This article explains the typical reasons behind Redis latency spikes—such as complex commands, big keys, concentrated expirations, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network overload—and provides practical steps and monitoring techniques to identify and resolve each problem.
The October 2020 Spring Data Ockham (2020.0.0) release introduces a new version‑naming scheme, updates to Spring Data Neo4j, JDBC, R2DBC, Redis, adds RxJava 3 and De‑lombok support, and outlines compatibility notes for Spring Boot 2.4 and Neo4j users.
This article provides a comprehensive guide to advanced Redis operations, covering pipeline usage, transaction handling, publish/subscribe mechanisms, key migration techniques, custom command implementation with Jedis, and efficient key scanning methods, complete with code examples and performance comparisons.
This article shares a developer's job‑search journey and detailed interview recap, covering project experience, Java collections, HashMap vs Hashtable, synchronized and volatile, singleton patterns, thread‑pool types, Spring Boot AOP, and Redis caching concepts, illustrated with diagrams.
This article explains how to replace a 29‑day serial processing job for 100,000 string records with a Redis‑backed asynchronous task queue powered by Node.js, PM2 clustering, and distributed locking, achieving a ten‑second runtime for 20 sample tasks.
This guide demonstrates how to use Python's redis module to manipulate all major Redis data structures—strings, lists, sets, sorted sets, and hashes—detailing each command, providing clear code examples, and showing expected output for practical learning.
This article explains why Redis clusters are needed, how CLUSTER MEET builds the network, slot assignment, scaling procedures, client redirection mechanisms, batch operations, fault detection, recovery processes, and common operational pitfalls, providing practical guidance for building and maintaining a robust Redis Cluster deployment.
This tutorial demonstrates how to use Redis SET operations and a Lua script to implement a lottery mechanism, and shows how to integrate the script into a Java Spring application using Spring Data Redis's RedisTemplate for atomic execution.
This article explains how Redis introduced Lua scripting to combine multiple commands atomically, covers Lua basics, data types, control structures, script execution with EVAL/EVALSHA, script management commands, and practical tips for writing efficient, safe Redis Lua scripts.
This guide explains how to use Redis key expiration notifications in a Spring Boot application to automatically close unpaid orders by storing an order‑ID key with a TTL, configuring Redis to emit expiration events, and implementing a listener that updates order status when the key expires.
This article examines the challenges of building a flash‑sale (秒杀) system—such as overselling, high concurrency, request throttling, and database strain—and presents a comprehensive backend design using separate databases, dynamic URLs, static pages, Redis clustering, Nginx, token‑bucket rate limiting, asynchronous order processing, and service degradation strategies.
This article explains common causes of Redis latency spikes, such as high‑complexity commands, large keys, concentrated expirations, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network saturation, and provides step‑by‑step troubleshooting commands and best‑practice recommendations.
This guide walks through the complete deployment of Spinnaker on Kubernetes using Halyard, covering architecture analysis, preparation of Redis, MySQL and MinIO, container image retrieval, BOM preparation, Halyard configuration, external Redis and SQL database integration, authentication, canary analysis, monitoring, and additional settings.
This article provides a comprehensive overview of Redis interview topics, covering persistence mechanisms, cache avalanche and penetration problems, hot and cold data concepts, differences from Memcached, single‑thread performance, data structures, expiration policies, clustering solutions, distributed locks, transactions, and practical troubleshooting tips.
This article details a production incident where Redis memory usage surged due to improper Set serialization, explains the investigation of storage structures and capacity formulas, and outlines a step‑by‑step data migration and cleanup process to restore normal operation.
This article explains the three major Redis cache problems—cache penetration, cache breakdown, and cache avalanche—describes their causes, illustrates solutions such as empty-object caching, Bloom filters, locking, and provides practical code examples and mitigation strategies.
This article explains why Redis, a single‑threaded server, adopts I/O multiplexing to avoid blocking, compares blocking I/O with multiplexed models, and details the internal implementation of select, epoll, and kqueue wrappers that power Redis's high‑performance event loop.
This article explains the concepts of cache penetration, cache breakdown, and cache avalanche in Redis, and provides practical mitigation strategies including null caching, distributed locks, random expiration times, and the use of Bloom filters to reduce database load.
This article explains the internal structure of Redis dictionaries, how elements are added, and how rehash-based resizing works, drawing parallels with Java's HashMap to help interviewees answer related questions effectively in technical interviews.
The article recounts a production outage caused by cloud‑platform network jitter, details step‑by‑step fault diagnosis using logs, APM and monitoring, reproduces the issue with chaos‑engineered Redis/Redisson faults, and outlines how the team turned the incident into a systematic fault‑drill practice.
This article examines the typical reasons Redis latency spikes—such as high‑complexity commands, big keys, concentrated expirations, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network saturation—and provides practical diagnostics and mitigation steps to keep Redis responsive.
This guide explains how to configure Redis Sentinel to monitor master‑slave instances, automatically promote a slave on master failure, and verify the high‑availability setup with detailed configuration files, startup commands, status checks, and failover testing steps.
This page provides a comprehensive collection of links to over a hundred interview‑focused articles covering Java, Spring, Redis, MySQL, concurrency, design patterns, and other backend development topics, organized by issue number for easy reference.
This article compares Redis and Memcached across thread models, data structures, eviction policies, pipelines, persistence, high availability, and clustering, helping developers choose the most suitable in‑memory database for their specific workload and performance requirements.
This article explains the typical reasons for Redis latency spikes—including complex commands, large keys, expiration bursts, memory limits, fork overhead, AOF settings, swap usage, and network saturation—and provides practical steps and commands to identify and mitigate each issue.
This article explains why Redis can become slow, covering typical latency causes such as high‑complexity commands, large keys, concentrated expirations, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network saturation, and provides practical troubleshooting steps and best‑practice recommendations.
This article explains the three major cache issues—penetration, breakdown, and avalanche—describes why they occur in high‑traffic systems, and presents four practical mitigation strategies including Bloom filters, short‑lived empty caches, distributed mutex locks with Redis or Memcache, and resource isolation with Hystrix.
This article explains why using Redis's KEYS command can block other operations, illustrates the underlying single‑threaded execution model, and shows how upgrading shiro‑redis to use the SCAN command avoids performance issues in distributed session management.
This article explains the concept of API idempotency, reviews common solutions, and provides a complete Spring Boot implementation using a Redis‑based token mechanism, custom @ApiIdempotent annotation, interceptor, and supporting services, along with testing and important concurrency considerations.
This article explains how to automatically renew JWT tokens in a front‑end/back‑end separated system by storing tokens in a cache, checking them in a filter, and refreshing them when expired, thereby preventing frequent logins and preserving form data.
The article explains how MySQL stores persistent data while Redis serves read‑only data, outlines read/write request handling, discusses consistency issues in low and high concurrency scenarios, and provides practical solutions such as cache invalidation, queue‑based updates, and deployment considerations.
This article explains why a multi‑level cache combining JVM‑level Caffeine and distributed Redis is essential for modern Spring Boot applications, outlines design challenges, provides step‑by‑step integration instructions, and demonstrates performance gains with benchmark results and core implementation code.
This article explains how Redis Sentinel provides automatic failover and high availability by using master‑slave replication, multiple Sentinel nodes, consensus‑based leader election, and client notification mechanisms to ensure continuous service despite node failures.
This article introduces Redis's advanced bitmap capabilities, detailing the SETBIT, GETBIT, BITCOUNT, and BITOP commands, their syntax, underlying SDS data structure, performance characteristics, storage calculations, and practical use cases such as user sign‑in tracking and online status monitoring.
The article narrates Redis’s journey to implement durable storage, contrasting RDB snapshotting and AOF logging, detailing configuration options, forked processes, and trade‑offs, while illustrating interactions with MySQL’s binlog to highlight persistence strategies and performance considerations.
The article explains how Redis caching boosts high‑concurrency applications by outlining common use cases such as counters, session storage, rate limiting, leaderboards and distributed locks, then details best‑practice guidelines, typical pitfalls like TTL overwrites and cache stampedes, and essential monitoring techniques for performance and reliability.
This tutorial explains how to upgrade a SpringBoot application from a single‑node Redis setup to a Redis cluster by adjusting configuration parameters, adding the correct Maven dependencies, injecting a RedisTemplate with JedisConnectionFactory, and providing a reusable utility class for common Redis operations.
This article explains why Redis latency can suddenly increase—covering high‑complexity commands, large keys, concentrated expirations, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network saturation—and provides practical diagnostic steps and mitigation techniques.
This article explains why native Java locks fail in multi‑node deployments, introduces the concept of a distributed lock, and compares two popular implementations—Redis (including RedLock and Redisson) and Zookeeper (with Curator)—detailing their mechanisms, code examples, advantages, drawbacks, and practical selection guidance.
This article walks through building a two‑level caching system in Java, starting with a generic cache interface, implementing a local Guava cache, then adding a Redis distributed cache, and finally combining them with versioned keys to achieve timely expiration and seamless cache switching.
This article explains why a Redis instance may experience sudden latency spikes, walks through diagnosing the problem with slow‑log and big‑key scans, and provides concrete configuration tweaks, command‑level best practices, and operational guidelines to keep Redis performing at peak speed.
This article examines typical Redis latency spikes—such as complex O(n) commands, large keys, concentrated expirations, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network saturation—explaining how to detect, monitor, and mitigate each issue to maintain high‑performance operation.
This article explains why a high‑performance Redis instance can suddenly experience high latency, covering complex commands, large keys, expiration bursts, memory limits, fork overhead, CPU binding, AOF settings, swap usage, and network saturation, and provides practical troubleshooting and mitigation steps.
This article explains how Redis, created to alleviate MySQL’s read‑heavy load, provides in‑memory caching, various data structures, expiration policies, eviction strategies, Bloom‑filter protection against cache penetration, and techniques to prevent cache breakdown and avalanche, improving overall system performance.
This guide walks you through creating and using a one‑click installation package that sets up essential development services—MySQL, Nginx, JDK, Redis, RabbitMQ, and a SpringBoot jar—on Ubuntu 16.x, detailing directory structure, required prerequisites, individual start/stop scripts, and customization options for small‑scale deployments.
This guide introduces AnotherRedisDesktopManager, a free and visually appealing Redis GUI that supports cluster connections, walks through installation from GitHub, explains key features such as dark mode, command console, and versatile data operations for strings, lists, and hashes, and demonstrates practical cluster usage.
This article explains the concept of API idempotency, outlines common solutions, and provides a complete Spring Boot implementation using Redis and a token mechanism, including custom annotation, interceptor, utility classes, and testing procedures to ensure safe, single‑execution requests.
This article reviews six practical URL deduplication methods—including Java Set, Redis Set, database queries, unique indexes, Guava Bloom filter, and Redis Bloom filter—explaining their principles, providing complete implementation code, and recommending the most suitable approach for different system scales.
This article explains the design and evolution of Redis's Simple Dynamic Strings (SDS), covering the original pre‑3.2 structure, the newer type‑specific headers, the core API functions for creating, clearing, and concatenating SDS objects, and the memory‑reallocation strategy that ensures binary safety and efficient storage.
After an AWS network jitter caused lingering slow Redis requests in a Java project using Redisson sentinel, the team traced the issue through source code inspection, custom Prometheus metrics, chaos‑blade testing, and Arthas debugging, ultimately identifying a connection‑pool bug and submitting a fix to Redisson's master branch.
This article explains the principles of primary keys, compares auto‑increment IDs and GUIDs, introduces the Snowflake ID structure, discusses its benefits and drawbacks, and provides a complete .NET implementation using Redis for dynamic worker‑ID allocation, including handling clock rollback and code examples.
This article explains how Redis Sentinel provides automatic failover by combining multi‑replica deployment, health monitoring, leader election, and distributed consensus to detect master failures, select a new master, promote it, and notify clients, ensuring high availability for Redis databases.
This tutorial walks you through downloading RuoYi-Vue 3.1, creating a MySQL database, importing required SQL files, configuring Redis and application settings, and then launching the Spring Boot back‑end and Vue front‑end so you can access the admin console at http://localhost:81/.
This article explains the concept of caching, why database caching with Redis is needed for MySQL, the consistency challenges it introduces, and compares four practical solutions—TTL, write‑through, message‑queue, and binlog replication—offering guidance on selecting the appropriate approach for different latency and reliability requirements.
This article explains Redis sharding, covering its purpose, various partitioning methods such as range and hash partitioning, implementation approaches like client‑side and proxy‑assisted sharding, their drawbacks, and practical steps for migration and using Redis Cluster or Twemproxy.
This article explains how to design and build a simple two‑level caching solution in Java, covering generic cache interfaces, local caching with Guava, distributed caching with Redis, configuration details, version‑controlled cache keys, and practical usage within a Spring Boot application.
This article examines a real flash‑sale incident where Redis distributed locks expired, causing overselling, analyzes the root causes such as lock safety and non‑atomic stock checks, and presents safer lock implementations, atomic stock operations, and architectural reflections to prevent future failures.
This article compiles common Redis interview questions, compares Redis with Memcached, explains eviction policies, and provides a concise introduction to distributed systems, high‑availability architectures, master‑slave replication, synchronization methods, and Redis‑based distributed lock solutions.
This article explains why caching is essential for high‑traffic MySQL applications, outlines the consistency challenges of using Redis as a cache, and compares four practical synchronization solutions—TTL‑only, write‑through, message‑queue‑based, and binlog‑driven—highlighting their advantages, drawbacks, and selection guidelines.
This article details the business flow analysis, functional decomposition, database schema, API design, and high‑concurrency implementation of a WeChat red‑packet and seckill system, showcasing Redis atomic decrement, Bloom filter usage, Lua scripts, JMeter load testing, and integration with SpringBoot.
This article explains Redis's asynchronous master‑slave replication, covering the three core mechanisms, partial and full resynchronization processes, configuration methods, diskless sync, key expiration handling, replication IDs and offsets, and safety considerations when disabling persistence.
This article details the end‑to‑end design, database schema, Redis atomic operations, Bloom filter integration, JMeter load testing, and SpringBoot implementation for a high‑concurrency WeChat red‑packet (抢红包) service, including flash‑sale (秒杀) techniques and Lua scripts for atomic stock handling.
This article provides an in‑depth technical overview of Redis, covering its core data structures, memory allocation strategies, eviction policies, persistence mechanisms (RDB and AOF), transaction model, sentinel and cluster architectures, Pub/Sub messaging, and multiple approaches to implementing distributed locks.
This tutorial explains how to implement a Redis distributed lock with SpringBoot and Jedis, covering lock creation using SETNX, expiration handling, safe unlocking via Lua scripts, and a 100,000‑user parallelStream simulation of a limited‑stock order‑grab scenario, complete with code samples and results.
The article shows how a Vue login page can request a SpringBoot endpoint that creates a four‑character captcha image, encodes it as a Base64 data URL, returns it together with a UUID, stores the code in Redis with a two‑minute expiration, and validates the UUID during login.
This article explains how to implement distributed session management, transaction handling, and locking mechanisms in Java applications, covering Tomcat‑Redis integration, Spring Session with Redis, various distributed transaction patterns, and both Redis and Zookeeper based distributed locks with complete code examples.
This article presents a comprehensive design of a flash‑sale system, covering business scenario analysis, high‑concurrency problems such as overselling and malicious requests, and detailed front‑end, Nginx, risk‑control, back‑end, database, and distributed‑transaction solutions to ensure reliability and performance.
This article explains how to use Redis and Redisson for distributed locking, introduces an abstract DistributedLock interface for flexible implementations, demonstrates automatic lock release with functional callbacks, and discusses fallback strategies and monitoring to ensure reliability in backend systems.
This article explains Redis server's event-driven architecture, detailing how file events (read/write) and time events are processed, illustrated with state diagrams, pseudocode, and examples that show the interaction, scheduling, and impact on server performance.
This guide explains how to configure Celery to use Redis as both broker and result backend, covering project layout, code setup, task definition, execution flow, task states, and common control operations for asynchronous Python workloads.
This article explains how Redis implements a single‑threaded architecture by using a file event handler built on non‑blocking I/O multiplexing (select, epoll, evport, kqueue), detailing socket event abstraction, the I/O multiplexing program, event dispatcher, and the mapping of various socket operations to specific handlers.
This article explains the two persistence mechanisms of Redis—RDB snapshots and AOF append‑only logs—detailing how each works, their respective benefits such as backup compactness and durability, and their drawbacks including potential data loss windows and larger file sizes.
This article explains three practical ways to implement distributed locks—using a relational database, Redis cache, and Zookeeper—detailing their underlying mechanisms, Java code examples, performance trade‑offs, and a side‑by‑side comparison of strengths and weaknesses.
This article explains Redis Cluster’s architecture, node and slot management, failover and resharding mechanisms, and how they together affect write safety, detailing commands, metadata storage, conflict resolution, and client redirection strategies in distributed environments.
This article explains the fundamentals of backend architecture, covering Maven's settings.xml, front‑back separation, various types of locks (thread, process, distributed), detailed Redis‑based and Zookeeper‑based distributed lock implementations with code examples, session handling in distributed systems, and key Spring‑Redis caching annotations.
Grafana’s new Redis Data Source plugin lets DevOps engineers and DBAs seamlessly connect to Redis instances—whether open‑source, Enterprise, or Cloud—visualize time‑series and core data types, run management commands, and build interactive dashboards using Grafana’s transformations and built‑in panels.
This article walks through configuring Redisson with Maven, demonstrates a simple distributed lock example using Sentinel, lists the Redis commands and Lua script semantics involved, and provides a detailed source‑code analysis of the RLock interface, tryLock, unlock, and forceUnlock methods.
The article shares the author's recent move to Xi'an, discusses the local job market, and provides detailed interview questions and answers on Java backend topics such as Redis replication, Kafka performance, MySQL transactions, and JVM garbage collection to help job seekers prepare effectively.
This article provides a detailed, step‑by‑step tutorial on building a six‑node Redis cluster on a single Linux machine, covering directory setup, configuration files, Ruby‑based cluster tools, instance startup, cluster creation, verification, online scaling, slot rebalancing, and using Redis for session sharing.
This article provides a comprehensive guide to Redis deployment, covering standalone, master‑slave replication, Sentinel high‑availability, and cluster sharding modes, detailing their principles, advantages, drawbacks, and step‑by‑step configuration examples with Maven dependencies and Redis configuration files.
This article explains why short URLs are used in spam SMS, outlines their benefits, describes the basic principle of mapping long URLs to short ones, and details service design choices such as storage, one‑to‑one mapping, high‑concurrency handling, distributed ID generation, and provides a Java implementation using Redis.
The article details the architecture of 58.com’s SSP advertising platform, identifies three key reliability challenges—data consistency, interface regression, and storage synchronization—and presents a three‑layer testing quality system comprising web‑layer validation, service‑layer automated testing, and data‑layer monitoring with concrete tools and future improvement plans.
This article explains several ways to implement scheduled tasks in Java, covering the simple Timer class, the more robust ScheduledExecutorService, Spring's @Scheduled annotation, and distributed solutions using Redis ZSet and key‑space notifications, with code examples and practical considerations.
This article explains how to configure Redis's maximum memory usage, describes the built‑in eviction strategies such as noeviction, allkeys‑lru, volatile‑lru, random and ttl policies, shows how to query and set these policies via configuration files or runtime commands, and details the LRU and LFU algorithms used by Redis, including Java sample code and recent improvements in Redis 3.0 and 4.0.
This article explains three practical implementations of distributed locks—using a relational database, Redis cache, and Zookeeper—detailing their mechanisms, Java code examples, advantages, disadvantages, and comparative analysis of performance and reliability.
This article explains how to use Spring Integration to implement distributed locks across Redis and Zookeeper, detailing the unified lock API, required dependencies, configuration steps, and sample code for both storage backends.
This page provides a comprehensive list of over 150 Java interview question articles, covering topics such as collections, concurrency, JVM, databases, Redis, Spring, and system design, organized by issue numbers for easy reference.
This article explains the concept of distributed locks, compares system classifications based on safety, and provides detailed implementation guides for Redis‑based locks using SET NX EX, as well as exclusive and shared locks using etcd/Zookeeper with proper handling of TTL, leases, and atomic operations.
This article explores practical database designs for app features like likes, comments, and collections, comparing MySQL partition‑plus‑cache approaches with Redis storage and caching solutions, detailing schema definitions, query examples, Redis commands for various scenarios, and discussing scalability and consistency trade‑offs.
This article explains Redis as an open‑source in‑memory data store used for caching, database, and messaging, walks through its evolution from simple HTTP caching to server‑side Redis, and details core features such as persistence, high availability, clustering, data types, transactions, Lua scripting, pipelining, and distributed locking.
This article introduces Redis Pub/Sub messaging, explains its purpose of decoupling publishers and subscribers, demonstrates command-line operations such as PUBLISH, SUBSCRIBE, PSUBSCRIBE, and provides a complete Java Spring Boot example using Jedis to publish and subscribe to channels.
This article explains the challenges of generating globally unique IDs in sharded databases, compares common solutions such as auto‑increment, UUID, Snowflake, and Redis, and presents a practical MySQL‑based design that uses table‑level auto‑increment combined with in‑memory segment allocation to achieve high concurrency, reliability, and performance.
This article explains how to manage sessions, implement distributed transactions, and coordinate distributed locks in Java-based distributed systems, covering practical solutions with Tomcat‑Redis, Spring Session, CAP theory, XA, TCC, message‑based consistency, Redis locks, RedLock, and Zookeeper locks, complete with configuration and code examples.
The article details how New Oriental's Cloud Classroom backend, built with Java, Spring, MySQL, Redis, Kafka, Sentinel, and other modern technologies, scaled to support millions of users and a hundred‑fold surge in demand during the pandemic through architectural optimizations, distributed caching, traffic control, and rapid performance improvements.
This article dives deep into the design and implementation details of Redis cross‑IDC bidirectional synchronization, covering copy‑loop elimination, conflict handling with Last Write Wins and Vector Clocks, tombstone usage, garbage collection strategies, and the challenges of TTL consistency across replicas.
This article demonstrates how to implement real-time hot item ranking, page view counting, and unique visitor estimation using Apache Flink with Kafka sources, sliding windows, custom aggregation functions, and a Bloom filter backed by Redis, providing complete Scala code examples.
This article outlines the latest upgrades to the open‑source Mall project, including migration to SpringBoot 2.3.0, support for Elasticsearch 7.6.2, enhanced ELK log collection, unified Swagger and Redis configurations, and updated deployment guides for Windows and Linux environments.
This article analyzes a real‑world flash‑sale overselling incident caused by unsafe Redis distributed locks, explains the root causes such as lock expiration and non‑atomic stock checks, and presents safer lock implementations and atomic stock decrement strategies to prevent future overselling.
This article explains how to implement automatic idempotency for Spring Boot APIs using Redis, a custom @AutoIdempotent annotation, token generation and validation, and an interceptor, providing step‑by‑step code examples, configuration details, and testing procedures to ensure each request is processed only once.
This guide demonstrates how to integrate Apache Shiro into a Spring Boot application, covering project setup, Maven dependencies, configuration of Redis-backed session and cache management, creation of utility and realm classes, and implementation of role‑based permission controls with example controllers and Postman testing.
