This article explains the basic network programming pattern, introduces epoll as an I/O multiplexing solution for high‑concurrency servers, and demonstrates how Redis 5.0 integrates epoll through its event‑loop abstraction with detailed code examples and debugging tips.
To prevent duplicate OpenID records caused by concurrent synchronization requests in the Fast App Center, this article analyzes the root cause, evaluates database‑level unique indexes versus application‑level distributed locks, and presents a Redis‑based lock implementation with cleanup procedures to ensure data consistency.
This article documents a step‑by‑step performance optimization of a Python web module, covering requirement analysis, environment setup, load‑testing results, database and TCP bottleneck identification, caching strategies, kernel tuning, and the final achievement of 50,000 QPS with low latency.
This article reviews Redis 6.0 and 5.0 new features, compares cluster, master‑replica, and read‑write separation architectures, explains proxy and direct connection modes, and provides Java code for custom connection pools, helping you select the optimal Redis deployment for your workload.
This article explains how Redis implements the “nearby people” feature using its Geo module, detailing the GEOADD and GEORADIUS commands, their underlying algorithms, source‑code flow, and the resulting time‑complexity for adding and querying location data.
This article provides a comprehensive tutorial on preparing the development environment, configuring backend and frontend components, and launching a Jeecg‑boot powered logistics warehouse management system built with SpringBoot, Vue, MySQL, Redis, and related tools.
This article introduces the various Redis eviction strategies—including volatile-ttl, volatile-random, volatile-lru, volatile-lfu, allkeys-random, allkeys-lru, and allkeys-lfu—explains their behavior, shows where they are configured in redis.conf and the initServer source code, and notes the default noeviction policy when memory exceeds maxmemory.
This page aggregates over 300 curated interview question articles covering Java backend development topics such as Spring, MySQL, Redis, concurrency, data structures, and system design, organized by issue numbers to help candidates prepare effectively for technical interviews.
The article explains Redis's two expiration key removal mechanisms—lazy deletion, which removes keys only when accessed, and periodic deletion, which randomly scans and deletes expired keys at regular intervals—detailing their concepts, pros, cons, and underlying source‑code implementations.
This article explains why session sharing is needed in micro‑service architectures, outlines common Nginx reverse‑proxy strategies, and presents four practical solutions—Nginx ip_hash load balancing, Tomcat session replication, Redis centralized cache, and cookie‑based sharing—detailing their implementations and trade‑offs.
This guide explains Go’s built‑in testing framework, assertion libraries, table‑driven and sub‑tests, and demonstrates how to mock functions, structs, interfaces, databases, and Redis using tools such as ngmock, gomock, sqlmock and miniredis, while covering test setup, teardown, coverage handling, and best‑practice insights.
This article outlines the major new features of Redis 6.0 and 5.0, compares various deployment architectures—including master‑replica, cluster, and read‑write separation—explains proxy versus direct connection modes, and provides a Java Jedis connection‑pool code sample.
This article explains what Redis Sentinel is, its architecture, how to configure it in a master‑slave environment, and demonstrates handling of slave and master failures as well as setting up multiple Sentinel instances for high availability.
This article explains how to identify and resolve Redis slow queries by using the slow query log, understanding command complexity, replacing inefficient commands with more efficient alternatives, and configuring slowlog parameters for optimal performance.
This article thoroughly explains why distributed locks are needed, walks through basic Redis lock implementations, exposes deadlock and expiration issues, presents robust solutions with unique IDs and Lua scripts, examines the Redlock algorithm, reviews the Martin‑Antirez debate, and compares Redis with Zookeeper locks.
This article explains how Redis handles memory exhaustion by setting key expirations with commands like expire and pexpire, describes its lazy and periodic expiration strategies, details the eight configurable eviction policies, and dives into the internal LRU and LFU algorithms used for key eviction.
The article explains how to scale MySQL for massive traffic by combining Redis caching, read‑write splitting, data archiving, and sharding techniques, while highlighting their benefits, implementation steps, and potential consistency challenges in modern systems.
The article explains the concepts of cache penetration, cache breakdown, and cache avalanche in Redis‑based systems, describes the performance risks they pose to persistent databases, and presents practical mitigation techniques such as Bloom filters, empty‑object caching, hot‑key permanence, distributed locks, high‑availability clusters, rate limiting, and data pre‑warming.
This article explains how cache penetration occurs in high‑traffic systems and demonstrates how Bloom filters—using minimal memory and fast hash checks—can efficiently prevent such attacks, including construction details, Redis BitMap experiments, and Java Redisson implementation examples.
This article explains why message middleware guarantees at‑least‑once delivery, the challenges of duplicate consumption, and presents both simple and advanced deduplication strategies—including transactional and non‑transactional approaches using relational databases or Redis—to achieve effectively exactly‑once semantics in RocketMQ.
This article explains Redis's Simple Dynamic String (SDS) data structure, its internal layout, how it differs from traditional C strings, and the performance, memory‑reallocation, and data‑format benefits it brings to Redis's key‑value storage.
This article reviews Redis 6.0 and 5.0 new features, compares cluster, master‑replica (single and double replica), and read‑write‑separation architectures, explains their reliability and use‑case scenarios, and provides a Java/Jedis code sample for custom connection‑pool configuration.
The Fast App Center’s duplicate OpenID rows were traced to a non‑atomic check‑then‑insert race condition, prompting the team to evaluate a unique‑index safeguard versus application‑level distributed locking, ultimately implementing a Redis‑based lock to serialize inserts and adding a cleanup job to purge existing duplicates.
This article explains the Redis Simple Dynamic String (SDS) data structure, comparing it with traditional C strings, detailing its struct layout, O(1) length retrieval, pre‑allocation strategy, lazy space release, and provides code examples illustrating how SDS avoids buffer overflows and improves performance.
Discover a comprehensive Redis best‑practice guide covering memory optimization, performance tuning, high reliability, daily operations, resource planning, monitoring, and security, with actionable tips such as key length control, maxmemory settings, lazy‑free, connection pooling, replication strategies, and safe deployment practices.
This article reviews Redis 6.0 and 5.0 new features, compares deployment architectures such as cluster, master-replica, and read-write split, and provides Java connection-pool code examples to help engineers select the appropriate Redis setup for performance, reliability, and scalability requirements.
In distributed micro‑service environments, session sharing is essential to prevent repeated logins, and this article explains four practical solutions—Nginx ip_hash load balancing, Tomcat session replication, Redis‑based centralized sessions, and cookie‑based sharing—detailing their implementations, advantages, and drawbacks.
This article introduces a Java web application that integrates movies, music, and books, detailing its development environment, system architecture, core features such as login, search, and recommendations, and provides step‑by‑step deployment instructions along with the GitHub source link.
This article outlines a universal caching strategy for low‑frequency static data in microservice systems, explaining why in‑memory caches like Redis are needed, detailing a six‑component architecture with services, queues, and consistency checks, and weighing trade‑offs such as cache eviction, persistence, and scalability.
This article explains Redis's ziplist compressed list structure, its internal fields, lookup algorithm, performance characteristics, configuration thresholds for Hash and List types, and demonstrates a real‑world use case with memory‑saving calculations and experimental results.
The article explains why Java's synchronized lock cannot be used for distributed scenarios, demonstrates how to build a Redis‑based distributed lock with setIfAbsent, discusses pitfalls such as server crashes and lock expiration, and presents robust solutions including atomic expiration, thread‑ID verification, lock renewal, and Redisson usage.
This article explores the architecture and implementation of a high‑traffic ticket‑spike service, covering load‑balancing strategies, Nginx weighted round‑robin configuration, local and remote stock deduction using Go and Redis, fault‑tolerant buffering, and performance testing results.
This article explains how to use Redis's SCAN command to iterate over dictionary data, clean up stale keys, understand the command's underlying mechanics during dictionary resizing, and avoid common pitfalls through practical code examples and performance analysis.
This article explains Alibaba Cloud's Redis read‑write separation architecture, comparing star and chain replication models, their performance and scalability trade‑offs, and how transparent compatibility, high availability, and high performance are achieved through redis‑proxy, HA monitoring, and optimized binlog replication.
Redis achieves its remarkable speed through a combination of in‑memory data storage, optimized data structures like SDS, ziplist, quicklist and skiplist, a single‑threaded command model, efficient I/O multiplexing, and sophisticated persistence, replication, Sentinel and Cluster mechanisms that together ensure high performance and reliability.
This article examines the challenges of storing massive DMP data in Redis, analyzes memory fragmentation, key‑value explosion, and latency constraints, and presents practical solutions such as eviction policies, bucket hashing, key compression, and fragmentation reduction to enable efficient in‑memory storage.
This tutorial explains how to integrate Redisson into a Spring Boot application to implement robust distributed locks, covering Redisson's architecture, configuration, code examples, lock types, watchdog mechanism, and practical testing procedures for reentrant, read‑write, and semaphore locks.
This article explores how backend developers can handle intricate e‑commerce search filters by first attempting a monolithic SQL solution, then improving performance with index analysis and query splitting, and finally achieving fast, scalable results using Redis sets, sorted sets, and transaction commands.
This article explains how computers store text using binary, introduces ASCII, Unicode and UTF‑8 encoding rules, discusses the limitations of C‑style null‑terminated strings, and describes Redis's Simple Dynamic String (SDS) data structure, its old and new versions, advantages, and related APIs.
The article compares five practical methods—single‑server deployment, IP‑based restriction, database‑driven task selection, Redis expiration with distributed lock, and Quartz clustering—to ensure that a scheduled job runs only once across multiple servers, outlining each approach's advantages, drawbacks, and implementation details.
This article explains how to design a flash‑sale (秒杀) system that can handle massive traffic spikes by using static page CDN caching, gateway request interception, Redis inventory control, asynchronous order processing, and thorough business, deployment, and data isolation to ensure high performance and stability without affecting regular services.
This article demonstrates how to create a custom @AccessLimit annotation in Spring Boot, implement a rate‑limiting interceptor using Redis, register the interceptor, and apply the annotation to controller methods to restrict request frequency, with full Java code examples.
This article explores the HyperLogLog algorithm for cardinality estimation, tracing its development from Linear and LogLog counting, detailing its Redis implementation with sparse and dense encodings and command workflows, and presenting experiments that demonstrate its memory efficiency and analyze observed error rates versus the theoretical 0.81% standard deviation.
This article explains how to build a location‑based "nearby people" feature by storing coordinates in MySQL, filtering with rectangular bounds, calculating distances in Java, and then scaling the solution with Redis GEO using GeoHash and Sorted Sets for high‑performance proximity queries.
Lettuce, a thread‑safe, Netty‑based Java Redis client supporting synchronous, asynchronous, reactive, Cluster, Sentinel, pipelining and custom codecs, outperforms Jedis’s non‑thread‑safe pooled connections by reducing resource consumption, simplifying Spring integration, and offering advanced features like read‑write splitting, topology refresh, and optional pooling for high‑throughput applications.
This article provides a comprehensive overview of Redis monitoring metrics—including performance, memory, basic activity, persistence, and error indicators—along with recommended monitoring tools, configuration settings, and command-line examples for gathering and interpreting these metrics in production environments.
This article explains Redis master‑slave replication, detailing the replication principles, full‑sync steps, essential configuration file settings, commands to establish replication, verification methods, and a practical test showing data synchronization between master and slave instances.
This article introduces Spring Cache as a unified caching solution that abstracts away the specifics of Redis, Ehcache, and other providers, explains its core concepts, annotations, configuration, and demonstrates practical usage with code examples to eliminate manual cache handling.
This article explains how to implement a real‑time ranking system for a mobile tank game using Redis sorted sets, covering ranking categories, composite scoring formulas, dynamic updates, efficient data retrieval with pipelines, and a complete PHP class example.
This article explains the concept, characteristics, and multiple implementation approaches of distributed locks, focusing on Redis‑based locks and the Redlock algorithm, and provides complete Java code examples using Spring Boot and Redisson for acquiring and releasing locks safely.
The article explains how to abstract remote data location logic using an RPC framework built on Spring and Dubbo, demonstrates proxy injection and service registration, and shows how similar principles are applied to Redis Cluster to reduce request redirection and improve scalability.
This article explains the challenges of flash‑sale traffic spikes and presents a multi‑layered backend architecture—using CDN‑cached static pages, read‑write split Redis, Lua scripts for atomic stock deduction, and Redis‑based message queues—to achieve high concurrency, stability, and fairness.
This article examines the challenges of storing and querying billions of DMP identifiers in Redis, analyzes data characteristics and memory fragmentation issues, and presents practical solutions such as eviction policies, bucket‑based key hashing, and fragmentation reduction techniques to achieve low‑latency, large‑scale caching.
This article explains the limitations of open‑source Redis, introduces Huawei Cloud's GaussDB for Redis with its compute‑storage separation architecture, details its design, implementation, and disaster‑recovery mechanisms, and summarizes the competitive advantages such as strong consistency, high availability, elastic scaling, and superior performance.
This article explains how to use Redis bitmap operations to efficiently implement like, sign‑in, and other binary state features, covering bitmap fundamentals, common use cases, essential commands, Java code examples with Jedis, and range query techniques.
This article introduces Spring Cache as a framework‑agnostic caching abstraction that eliminates manual cache code, explains its core concepts, annotations, configuration options, and demonstrates practical usage with Redis and custom key, condition, and eviction strategies in Spring Boot applications.
This article thoroughly examines the safety of Redis‑based distributed locks, explains basic SETNX locking, explores deadlock and lock‑release problems, presents robust solutions such as atomic SET with expiration, Lua scripts, and unique tokens, and critically compares Redlock with Zookeeper while summarizing expert debates and best‑practice recommendations.
This talk walks through the evolution of containerization—from early chroot and jails to modern Kubernetes—explains Redis’s core features, compares various container solutions for Redis deployment, and offers practical guidance on installation, scaling, monitoring, and fault recovery in both single‑instance and clustered environments.
This guide demonstrates how to add a custom AOP‑based caching layer to a SpringBoot application, using Redis to store frequently queried MySQL table data, defining @AopCacheEnable and @AopCacheEvict annotations, implementing an aspect, handling key generation, expiration, and cache eviction on CRUD operations.
This article explains how to integrate the kk‑anti‑reptile anti‑crawler component into a Spring Boot application, covering system requirements, filter workflow, rule configuration, Maven setup, Redis and Apollo settings, as well as front‑end handling of the 509 response and captcha verification.
This article presents Ctrip Finance's design of a unified high‑availability Redis cache service, covering both eventual‑consistency and strong‑consistency scenarios, the overall architecture, data‑accuracy, completeness and availability mechanisms, lock handling, fault‑tolerant updates, and operational recovery strategies.
This article explains the background, architecture, and replication models of Redis read‑write separation, compares star and chain replication, and outlines its transparent compatibility, high availability, and performance benefits while noting consistency trade‑offs for read‑heavy workloads.
The article explains how to choose appropriate Redis data structures—such as Bitmap, HyperLogLog, Set, List, Hash, and Sorted Set—to efficiently handle massive statistical scenarios like UV counting, ranking, and set‑based aggregation, while providing concrete command examples and performance considerations.
The article outlines Vivo Mall’s new independent promotion system architecture—introducing a unified discount model, flexible pricing engine, and scalable, high‑concurrency design—while detailing technical solutions such as Redis caching, batching, hot‑cold separation, rate‑limiting, idempotency, circuit‑breaker safeguards, and lessons learned from Redis SCAN and hot‑key issues.
This article introduces Redis as a high‑performance, in‑memory key‑value database, explains its core features such as persistence, pub/sub, data structures, and atomic operations, and provides a comprehensive list of commands for keys, strings, hashes, lists, sets, and sorted sets.
This article explains how to obtain a user's city from their IP address in a Java Spring backend, using the QQWry IP database, custom utility classes, and a login interceptor to count visits per city, with complete code examples and deployment considerations.
This article examines the limitations of Redis master‑slave replication, such as manual failover and single‑node bottlenecks, and provides an in‑depth exploration of Redis Sentinel’s architecture, configuration parameters, detection mechanisms, automatic failover process, and best‑practice recommendations for achieving high availability.
This article explains the differences between in‑process caches and external cache services like Redis, outlines the drawbacks of process‑level caching in distributed systems, and provides concrete criteria and strategies for deciding when to migrate to a dedicated cache service.
This article explains how to design and implement a follow/unfollow feature using a MySQL table for persistence and Redis ordered‑set commands (zAdd, zRem, zRange, zCard, zScore) in PHP, covering database schema, code examples, pagination, and status detection.
This article traces the evolution from ASCII to Unicode, explains how Unicode defines universal code points, compares the UTF‑8, UTF‑16 and UTF‑32 encoding schemes, discusses byte order and BOM, and shows practical fixes for common encoding problems in Redis and MySQL.
This article provides a comprehensive overview of caching in large‑scale distributed systems, covering cache fundamentals, classification, major implementations such as CDN, reverse‑proxy, local, and distributed caches, detailed analyses of Memcached and Redis, common design challenges, and real‑world industry solutions.
This article walks through the challenges of implementing a multi‑criteria product search for a shopping site, compares a naïve SQL solution with optimized query splitting, and then shows how Redis sets, sorted sets, and transactions can dramatically improve performance while adding pagination and update handling.
The article proposes a comprehensive microservice‑based caching solution for low‑frequency static data such as vehicle models and user profiles, detailing why caching is needed, why Redis and persistent queues are chosen, how consistency checks work, and the trade‑offs compared with simple expiration strategies.
This article explains why caching is used, distinguishes between local and distributed caches, compares popular Java cache libraries, describes Redis and Memcached differences, outlines the Cache‑Aside pattern, and discusses common cache problems such as inconsistency, penetration, breakdown, avalanche, hot‑key detection, and their mitigation strategies.
This article explains a reusable caching architecture for low‑frequency static data in microservice systems, covering why caching is needed, the role of Redis, persistent queues, consistency checks, and trade‑offs such as cache expiration and operational complexity.
The case study details how a high‑traffic Dubbo service handling 1.8 billion daily requests suffered periodic circuit‑breaks due to thread‑pool exhaustion, traced to a cache‑bypass bug, Redis setex spikes, and an improperly warmed commons‑pool2 connection pool, and resolved by fixing the bug, scaling Redis, and tuning or downgrading the pool configuration to enable pre‑warming via minEvictableIdleTimeMillis.
The article explains various Redis high‑availability solutions—including Sentinel service discovery, VIP binding, keepalived VRRP, and proxy middleware—for both master‑slave and cluster architectures, and shows how clients can reliably locate the current master node after failover.
This article explains why short URLs are used in spam messages, outlines their benefits, describes the basic generation process, and dives into service design choices such as storage, one‑to‑one mapping, caching, batch issuance, and distributed handling, accompanied by a Java‑Redis implementation example.
This guide walks through upgrading GCC, extracting and installing Redis 6.2.4 on a Linux server, configuring a systemd service, verifying the installation, and provides basic performance tuning tips such as adjusting max connections, memory settings, data compression, and clustering.
This tutorial explains what Redisson is, how it extends Redis with powerful distributed data structures and lock mechanisms, and provides step‑by‑step Spring Boot integration, code examples, and detailed testing of re‑entrant, read‑write, and semaphore locks.
This article explains the theory behind Bloom filters and provides a step‑by‑step guide to integrate a Bloom filter into a Spring Boot 2.3.8 application using Redis, Guava, and custom configuration, including code samples, optimal parameter calculations, and testing of false‑positive rates.
This article traces Redis’s transition from its original single‑threaded design to a multi‑threaded architecture by examining the historical VM thread, the BIO background‑job threads introduced in Redis 2.4 and 4.0, and the network IO threads added in Redis 6.0, complete with source‑code excerpts and detailed explanations of each component’s purpose and implementation.
This article explains how to build a real‑time, dual‑dimension leaderboard for a mobile tank game using Redis Sorted Sets, covering ranking types, composite score calculations, dynamic updates, efficient data retrieval with pipelines, and a complete PHP implementation.
This article compares eight Redis visualization tools—desktop clients, a web app, and an IDE plugin—detailing their features, pricing, platform support, and usability, while also showing how command‑line tricks can enhance JSON handling, helping developers choose the most efficient solution for their workflow.
A Spring‑based service repeatedly hung because Redis connections were never returned to the pool, leading to thread starvation; the article walks through the investigation using top, jstack, Arthas, and code analysis, then shows the proper way to use RedisCallback and release connections to prevent the deadlock.
This article explains the evolution of message‑queue middleware by comparing the basic double‑ended queue implementation, Redis list usage, Kafka’s partitioned log architecture with segment files and sparse indexes, and Pulsar’s compute‑storage separation using BookKeeper, highlighting their designs, strengths, and trade‑offs.
An in‑depth look at how mattsta’s CRCSpeed implementation replaced Redis’s original CRC algorithm, delivering up to four‑fold speed gains, the history of its development from 2014 to its 2020 integration, and the performance impact on RDB generation and cluster slot hashing.
This article compares popular message middleware such as Redis, Kafka, and Pulsar, explaining their underlying data structures, strengths and weaknesses, and how concepts like partitions, replication, cursors, and storage segmentation enable high performance, scalability, and reliability in modern distributed messaging systems.
This comprehensive guide walks you through Redis fundamentals, data structures, persistence, high‑availability, performance tuning, and real‑world caching scenarios, providing the essential knowledge and interview tips needed to ace backend developer interviews focused on Redis.
This article explains how a company extended native Redis to support bidirectional synchronization across multiple data‑center sites, addressing issues such as lack of master‑master replication, data loops, idempotency, write conflicts, and providing a custom rLog design for efficient breakpoint‑resume and performance.
This article examines the challenges of caching low‑frequency static data in microservice systems and proposes a comprehensive solution that combines business services, Redis, persistent queues, and consistency‑checking programs to achieve high‑performance, near‑real‑time data access while mitigating cache‑related risks.
After a week of intermittent API hangs in an internal sandbox, we traced the issue to Redis connection pool blocking caused by missing max‑wait configuration, leading to threads waiting indefinitely; by adjusting Jedis pool settings, using proper connection release, and avoiding unsupported commands, the deadlock was resolved.
This article explains the limitations of local locks in distributed systems and provides detailed implementations of distributed locks using Redis (SETNX, Lua scripts, Redisson) and ZooKeeper (ephemeral sequential nodes), complete with code examples and best‑practice recommendations.
This article explains the drawbacks of traditional high‑latency timeout centers and presents a Redis‑based low‑latency design, detailing task storage, scheduling, topic and queue structures, two‑phase consumption, retry control, and the resulting performance and reliability benefits.
This article explains how to handle duplicate user requests—especially write operations—by using unique request IDs with Redis, computing MD5 hashes of sorted JSON parameters, and providing a Java helper class to reliably deduplicate requests on the server side.
This article walks through Redis's startup sequence, explaining how the server creates a listening socket, registers events with the aeFileEvent system, runs a single‑threaded select‑based event loop, and processes client commands using the Reactor pattern, complete with code examples and diagrams.
This article explains how Redis read‑write separation works, compares star and chain replication architectures, and highlights the benefits of transparent compatibility, high availability, and high performance for read‑heavy, write‑light workloads.
This article explains how to protect data exchange with third‑party systems by using access tokens, timestamps, cryptographic signatures, and duplicate‑submission safeguards, providing detailed Java/Spring Boot examples and code snippets for implementing secure API authentication and request validation.
This article explains how to use Jedis to create and delete a Redis distributed lock, demonstrates a setNX‑based locking strategy with expiration, and simulates a 100,000‑user concurrent order‑抢单 scenario to show lock acquisition, order processing, and release in Java.
This guide walks through building a highly available Harbor container registry across multiple nodes by selecting a shared storage backend, configuring Redis and PostgreSQL as external services, mounting Alibaba Cloud high‑performance NAS via NFS, and exposing the service through Alibaba SLB.
