomicity.
This comprehensive guide walks through Redis's core data structures—including strings, lists, sets, sorted sets, hashes, HyperLogLog, bitmaps, streams, and geospatial indexes—explaining their characteristics and providing concrete command‑line examples to help developers select and use the right structure for their applications.
This article introduces Redis fundamentals and demonstrates how to integrate Redis into PHP web applications for caching, session management, database caching, and queue operations, providing code examples that illustrate connecting to Redis, setting and retrieving data, and configuring expiration to boost performance and stability.
This guide introduces RedisInsight, a powerful GUI for Redis, outlines its key features such as cluster support, visual data browsing, built‑in CLI, stream and log analysis, and provides step‑by‑step installation instructions for Linux, Kubernetes, and macOS, plus basic usage tips.
This guide introduces RedisInsight, outlines its key features, provides step‑by‑step installation on a physical server and via Kubernetes, explains environment configuration and startup, and demonstrates basic usage for monitoring and managing Redis instances through its graphical interface.
This article walks through the complete process of implementing a custom login authentication in Spring Boot, including custom authentication filters, success/failure handlers, a token stored in Redis, role‑based URL security, and detailed configuration of Spring Security headers and session handling.
This article analyzes why Lettuce's mget on Redis Cluster performs poorly due to slot-based architecture, presents client-side refactoring using hashtags and pipeline‑based JedisCluster modifications, and shows benchmark results demonstrating up to double speed improvement over Lettuce.
In his first 2024 blog post, Redis founder antirez shares a programmer's perspective on large language models, sharply critiques Google's search engine, evaluates current AIGC as both foolish and historically knowledgeable, and argues that generative AI mainly amplifies the abilities of already strong developers.
This article explains cache prewarming—its purpose, benefits, and various strategies such as startup loading, scheduled tasks, manual triggers, and cache loaders—while providing concrete Spring Boot and Redis examples, including code snippets for ApplicationReadyEvent, CommandLineRunner, InitializingBean, @PostConstruct, @Scheduled, and Caffeine cache loader.
This article explains why Redis traditionally operates with a single thread, how its memory‑centric design, simple data structures and I/O multiplexing keep it fast, and why newer Redis versions introduced multithreading for network I/O and lazy deletion of large keys.
This article covers Java backend architecture fundamentals, including front‑end/back‑end separation, Maven configuration, distributed lock implementations with Redis and Zookeeper, session handling in distributed systems, database locking strategies, and useful code snippets for common patterns.
A sudden Redis outage caused a shopping homepage to take 20 seconds to load, prompting a rapid analysis of data‑volume growth, a post‑mortem of the fallback logic, and the design of a combined local‑cache, MongoDB, and database strategy to restore fast, reliable service.
This article explains how to prevent API abuse by using a Spring Interceptor combined with Redis to count requests per IP and URI, demonstrates step‑by‑step code implementations, discusses custom annotations, mapping rules, time‑window challenges, path‑parameter handling, and real‑IP extraction for robust backend rate limiting.
This article reveals the most common Redis pitfalls—including unexpected key expiration loss, O(1) commands that block or cause OOM, master‑slave synchronization quirks, and persistence bugs—while providing practical guidance to avoid each issue and keep your cache performant and reliable.
The article analyzes the inventory oversell problem caused by concurrent purchase requests and presents four backend solutions—including a Redis distributed lock, MySQL row lock, optimistic locking with version fields, and conditional SQL updates—illustrated with Java code and SQL examples to ensure data consistency.
This article explains Redis's two persistence mechanisms—Append Only File (AOF) and RDB snapshots—detailing their operation, advantages, risks, write‑back strategies, rewrite process, and how to choose the appropriate method for performance and reliability requirements.
This article walks through implementing a Redis‑compatible sorted‑set in Go, covering requirement analysis, data‑structure design with a map and skiplist, detailed insertion and search algorithms, complete code examples, and edge‑case handling, all illustrated with diagrams and sample output.
This article explains two API rate‑limiting strategies—fixed‑window using Redis keys and sliding‑window using Redis sorted sets—detailing their principles, drawbacks, and providing complete Java implementations with Lua scripts, AOP annotations, and Redis configuration to enforce request limits.
This guide explores ten practical Redis scenarios—including login authentication, counters, fan following, leaderboards, anti‑scraping, message queues, browser history, distributed locks, user sign‑in tracking, and website UV statistics—showcasing commands and patterns to boost performance in real‑world applications.
Redis is an open‑source, in‑memory NoSQL database that provides ultra‑fast key‑value storage, rich data structures, persistence, clustering and extensible modules, making it the preferred distributed cache over Memcached, which lacks these features and is now rarely chosen for new projects.
This article presents a concise Spring Cloud microservice architecture diagram, explains each component such as DNS, CDN, LVS, Nginx, Nacos, Sentinel, Redis, and Elasticsearch, and offers practical guidance on their roles, selection criteria, and implementation details for interview preparation.
This article explains three Spring Boot approaches—using @Scheduled tasks, RabbitMQ delayed queues, and Redis key‑expiration events—to automatically cancel orders that remain unpaid for 30 minutes, complete with code samples and configuration guidance.
This article explains how KeyDB, a Redis fork, redesigns the single‑threaded key‑value store into a multi‑threaded system, covering its thread model, connection management, fastlock mechanism, and active‑replica features while maintaining full Redis API compatibility.
This article walks through the full design of a billion‑user group chat system, covering functional and non‑functional requirements, core components such as WebSocket and Redis, face‑to‑face group creation, message flow, database schema, and performance‑oriented scaling techniques.
This article explains the core design goals, sharding strategies, replication models, communication protocols, cache selection, and monitoring techniques needed to build high‑performance, highly available, and scalable distributed cache systems for large‑scale internet applications.
This article provides a step‑by‑step guide to implementing custom login authentication in a Spring Boot application, including Redis‑backed session storage, token handling, security headers, and fine‑grained role‑based URL permission checks using custom filters and handlers.
This article explains how to use Spring Boot Security for authentication and improve performance by caching user details in Redis, covering dependency setup, security configuration, Redis integration, testing endpoints, and optimization tips for a robust backend authentication solution.
This article explains how to migrate a specific Redis database (db8) to another server's db15 by writing a Python script that batches keys, tracks progress, estimates remaining time, and verifies the migration results.
This article demonstrates step‑by‑step how to prevent API abuse in a Spring MVC application by using an Interceptor combined with Redis for counting requests, customizing limits per endpoint through annotations and reflection, handling mapping rules, path‑parameter challenges, and obtaining the real client IP.
This article compares delayed tasks with scheduled tasks and presents six practical Java solutions—database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis ZSET, Redis key‑space notifications, and RabbitMQ delayed queues—detailing their implementations, advantages, and drawbacks for handling order‑timeout scenarios.
This article explains the concept of idempotency, why it matters for HTTP APIs, the impact on system design, RESTful method characteristics, and compares four practical implementation strategies—including database primary keys, optimistic locking, Redis token, and downstream sequence numbers—followed by a complete SpringBoot example with code and tests.
This article introduces Redis Stack’s RedisJSON module, explains its JSONPath syntax, details the full set of JSON commands for handling various data types, provides practical code examples, and highlights how RedisJSON enables Redis to function as a document, full‑text, and vector search database.
A Redis lock timeout caused users to be blocked for two hours, revealing problems with lock leakage and mis‑release; the article explains the root causes, proper use of SETNX with EXPIRE, and Lua scripts for atomic operations and safe lock deletion.
RedisInsight is a GUI for Redis that monitors memory, connections, hit rate, and uptime, supports clusters, SSL/TLS, and key editing, and can be installed on Linux via a downloadable package with environment variables and launched as a service, or deployed on Kubernetes using a NodePort service and a Deployment of the redislabs/redisinsight image, after which the UI provides metrics, data editing, and memory analysis.
This article explores Redis's capabilities beyond simple caching, detailing its use for distributed locks, rate limiting, session storage, complex business scenarios, and various messaging patterns—including List‑based queues, blocking commands, Pub/Sub, and the Stream data structure—while highlighting practical limitations and best‑practice recommendations.
This article introduces Redis, explains its key advantages as an in‑memory data store, provides step‑by‑step installation instructions for CentOS including required packages, and demonstrates basic commands to start the server and interact with the database.
This article explains why duplicate form submissions occur, the risks they pose, and demonstrates a Spring Boot solution that uses a custom @RequestLock annotation together with Redis SETNX to generate a unique key and block rapid repeated requests, complete with project setup, code examples, and usage instructions.
Redis implements its own Simple Dynamic String (SDS) instead of plain C strings because SDS stores length for O(1) queries, pre‑allocates extra space and lazily reuses freed bytes, prevents buffer overflows, handles binary data, and uniformly backs all string keys, values and container elements.
This article walks through the design of a billion‑user group chat platform, covering functional and non‑functional requirements, core components, database schema, face‑to‑face group creation, message flow, storage strategies, and performance‑optimizing techniques such as clustering, message queues, multithreading, and Redis caching.
Salvatore Sanfilippo, a self‑taught hobbyist who launched Redis in 2009, broke traditional database rules by building an in‑memory NoSQL system, sharing his open‑source philosophy, and shaping a thriving community that powers companies like Uber, Slack, and Twitter.
This article explains how to implement API request rate limiting in Spring Boot by creating a custom @RequestLimit annotation, using Redis to track request counts, and configuring a HandlerInterceptor and WebMvcConfig to enforce limits on controller methods.
This article explains how to design and implement a token generation, storage, and verification system for both PC and mobile clients in a distributed microservice architecture, using Spring Boot, Redis, custom annotations, AOP aspects, and Vue front‑end integration.
The article explains how Redis Cluster distributes keys using CRC16‑based hash slots instead of traditional consistent hashing, detailing the slot calculation, node addition and removal processes, client redirection, smart client optimizations, and the design reasons behind the fixed 16,384 slot count.
This tutorial demonstrates how to use Docker‑Compose to deploy a Redis exporter, configure Prometheus to collect its metrics, and define alerting rules for Redis health monitoring, providing step‑by‑step commands and YAML examples for a complete monitoring setup.
This article compiles a comprehensive set of ByteDance daily internship interview questions covering Java backend fundamentals, networking protocols, operating system concepts, Linux process management, Redis data structures and persistence, MySQL indexing and query optimization, as well as essential algorithms, providing detailed explanations and code examples for each topic.
This article walks through building an EasyRedis service in Go, explaining Redis's lazy and timed expiration strategies, showing concrete code for on‑read expiration checks, and detailing a time‑wheel implementation that efficiently schedules key deletions.
This article walks through the third part of an eleven‑article series that implements a functional Redis‑compatible in‑memory database in Go, detailing how the PING, AUTH, SELECT, SET and GET commands are parsed, routed and executed with concrete code examples.
This article explains how to design and implement a distributed rate‑limiting solution that supports multiple concurrent rules—such as per‑minute and per‑hour limits—by analyzing the shortcomings of simple string counters, introducing atomic Lua scripts and Zset structures, and providing complete Java annotation and AOP code examples.
This article explains how KeyDB, a multithreaded fork of Redis, restructures the original single‑threaded design by introducing worker threads, per‑thread connection handling, a fastlock spin‑lock implementation, and an active‑replica feature that enables writable replicas with conflict‑resolution using timestamped keys.
This guide walks through Redis fundamentals, covering how data persists after restarts, core key operations, database selection, serialization, expiration handling, key movement, random retrieval, renaming, and how to check the number of configured databases, all with practical command examples and visual illustrations.
Jedis uses Apache Commons’ GenericObjectPool to manage Redis connections, with Spring‑Data‑Redis creating a JedisConnectionFactory that holds a configurable pool where borrowObject and returnObject handle idle queues, eviction and validation settings (testOnBorrow, testWhileIdle, etc.) can be tuned, and JMX metrics aid troubleshooting.
This article walks through a real‑world sales‑ranking scenario, explains why a simple SQL solution falls short at scale, and demonstrates how Redis Set and ZSet data structures provide high‑performance, real‑time ranking, including detailed command examples, performance metrics, and an in‑depth look at ZSet's internal listpack and skiplist‑dict implementations.
Learn how to generate text embeddings with OpenAI's ChatGPT API, store them in Redis' vector database, and perform efficient similarity searches using PHP, covering installation, API calls, index creation, vector storage, KNN querying, and practical code examples.
The article explains how to handle the most complex part of an e‑commerce order flow—stock deduction under high concurrency—by using JVM and distributed locks, Redis atomic operations, two‑phase commit, hot‑cold routing, fault tolerance, and cache rebuilding strategies.
This guide introduces RedisSearch, walks through installation, explains its rich feature set, details core concepts like data models and indexing, shows command‑line operations for creating indexes and querying, and provides a complete PHP example for integrating RedisSearch into applications.
This article compiles essential backend interview questions and answers covering MySQL storage engines and indexes, Redis persistence modes, Java collection frameworks and HashMap internals, thread‑safe ConcurrentHashMap implementations, as well as HTTP message structure and TCP reliability mechanisms, providing a thorough review for candidates preparing for backend positions.
The article explains the concept of delayed tasks versus scheduled tasks in payment systems, outlines their key differences, and evaluates five practical implementation approaches—Quartz database polling, JDK DelayQueue, Netty's HashedWheelTimer, Redis ZSET/Keyspace notifications, and RabbitMQ delayed queues—detailing their code examples, advantages and drawbacks.
This article explains why traditional file uploads struggle with large files, then introduces three advanced techniques—instant (秒传), chunked (分片上传), and resumable (断点续传) uploads—detailing their core logic, implementation steps, and Java code examples for backend developers.
Redis processes core command operations in a single thread but incorporates multithreaded components for asynchronous tasks and network I/O, using an event‑driven epoll model and optional I/O threads introduced in v6.0 to boost performance on multi‑core systems.
KeyDB is a high‑performance, multithreaded fork of Redis that retains full protocol compatibility while adding features like Active Replication, flash storage support, and advanced locking, offering up to double the query throughput and reduced latency on the same hardware.
This article explains the concept of idempotency, presents several strategies to achieve it, and provides a complete Spring Boot implementation using Redis, a custom @AutoIdempotent annotation, token generation and verification, interceptor configuration, and test cases to ensure only the first request succeeds.
This article presents a complete solution for reliable, resumable file upload and download over MQTT in distributed IoT platforms, leveraging FastDFS for storage and Redis for caching file metadata and progress, detailing the architecture, data structures, and handling of packet fragmentation, offsets, and cluster coordination.
This guide explains how to set up Redis Stack with Docker, covering its components, available images, commands to pull and run the containers with volume mounts and port mappings, configuration file details, and how to access RedisInsight for visual data management.
This article explores how counters, especially 24‑bit timestamps, are employed in Redis’s LRU eviction algorithm and other memory‑constrained scenarios, detailing implementation tricks, precision trade‑offs, and practical code examples for efficient cyclic counters and compact storage techniques.
This article explains how to determine whether Redis is truly experiencing latency spikes, outlines a step‑by‑step benchmarking process, identifies common causes such as high‑complexity commands, big keys, memory limits, fork overhead, AOF settings, CPU binding, swap usage, and provides concrete configuration and code examples to resolve each issue.
RediSearch, a low‑memory Redis module, offers comparable full‑text search capabilities to Elasticsearch, with faster indexing and query performance on modest hardware; this article explains its features, compares benchmarks, shows Docker installation, and provides Java/Jedis code examples for creating, querying, and managing indexes.
This article explains the concept of idempotency, outlines common strategies, and provides a complete Spring Boot implementation that uses Redis, a custom @AutoIdempotent annotation, token generation, and a web interceptor to ensure each API request affects the database only once.
Redis serves as a powerful in‑memory key‑value store for distributed caching, offering various data structures, persistence options, deployment modes, eviction policies, and update strategies, while addressing consistency challenges, cache miss scenarios, and failure modes such as penetration, breakdown, and avalanche.
This article walks through the full design of a large‑scale comment system, covering functional requirements, database schema, distributed architecture, high‑concurrency handling, caching, security measures like Bloom filters, and optional NLP‑based sentiment analysis to moderate live‑stream comments.
This article introduces the Lock4j distributed lock library for Java, outlines its key features and supported backends, provides step‑by‑step Maven dependency setup, Redis configuration, annotation details, and demonstrates both basic and advanced usage patterns including custom executors and lock‑failure strategies.
This article explains the fundamentals of finite state machines, introduces Spring Statemachine, shows how to define states, events, and transitions for an order lifecycle, demonstrates memory and Redis persistence, provides full Java code for controller, service, listeners, and discusses testing, error handling, and AOP logging.
The article presents a collection of typical Java backend coding mistakes—ranging from misused ternary operators and poor parameter validation to logging pitfalls, dead code, improper exception handling, AOP self‑invocation issues, Redis resilience problems, and Excel file upload bugs—along with concrete examples, images, and corrected code snippets to help developers avoid and fix them.
This article presents a concise tutorial on building a flash‑sale (Seckill) system with SpringBoot, MySQL, Redis, RabbitMQ and a basic HTML/JQuery front‑end, covering architecture, key features, code snippets, over‑selling prevention, rate limiting, and deployment screenshots.
