This article walks through the design, pitfalls, and step‑by‑step implementation of a token‑bucket rate‑limiting middleware for the Webman PHP framework, highlighting the need for atomic Redis operations and showing how a Lua script resolves concurrency issues in distributed environments.
Learn how to build a secure authentication system in Spring Boot 3 that restricts each user to a single active session, stores tokens in Redis, and implements automatic JWT token refresh, with detailed code examples and step‑by‑step explanations.
This guide walks you through installing RedisInsight, configuring its environment variables, deploying it on Kubernetes, and using its GUI to monitor Redis memory, connections, and performance, while also covering the prerequisite Redis server setup and essential command‑line operations.
This article explains the three‑stage execution flow of a Redis command—connection establishment, command processing, and result return—detailing how the single‑threaded reactor pattern drives event handling, how commands are parsed and dispatched, and how the output is sent back, with code snippets and a comparison to Netty’s multithreaded reactor.
To retrieve up to 100 000 items from a pool of tens of millions, the article compares multi‑threaded ClickHouse pagination, Elasticsearch scroll‑scan deep paging, a combined ES‑HBase approach, and RediSearch + RedisJSON, detailing design, implementation code, performance benchmarks, and trade‑offs.
This comprehensive guide walks you through Redis cluster architecture, deployment, enterprise‑grade configuration management, logging, monitoring, queue handling, performance tuning, and fault‑tolerance practices, providing step‑by‑step instructions, scripts, and best‑practice recommendations to quickly resolve the majority of production problems.
This article breaks down the massive‑scale challenge of calculating mutual friends for hundreds of millions of users, analyzes data‑size, latency, and memory constraints, and presents three Redis‑based solutions—basic Set, bitmap, and a sharded architecture—complete with code snippets, performance numbers, and practical trade‑offs.
This article explores four common rate‑limiting algorithms—fixed window, sliding window, leaky bucket, and token bucket—explains their core principles, shows Java and Redis implementations, discusses real‑world production cases, and provides practical tips for avoiding pitfalls and optimizing performance.
This article provides comprehensive interview guidance and technical deep‑dives covering Java self‑introduction, the B‑T‑A‑R project‑highlight model, differences between abstract classes and interfaces, varargs usage, database index pros and cons, Redis pipeline vs Lua scripting, cache‑breakdown mitigation, distributed session consistency, and memory‑efficient Excel export techniques.
The article reveals REDstar algorithm and developer salary packages, explains why Xiaohongshu’s work schedule changed, and then provides detailed Java interview questions covering MySQL indexes, composite indexes, Java primitive types, boxing/unboxing, ReentrantLock vs synchronized, Redis usage, common commands, distributed locking, and the benefits of RocketMQ, all illustrated with code snippets and diagrams.
This article explains how to protect time‑consuming business operations using a Redis‑based distributed lock implemented with a custom annotation, Spring AOP interception, automatic lock renewal via a scheduled executor, and proper lock release, ensuring data consistency across concurrent requests.
This article explains the Bloom filter data structure, its hash‑based design and false‑positive behavior, then demonstrates practical implementations using Java BitSet, Guava, and Redisson, covering initialization, configuration, usage tips, and performance considerations for Redis bitmap storage.
This article explains how to implement a precise sliding‑window rate‑limiting algorithm using Redis Sorted Sets, detailing the problem scenario, the algorithm steps, Lua script implementation, Java integration, and practical extensions for high‑performance backend services.
This article explains how to use segmented (sharded) locks and Redis‑based routing strategies to parallelize inventory deduction and order creation, dramatically increasing orders processed per second while maintaining atomicity and fault tolerance.
This article explains why Redis, a single‑threaded in‑memory database, can become blocked, covering five common culprits such as blocking commands, big keys, database flushes, synchronous AOF writes, and the SAVE command, and offers guidance on preventing performance stalls.
This guide walks operations engineers through installing Redis, configuring a six‑node cluster, applying memory and system‑level performance tweaks, setting up Sentinel high‑availability, and implementing Python‑based monitoring and automated recovery scripts, providing a comprehensive, hands‑on approach to building a robust Redis service.
Learn how to design and implement a Redis-based distributed lock in Java using custom annotations, AOP interception, and a scheduled executor to automatically extend lock expiration, ensuring safe concurrent access to critical resources while handling timeouts, retries, and thread interruptions.
This article explores various techniques for implementing delayed tasks in Java, comparing Quartz database polling, JDK DelayQueue, Netty's HashedWheelTimer, Redis sorted sets, and RabbitMQ delayed queues, detailing their implementations, advantages, drawbacks, and practical code examples for handling order timeouts.
This article explains why single‑node Redis can become a single point of failure, compares Redis Sentinel and Redis Cluster deployment options, provides step‑by‑step Docker deployment scripts, details Sentinel’s inner workings, demonstrates failover verification, and shares best‑practice recommendations for production environments.
The article shares a detailed SF interview experience, covering typical Java interview questions such as self‑introduction, challenging projects, learning paths, abstract class vs interface, HashMap vs Hashtable, insertion steps, red‑black and B+ trees, MySQL and Redis indexing choices, large‑table optimization, JVM memory model, and the purpose of the Survivor space.
A week‑long API freeze in a sandbox environment was traced to a misconfigured Redis connection pool in a Spring Java application, where threads waited indefinitely for a Jedis resource, and the fix involved setting proper pool timeouts, using RedisCallback for scans, and correctly releasing connections.
This comprehensive guide walks you through installing Redis on a single server using source compilation and Docker, configuring persistence, memory management, backups, disaster recovery, and systemd service setup, ensuring a production‑ready Redis instance that can handle over 10,000 QPS.
This tutorial walks Java developers through using Redis in Spring Boot projects, covering the essential spring-boot-starter-data-redis dependency, RedisTemplate basics, the underlying RedisConnectionFactory design, custom connection configurations for single‑node and sentinel modes, and seamless integration of the Redisson client for advanced distributed features.
This article explains what debounce means for web APIs, identifies which endpoints need it, describes how to detect duplicate requests, and provides complete Java implementations using shared Redis caches and Redisson distributed locks with code examples and key generation strategies.
This article analyzes a production‑line data‑distribution issue where parallel processing and rule‑based assignment cause some employees to receive no tasks, explains why simply increasing batch size fails, and presents a Redis‑counter solution that balances efficiency with fair workload distribution.
This article explains Redis' deployment models, core components, and the event‑driven engine that powers command processing, detailing the flow from client connection through the reactor loop, command parsing, execution, and response delivery with code examples and diagrams.
This guide walks you through the realities of joining state‑owned enterprises, offers practical tips for Java backend interview preparation—including self‑introduction, project presentation, database choices, Redis eviction policies, common design patterns, singleton usage, thread‑safety concepts, and commands to terminate Java processes on Linux, macOS, and Windows.
This article explains why the KEYS command is unsafe for large Redis keyspaces, introduces the SCAN command and multithreaded scanning techniques, compares performance, and offers alternative counting strategies to reliably count hundreds of millions of keys.
This article explains why traditional polling fails for large‑scale delayed tasks, compares built‑in Java, RocketMQ, and RabbitMQ delay queues, and provides a detailed Redis‑based design with architecture diagrams, message structures, and a 2.0 version that uses real‑time locking for low‑latency delivery.
This article explains how to implement distributed locks using Redis, covering basic SETNX/EXPIRE techniques, common pitfalls, atomic Lua scripts, the RedLock algorithm, and practical Redisson usage, while providing Java code examples and best‑practice recommendations.
This article examines the open‑source memory cache Dragonfly, its claim of being the world’s fastest Redis‑compatible system, the Redis team’s detailed response and benchmark methodology, and presents comprehensive performance comparisons that show Redis often outperforms Dragonfly across various workloads and configurations.
Redis bitmap commands enable efficient bit‑level storage and fast counting, and this article explains the core concepts, key commands like BITSET, BITGET, BITCOUNT, and provides a complete PHP example that tracks user sign‑ins and calculates daily totals using Predis.
This article explains Redis 6.0's multithreaded I/O feature, covering its background, configuration parameters, execution flow, source code analysis, performance benchmarking against single‑threaded mode, identified limitations, and a brief comparison with Valkey 8.0's advanced I/O design.
This article explains why multiple independent login systems hurt user experience and security, reviews traditional session mechanisms and their limitations in clustered environments, and then presents two session‑sharing strategies and a complete CAS‑based SSO solution with Java code examples.
This article explains why the KEYS * command is dangerous for large Redis deployments and presents several practical alternatives—including SCAN, multithreaded SCAN, cluster‑wide parallel scans, built‑in counters, and real‑time incremental counting—along with code samples, performance comparisons, and guidance on choosing the right solution.
This tutorial explains how to integrate Redis caching into a FastAPI application, covering installation, connection handling, cache expiration, testing, cache clearing, and best‑practice considerations to dramatically improve API response times and scalability.
The article shares a personal experience of TP-Link's early campus recruitment and salary expectations, then provides a comprehensive Java backend interview guide covering class‑loader delegation, JVM memory layout, garbage‑collector types, synchronized lock mechanics, and common Redis cache pitfalls with practical solutions.
Explore essential Redis Cluster interview questions covering slot count, hashing mechanisms, use cases, configuration options, hash slots, hash tags, node ports, and consistency model, providing concise answers that help candidates master the core concepts and excel in technical interviews.
This article explains what Redis hotspot keys are, the performance and stability issues they cause, common causes, how to monitor and identify them, and practical mitigation strategies such as cluster scaling, key sharding, and multi‑level caching.
Redis, an in‑memory high‑performance data store, serves as a popular secondary cache; this article explains its key features, data structures, persistence options, and presents a step‑by‑step Java workflow—including client creation, request sending, result handling, and connection cleanup—to help test engineers design effective performance tests.
This article examines common pitfalls of using single‑machine synchronization and basic SETNX locks for high‑concurrency stock‑deduction scenarios, demonstrates step‑by‑step improvements—including lock expiration and Redisson’s Lua‑based implementation—and discusses trade‑offs between Redis and Zookeeper for distributed locking.
This article explains Redisson's various distributed lock mechanisms—including watchdog, reentrant lock, multi‑lock, read‑write lock, semaphore, RedLock, and CountDownLatch—detailing their principles, usage patterns, code examples, and best‑practice recommendations for robust backend concurrency control.
This article explains MaShang Cloud's RDS high‑availability design, detailing the distributed sentinel monitoring system, proxy layer, multi‑AZ disaster‑recovery strategies, and real‑world case studies that demonstrate how MySQL and Redis services maintain continuous, consistent access with minimal RTO and RPO.
The article explains how Baidu Cloud Redis's Data Flashback feature combines RDB snapshots with timestamped AOF logs to provide fast, space‑efficient, point‑in‑time data recovery, overcoming the limitations of native Redis persistence in high‑traffic scenarios.
This article explains how to implement request debouncing in Java backend services using Redis and Redisson, covering the concept, interface types needing debouncing, duplicate request detection, shared cache and distributed lock solutions, with complete code examples and testing results.
This article walks through five concrete implementations for per‑minute API call counting—fixed window, lazy sliding window, Spring AOP, Redis time‑series, and Micrometer + Prometheus—detailing their design, code, trade‑offs, benchmark results, memory usage, and real‑world deployment tips.
This guide walks you through creating a full-featured QR code login demo using Spring Boot, WebSocket, and Redis, covering backend services, frontend pages, project structure, code snippets, deployment steps, and security best practices for a seamless login experience.
This article explains why per‑minute API call counting is essential for performance bottleneck detection, capacity planning, security alerts and billing, and presents five concrete Java‑based implementations—including a fixed‑window counter, a sliding‑window counter, AOP‑based transparent monitoring, a Redis time‑series solution, and Micrometer‑Prometheus integration—along with a hybrid architecture, performance benchmarks, and practical capacity‑planning advice.
The author recounts fixing a complex Redis Vector Sets bug, explores how human creativity outperforms LLMs in devising efficient data‑consistency checks, and shares experimental ideas—including XOR accumulators and MurmurHash—to detect non‑mutual links in large HNSW graphs.
This article explains how Baidu Intelligent Cloud Redis introduces a hybrid RDB‑AOF persistence model with built‑in timestamps, enabling fast, storage‑efficient point‑in‑time recovery—addressing the limitations of native Redis RDB snapshots and AOF logs for critical game and e‑commerce workloads.
The article analyzes a Meituan interview question about caching 10 million MySQL rows when Redis can store only 200 thousand rows, presenting a five‑step three‑tier cache architecture that separates cold and hot data, selects appropriate eviction policies, uses proactive hotspot detection, adds multi‑level defense, and employs both scheduled and real‑time pre‑heating, with performance numbers showing an 85% hit rate and 100 ms latency.
This guide explains how to set up and run Locust load tests for WebSocket connections and Redis interactions in Python, including client implementations, heartbeat simulation, and practical tips for resource management and concurrency control.
This article explains how to achieve API idempotency by having clients send a short‑lived unique serial number, storing it as a Redis key with SETNX and an expiration, and handling the Redis response to process or reject duplicate requests.
Redis 8 has been released under the OSI‑approved AGPLv3 license, reversing its 2024 SSPL shift, and brings up to 87% faster command execution, double the throughput, and integrated modules like JSON, TimeSeries, and the new Vector Sets data type, sparking community debate and competition with Valkey.
This article explains how to use Redis Sorted Sets and Hashes to achieve efficient pagination, fuzzy multi‑condition queries, and their combination, while also discussing performance‑optimisation strategies such as temporary ZSet expiration and data‑freshness handling, before concluding with a brief promotional segment.
This article provides a comprehensive tutorial on RedisInsight, covering its features, step‑by‑step physical and Kubernetes installation, environment variable setup, service startup, and basic usage together with Redis server configuration, illustrated with code snippets and screenshots.
This article shares ten practical cache governance rules—from avoiding large keys and setting proper TTLs to using distributed locks and final consistency strategies—illustrated with real‑world Java examples, code snippets, and diagrams to help backend developers design reliable, high‑performance caching solutions.
During a major promotion a huge activity generated an oversized Redis cache key that caused cache‑penetration, saturated network bandwidth, and triggered a cascade of service failures, prompting a detailed root‑cause analysis and a set of mitigation and prevention measures.
Redis clusters use two redirection commands—MOVED for permanently migrated hash slots and ASK for temporary redirects during slot migration—explaining their trigger conditions, typical scenarios, and step-by-step client interaction examples, including sample CLI output.
This article explains why API debounce is needed in web back‑ends, identifies the types of endpoints that require it, outlines how to detect duplicate requests, and provides two concrete distributed solutions—shared Redis cache and Redisson lock—complete with annotation design, key generation logic, and full Java code examples.
This article analyzes the challenges of e‑commerce flash‑sale spikes and presents four proven architectural patterns—pressure distribution, Redis + MQ, Inventory Hint, and their combined use—detailing their principles, Lua scripts, transaction messaging, and practical trade‑offs for building resilient, high‑throughput systems.
Redis is ubiquitous in Java development for caching, ranking, and distributed locks, but its transaction model differs from traditional databases; this article explains Redis transaction fundamentals, core commands (MULTI, EXEC, DISCARD, WATCH), common pitfalls, best practices, and interview FAQs to help developers avoid mistakes.
This article explains the PFAIL (possible fail) and FAIL (failed) states in Redis clusters, describes the state transition process, demonstrates node failure and automatic failover with command‑line examples, and provides practical insights into cluster health monitoring and recovery.
Redis 8.0, released on May 1 2025, introduces a major license shift to AGPL‑v3, adds eight native data structures—including vector sets, JSON, and time‑series—enhances the query engine with up to 16× performance gains, improves scalability, security, and cloud‑native support, and provides extensive code examples for AI and real‑time analytics.
This article explains how to prevent duplicate order submissions during high‑traffic e‑commerce events by using a server‑generated anti‑duplicate token stored in Redis, detailing the token acquisition, validation flow, and handling of repeated requests to ensure inventory integrity and accurate financial reconciliation.
This article explains how to extract AOP annotation code, implements a Redis-based rate limiter using Redisson in Java, analyzes the underlying Lua script, and extends the utility to support automatic expiration of the limiter, providing complete code examples and detailed explanations.
This guide demonstrates how to protect a Spring Boot service from malicious requests by creating a custom interceptor that tracks URL‑IP request counts, uses Redis for distributed locking, and disables offending IPs after a configurable threshold, with full code examples and configuration steps.
This guide walks you through installing software on CentOS using three primary methods—source/tarball compilation, RPM packages, and Yum—demonstrating each approach with real‑world examples such as Redis, RabbitMQ, and Nginx, and covering essential concepts, commands, and configuration steps.
This guide explains the principles of MySQL master‑slave replication, shows how to configure and verify replication, provides Dockerfiles and docker‑compose files for MySQL and Redis clusters, and demonstrates testing each cluster step by step.
The article examines how e‑commerce platforms implement order auto‑closure using delayed tasks, compares methods such as message‑queue delayed delivery, Redisson delay queue, Redis expiration listening, RabbitMQ dead‑letter queues and time wheels, and recommends reliable approaches while warning against unsafe practices.
This article explains how to import 1 billion 1 KB log records stored in HDFS or S3 into MySQL by analyzing single‑table limits, using batch inserts, choosing storage engines, sharding, optimizing file‑reading methods, and coordinating distributed tasks with Redis, Redisson, and Zookeeper to ensure ordered, reliable, and high‑throughput data loading.
This article explains how to manually migrate a hash slot in a Redis cluster by checking cluster status, setting importing and migrating slots, retrieving keys, using the MIGRATE command, and updating slot assignments across nodes, with detailed command examples and explanations.
Redis 8.0 GA introduces major performance enhancements, adds AI‑focused vector and probabilistic data structures, expands native JSON support, improves the query engine with secondary indexes, and re‑embraces open source by offering an AGPLv3 licensing option.
This article explains why Redis is becoming a DBA's favorite, provides a five‑minute installation guide, essential commands, cache‑design pitfalls and solutions, explores Redis data structures with Java examples, demonstrates distributed locking and flash‑sale implementations, and covers clustering, backup, monitoring, and performance tuning.
Redis 8.0 GA introduces a suite of new data structures, AGPLv3 licensing, multithreaded query execution, horizontal scaling, and significant performance gains, positioning Redis as a more powerful in‑memory database for big‑data, AI, and real‑time applications.
The article explains why traditional auto‑increment primary keys are unsuitable for distributed systems, outlines the business requirements for a distributed ID (global uniqueness, trend and monotonic increase, security), and reviews several generation approaches such as UUID, database auto‑increment, segment mode, Redis, Snowflake, Baidu UidGenerator, Meituan Leaf and Didi TinyID, including their advantages and drawbacks.
Redis, after a year of closed‑source experiments, reopens its source code with version 8 under AGPLv3, offering developers a choice of three licenses, detailing the CEO's regrets, community backlash, emerging forks, and new performance‑focused features that reshape its future.
The production failure where a customer‑service event creation stopped each morning was traced to RedisTemplate’s increment returning null because @Transactional combined with enabled Redis transaction support caused the command to be queued in a MULTI/EXEC block, which is fixed by using separate non‑transactional and transactional StringRedisTemplate beans.
This article examines six different leaderboard implementation strategies—from simple database sorting and cache‑plus‑scheduled tasks to Redis sorted sets, sharded Redis clusters, pre‑computed layered caches, and real‑time stream processing with Flink—detailing their suitable scenarios, advantages, disadvantages, and architectural diagrams to help engineers choose the most appropriate solution.
Operations engineers struggling with countless Redis commands and opaque data structures can simplify their workflow with five recommended visual tools that turn complex Redis operations into intuitive interfaces, complete with monitoring, cluster support, and cross‑platform clients.
Redis, after a year of closed‑source experiments and a controversial dual‑license strategy, announced its return to open source under AGPLv3 for version 8, sparking intense debate over licensing choices, community trust, and the future direction of the in‑memory database ecosystem.
This article explains how to integrate Lua scripts into Spring Boot applications to leverage Redis for atomic operations, performance optimization, and complex data processing, providing detailed Lua fundamentals, practical use‑cases, implementation steps, error handling, security considerations, and best‑practice recommendations.
This guide explains how to use Nginx, Lua (via OpenResty), and Redis to automatically block any IP that exceeds 60 requests per minute, storing the blacklist in Redis with a default one‑day ban and providing performance optimizations and testing steps.
This article examines Japan’s looming 500,000 IT talent shortage, Microsoft’s AI‑driven overhaul of M365, a fraud case involving outsourced development, Redis’s return to open‑source licensing, and Google’s rollout of Gemini AI for children, highlighting the broader implications for the tech industry.
This article presents a continuously updated collection of over 120 Spring Boot 3 practical examples, covering database initialization scripts, switching Redis clients, disabling and customizing security, configuring HTTP clients, and fine‑tuning Spring MVC behavior with code snippets and configuration details.
This guide reviews common backend interview topics, explaining TCP TIME_WAIT behavior, multi‑port listening, full page load steps, Redis data types, Kafka consumer sizing and at‑most‑once semantics, the CAP theorem, Singleton usage, C++ std::map complexity, and an O(n) doubly‑linked list reversal algorithm.
This article traces MySQL’s architectural evolution from single‑node to sharded clusters, explains the fundamentals and classifications of NoSQL databases, and provides a comprehensive guide to Redis—including installation, memory management, and detailed usage of its five core data types with best‑practice considerations.
This tutorial walks developers through setting up a low‑cost, containerized AI service on Windows by installing Docker, deploying Redis and Ollama containers, pulling the DeepSeek‑R1 model, and integrating everything with Spring AI to enable continuous conversation support.
This comprehensive guide explains Redis's core architecture, the underlying implementation of its various data types, persistence mechanisms (RDB and AOF), high‑availability solutions such as replication, Sentinel and Cluster, as well as performance‑monitoring techniques and common optimization strategies.
This article explains the process of moving hash slots between nodes in a Redis cluster using the redis-cli --cluster reshard command, detailing the required parameters, interactive steps, and verification of successful slot migration.
This article explains the key Redis cluster configuration options found in redis.conf, detailing required settings such as cluster-enabled, cluster-config-file, and cluster-node-timeout, as well as optional parameters like cluster-slave-validity-factor, migration barrier, full coverage requirement, and read‑when‑down behavior.
This article explains the various PHP caching layers—including OPcode, data, page, and HTTP caching—provides configuration examples, code snippets for file, Memcached, and Redis caches, and outlines best practices and invalidation strategies to improve web application performance.
This tutorial introduces NoSQL concepts and provides step‑by‑step Python code examples for installing, connecting, inserting, querying, updating, and deleting data in both MongoDB and Redis, highlighting their suitable use cases and key differences.
This article explains how to design and implement a reliable, resumable multipart file upload system in Java, using Redis for session tracking, FileChannel for zero‑copy merging, progress monitoring, checkpoint files for resume support, and NFS shared storage for Docker‑based distributed deployments.
This article explains the concept of epochs in Redis Cluster, describing the two types—currentEpoch and configEpoch—their roles in versioning and conflict resolution, how they are updated and persisted, and provides example node listings and commands for inspection.
This article analyzes how to build a real‑time, billion‑user leaderboard for a game like Honor of Kings, explaining why traditional ORDER BY queries fail, why Redis sorted sets excel, and detailing sharding, hot‑key mitigation, memory optimization, and fault‑tolerant implementation techniques.
This article explains how Redis cluster nodes use a TCP-based gossip protocol and a dedicated cluster bus to discover each other, detect failures, synchronize configuration, and automatically redirect client commands to the correct node, illustrated with practical command‑line examples.
This article compares several ways to implement order‑closing delayed tasks—message‑queue delayed delivery, Redisson DelayQueue, Redis expiration listening, RabbitMQ dead‑letter queues, and time wheels—explaining their mechanisms, drawbacks, and recommending the most reliable solutions for production systems.
Redis cluster relies on two ports per node, a hash‑slot based sharding scheme, a master‑slave replication model, and provides eventual consistency, making these four fundamentals essential knowledge for developers and operators to.
This guide demonstrates how to horizontally scale a Redis cluster by adding nodes as masters or slaves, configuring them, using redis-cli commands to join or remove nodes, and handling special cases such as removing a failed node, all with practical code examples.
