During a Redis version upgrade of the internal R2M cache service, a Biz thread‑pool exhaustion error was traced to JSF threads blocked on a read lock held by a topology‑updater task, revealing a deadlock caused by shared ForkJoinPool usage and missing lock timeouts.
This article introduces Go's built‑in os/exec package, explains its exported types and methods, demonstrates how to run commands synchronously or in the background, capture output, handle pipes, environment variables, working directories, and shows a practical case study using the tempredis library to start a Redis server programmatically.
Redis offers three persistence options—Append‑Only File (AOF) which logs every write, RDB snapshots that capture point‑in‑time data, and a hybrid mode combining both—each configurable with trade‑offs in durability, recovery speed, file size, and performance to suit different application needs.
This guide demonstrates how to create a robust online webpage screenshot service using Python, Selenium, and Flask, incorporating security measures like CSRF protection and domain whitelisting, performance enhancements with Redis caching and rate limiting, comprehensive error handling, resource management, and extensibility for future features.
This article explains how to track online users by storing their identifiers in a Redis sorted set, using expiration timestamps as scores, and demonstrates adding, querying, and cleaning up entries with ZADD, ZRANGEBYSCORE, ZREMRANGEBYSCORE, and ZREM commands in both Java and JavaScript.
This guide demonstrates how to build a Python Flask-based RESTful service that generates various types of unique identifiers—including UUIDs, timestamps, Redis counters, Snowflake IDs, and random strings—while covering installation, code implementation, API endpoints, error handling, rate limiting, and extensibility considerations.
The article explains how Redis, a high‑performance key‑value store, can leverage multithreading for I/O operations, background tasks like UNLINK, and jemalloc memory‑management threads, providing configuration examples and Python code to improve performance in high‑concurrency scenarios while noting the associated CPU cost.
Learn practical methods to identify users who exceed three failed login attempts within ten seconds, covering both a MySQL log‑table approach with window functions and a Redis‑based solution with key expiration, plus discussion of performance trade‑offs and atomicity considerations.
This article explains how Redisson leverages Redis, Lua scripts, and Pub/Sub to implement a robust distributed lock in Java, covering lock characteristics, client creation, acquisition, renewal, and release mechanisms with code examples.
The article shows how AI accelerated a chatroom project's development—cutting cycle time, lowering developer skill demands, and delivering over 8% efficiency gains—by auto‑generating boilerplate code, debugging suggestions, and routine components such as API, Redis, MySQL, and WebSocket snippets, while outlining future improvements and a potential additional 10% R&D boost through integrated AI tools.
This article demonstrates how to build a dynamic IP blacklist using Nginx, Lua scripts, and Redis, covering requirements, environment setup, design options, nginx.conf configuration, detailed Lua code, summary of advantages, and extensions such as use cases and advanced features.
This article investigates a Redis Sentinel failover anomaly in version 7.4.0 where the sentinel repeatedly elects a failed master, explains the underlying s_down/o_down states, examines network, configuration, and ACL settings, and resolves the issue by adjusting Pub/Sub permissions to allow proper failover.
This article examines why many large‑scale systems avoid the traditional delayed double‑delete cache‑invalidation strategy, explains its critical drawbacks, and presents alternative lease‑based and version‑based approaches with Lua scripts and Java wrappers for Redis to achieve stronger consistency.
This article examines a real‑world incident where oversized and frequently accessed Redis cache keys caused cache penetration and network bandwidth saturation during a high‑traffic promotion, analyzes the underlying reasons, and presents concrete solutions and preventive measures for backend systems.
This guide explains how to create a dynamic IP blacklist that blocks malicious crawlers or users by configuring Nginx with Lua scripts and a Redis store, covering requirements, environment setup, design choices, configuration files, Lua code, and advanced usage scenarios.
Redis Sets are unordered collections of unique strings backed by hash tables that provide O(1) add, delete, and lookup operations, automatically switch to a compact integer array (intset) for small integer-only sets, and are ideal for deduplicated data and fast set operations such as intersection, union, and difference, exemplified by computing common friends in social applications.
This article explains the fundamentals of workflow engines, compares process and rule engines, discusses why and how to use message queues (including delay levels and popular MQ products), and details Redis data structures and memory‑eviction policies, providing practical guidance for backend system design.
This article describes how a legacy SSM‑based backend reporting service was refactored by archiving log data, leveraging Redis for hourly counters, and scheduling synchronization tasks to dramatically reduce query time for millions of records without adding external processing frameworks.
The article explains that Redis's KEYS command scans all keys, blocks the server for seconds, can trigger failover issues, and provides faster alternatives like SCAN or storing keys in a set, while also showing how KEYS works in a Redis Cluster and its real‑world latency measurements.
This article explains the challenges of thread synchronization in distributed systems, introduces the concept of distributed locks, compares common implementations such as Redis, Zookeeper, and databases, and provides robust Java and Lua solutions to ensure atomicity, avoid deadlocks, and support lock renewal.
This article explains how to prevent duplicate data submissions in a Spring Boot application by designing an idempotent mechanism using AOP and Redis, covering the concept, design strategy, custom annotation, aspect implementation, and a simple test controller.
This article details how a legacy reporting module suffering from slow page loads was refactored by archiving log data, caching hourly counts in Redis, and using scheduled synchronization to dramatically improve query performance without adding new middleware.
This article explains why Redis, an in‑memory database, needs persistence, compares the four official persistence options (RDB, AOF, RDB+AOF, and no persistence), details their configurations, performance trade‑offs, and introduces the hybrid RDB+AOF approach for balanced durability and speed.
This article breaks down Shopee's backend interview experience, covering salary offers, location details, interview difficulty, and a comprehensive review of essential topics such as network protocols, rate‑limiting algorithms, Java thread pools, Redis eviction and expiration strategies, MySQL isolation levels, index structures, MVCC, slow‑query optimization, redo vs binlog, and RocketMQ distributed transaction, ordering, and backlog handling, while also linking to useful open‑source projects and video tutorials.
This article presents a comprehensive overview of the author's current technology stack, covering frontend frameworks like React and Next.js, mobile development with React Native, TypeScript usage, backend tools such as NestJS, Prisma with MySQL, Redis caching, and frontend engineering practices.
This tutorial introduces Spring Cloud Gateway, explains its core features and Actuator integration, and provides step‑by‑step practical examples for viewing routes, global filters, route filters, refreshing routes, managing routes via REST endpoints, creating and deleting routes, and sharing routes with Redis, all accompanied by code snippets and configuration details.
This article explains how to prevent brute‑force password attempts by locking an IP after three failed logins using a Spring Boot backend, Redis for distributed counters, and a Lua script to ensure atomic increment and expiration, while also providing a simple HTML login page for the front end.
This guide explains why a production Redis cluster may show intermittent timeouts and READONLY errors, analyzes root causes such as network jitter, resource saturation, and costly commands, and provides step‑by‑step troubleshooting and configuration fixes to restore stability and performance.
Redis can appear slow for many reasons—including baseline latency differences, high‑complexity commands, big keys, concentrated expirations, memory limits, fork overhead, huge pages, CPU binding, swap usage, memory fragmentation, and AOF configuration—so this guide explains each cause, how to diagnose it, and practical optimization steps.
This article explains how to prevent duplicate order submissions in e‑commerce systems by using a token mechanism and Redis‑based distributed locks within a Spring Boot backend, detailing the workflow, code implementation, and best‑practice optimizations for idempotent processing.
This article explains the concept of request debouncing, identifies which API endpoints need it, and provides a detailed tutorial on implementing distributed debounce using shared Redis cache or Redisson locks in a Spring Boot backend, complete with annotation design, unique key generation, and code examples.
This article compiles detailed backend interview notes covering salary expectations, OS stack vs heap differences, process and thread concepts, DNS resolution, ping protocol, MySQL indexing and locking mechanisms, Redis performance characteristics, Kafka throughput optimizations, and Docker's underlying implementation.
This guide presents eleven practical recommendations—including avoiding large keys, disabling costly commands, using UNLINK, enabling lazy free, batching operations, and configuring connection pools—to help developers maintain Redis performance and prevent latency spikes in production environments.
This course provides an in‑depth exploration of process fundamentals, socket programming with TCP/IP, Nginx and FASTCGI communication, host‑to‑network byte order conversion, and Redis basics, targeting backend engineers, system administrators, and network engineers seeking comprehensive backend development skills.
This article explains the probabilistic Bloom filter data structure, its characteristics and typical use cases such as cache‑penetration prevention, details its simple implementation steps, demonstrates how Redis (via Redisson) provides built‑in Bloom filter support with Java code examples, and summarizes its practical benefits.
This article explains what a feed stream is, why it exists, how it evolved from RSS to modern social feeds, classifies different feed models, outlines the challenges of real‑time delivery, and provides a detailed backend architecture, data structures, storage design, pagination strategy, and core publish‑read workflows to help engineers build reliable, high‑performance feed systems.
This guide explains how to install the Webman rate‑limiter plugin, configure its drivers (memory, APCu, Redis), and use annotation‑driven limits in PHP controllers, including custom keys, whitelist IPs, and manual limiter checks.
Redis Labs announces the return of its founder Antirez, who shares his reasons for rejoining, discusses the recent licensing shift, reflects on his past projects, and outlines future plans for AI integration, vector indexing, and community engagement within the Redis ecosystem.
This article explains how Laravel 11's built‑in rate‑limiting service can be configured with custom, global, segmented, and Redis‑backed limits, showing code examples for defining limiters, custom responses, multiple constraints, and applying them to routes via middleware.
The paper proposes a multi‑level storage architecture for Bilibili’s comment service that replaces TiDB with a custom KV store (Taishan) and Redis caching, introduces unstructured indexes, CAS‑based consistency, real‑time and offline reconciliation, and a hedged degradation strategy to boost reliability, read throughput, and scalability during traffic spikes.
This tutorial walks through creating a simulated SMS verification system using Spring Boot, Redis, and scheduled tasks, covering requirements, dependency setup, controller and service implementation, rate limiting, code expiration, validation logic, and daily reset of usage counters.
This article explains why storing daily sign‑in data in a traditional database can cause performance issues at scale and demonstrates how Redis bitmap, a memory‑efficient bit‑level structure, can record and compute continuous user sign‑ins both by date and by user.
This article examines the pitfalls of using Redis key‑expiration notifications for delayed business actions, presents a Docker‑based benchmark, provides Spring‑Boot code for scheduling and listening to expirations, and analyzes how notification latency grows as the number of keys increases.
This article examines the stability challenges of an e‑commerce inventory platform—including workflow complexity, database hotspots, and high‑frequency calculations—and details comprehensive solutions such as traffic splitting, gray releases, Redis caching, data consistency mechanisms, rate limiting, and monitoring enhancements that together improved throughput by 24× and reduced latency dramatically.
This article compiles sixteen practical Redis use‑cases—from caching and distributed locks to rate limiting, bitmaps, shopping carts, timelines, queues, likes, tags, filtering, follow/fan relationships, and leaderboards—providing code snippets and command examples to help backend developers design scalable systems.
This article explains why COUNT(*) on a large InnoDB table can take seconds while MyISAM returns instantly, explores the underlying storage‑engine differences, and presents six practical techniques—including Redis counters, counting tables with transactions or triggers, parallel read threads, secondary indexes, and SHOW TABLE STATUS—to dramatically speed up row counting in MySQL.
This article explores the core functions of e‑commerce shopping carts and compares client‑side storage methods such as Cookies and LocalStorage with server‑side solutions like Redis and MySQL, offering guidance on choosing the appropriate approach based on business scale and reliability requirements.
This article examines why using Redis key‑space expiration notifications for delayed job execution is unreliable, compares common approaches such as message‑queue delayed delivery, RabbitMQ dead‑letter queues, time wheels, and Redisson DelayQueue, and provides practical recommendations for robust timeout handling in e‑commerce systems.
Drawing on Kuaishou’s experience, this article examines whether stateful services like Redis belong on Kubernetes, outlines the benefits and risks, and details a cloud‑native solution using custom workloads, KubeBlocks, and a federated cluster architecture to achieve scalable, reliable Redis deployments.
Distributed locks synchronize multiple services across nodes, and can be implemented using Redis’s fast, AP‑oriented SET‑NX with automatic TTL renewal or Zookeeper’s CP‑oriented ephemeral sequential nodes, each offering distinct trade‑offs in performance, consistency, and suitability for various workload requirements.
This article explains Redis bitmap data structures, introduces the main bitmap commands (BITSET, BITGET, BITCOUNT), and provides a complete PHP example that demonstrates how to record user sign‑ins and count them efficiently using Redis bit operations.
The article describes a kernel‑level hot‑key detection module for Redis that tracks per‑second access counts via an O(1) LRU queue, flags keys exceeding configurable thresholds, and provides real‑time subscription alerts and queryable logs, overcoming the latency and overhead limitations of existing detection methods.
This article demonstrates how to achieve real‑time synchronization of MySQL data to Redis using Spring Boot 3, the open‑source mysql‑binlog‑connector‑java library, and optional JMX exposure, providing step‑by‑step setup, code examples for parsing binlog events, listening to changes, and configuring Maven dependencies.
Learn step‑by‑step how to deploy redis‑exporter, configure Prometheus to scrape Redis metrics, and create a comprehensive Grafana dashboard, enabling you to instantly visualize Redis performance, detect issues early, and maintain high availability in fast‑paced internet environments.
This article explains why syncing Redis with MySQL is essential for performance and consistency, and details three implementation methods—database triggers, application-level double writes, and message queues—providing code examples, practical tips, and key considerations for reliable data synchronization.
The article surveys feed‑stream systems—from their RSS roots to modern social‑media timelines—explaining classifications, core terminology, and a high‑performance architecture that uses Redis ZSET inboxes, write‑ and read‑diffusion, soft‑delete consistency, and last‑id pagination to handle massive real‑time writes, big‑V fan‑out, and efficient publishing and reading.
This article presents a detailed case study of four backend design alternatives for importing Excel data—ranging from synchronous processing to asynchronous pipelines with thread pools, message queues, and Redis locks—analyzing their advantages, drawbacks, and suitable scenarios.
This article explains the concept of idempotency, identifies which HTTP operations are naturally idempotent, describes why idempotency is needed in scenarios like timeout retries, async callbacks and message queues, and provides a complete Spring Boot implementation using a custom annotation, Redis storage, AOP interception, token generation and example controllers.
The article traces Bilibili’s customer‑service seat scheduling system from its initial balanced‑distribution algorithm and Redis‑based priority queues for live chat and ticket handling, through fairness‑focused saturation limits and virtual‑queue mechanisms, to planned dynamic tuning and expertise‑aware routing for future scalability.
This article introduces RediSearch—a Redis module for full‑text search—detailing its features, performance comparison with Elasticsearch, index‑building and query benchmarks, installation methods (source and Docker), and comprehensive command‑line examples for creating, querying, updating, and managing indexes.
This guide explains how to accelerate applications by deploying Alibaba Cloud Tair (Redis‑compatible) as a cache, covering account setup, one‑click resource stack deployment, cache validation, Locust performance testing, result analysis, and resource cleanup to handle high‑traffic scenarios efficiently.
This article explains how to design a scalable leaderboard using Redis Zset for moderate traffic and a sharded‑key plus local cache architecture for ultra‑high concurrency, detailing synchronization strategies, data flow, and practical implementation steps.
This article explains how to implement request debouncing and distributed locking in a Java backend using Redis and Redisson, covering the definition of debounce, identifying suitable APIs, generating unique keys, and providing complete code examples for both cache‑based and Redisson‑based lock mechanisms.
Cache penetration, a common issue in large-scale websites where malicious or non‑existent key requests bypass caches and overload databases, can cause crashes; this article explains the problem and presents four mitigation techniques—caching empty objects, rate limiting, blacklist mechanisms, and Bloom filters—to protect backend systems.
Redis primarily operates with a single thread using I/O multiplexing (select, poll, epoll) to handle massive concurrent connections, while newer versions introduce optional multi‑threaded networking and use child processes for persistence, maintaining its core single‑threaded design for data processing.
This article explains why API debouncing is crucial for backend Java services, outlines which endpoints need protection, describes how to identify duplicate requests, and provides step‑by‑step implementations using Redis shared‑cache and Redisson distributed locks with concrete code examples and test results.
This article explains three practical approaches—microservice isolation, Redis‑based whitelist, and gateway‑AOP header checks—to restrict APIs to internal calls only, and provides detailed Spring Cloud code examples for the preferred AOP solution.
Redis can become a bottleneck when a hot key concentrates traffic on a single shard; this article explains how to split such hot keys into multiple sub‑keys, distribute them across cluster nodes using CRC16 slot mapping, and implement the approach in high‑concurrency scenarios like coupon grabs or real‑time leaderboards.
This article introduces Bloom filters and Cuckoo filters, explains their probabilistic nature, false‑positive behavior, space‑time trade‑offs, provides Go and Java implementation examples, and discusses practical use cases such as Redis extensions and high‑traffic e‑commerce scenarios.
This article compiles an extensive Python reference covering Python 2 vs 3 differences, essential and advanced libraries, concurrency models, language internals, testing techniques, design patterns, data structures, algorithms, networking basics, MySQL and Redis insights, Linux I/O models, and performance‑optimization strategies, all illustrated with practical code snippets.
The article recounts a recent Hikvision interview, outlining campus salary ranges and providing a technical Q&A that explains Spring Boot’s startup sequence, Spring MVC request handling, MySQL index structures, creation rules, and performance diagnostics, as well as Redis’s in‑memory, single‑threaded architecture and optional I/O threading.
This article explains Redis 4.0's LFU‑based hot key detection mechanism, including its probabilistic counter algorithm, decay factor, and configuration options, and then describes Redis 6.0 client‑side caching with tracking, default and broadcast modes, and related protocol considerations.
The article shows how to avoid database pressure by recording daily comment counts in Redis sorted sets, merging the seven daily sets into a weekly ranking with a union command, and exposing the result through a Spring Boot service and a custom Freemarker tag, complete with code examples and screenshots.
This article walks through the complete process of implementing WeChat QR code login using a Java Spring Boot backend, covering prerequisite configuration, Maven dependencies, configuration classes, QR code generation, callback handling, session storage in Redis, and frontend integration.
This guide walks through installing software on CentOS using source tarballs, RPM packages, and yum, covering terminology, step‑by‑step commands, and practical examples with Redis, RabbitMQ, and Nginx.
This article presents a comprehensive engineering guide for importing one billion 1 KB unstructured log records stored in HDFS or S3 into MySQL, covering data sizing, B‑tree limits, batch insertion strategies, storage‑engine choices, sharding, file‑reading techniques, concurrency control, and reliable task coordination using Redis, Redisson, and Zookeeper.
The article presents a Redis‑based distributed ID generator for Spring Boot 3.0 that uses an atomic INCR on a Redis string to produce compact, monotonic, globally unique numeric identifiers, synchronizes the maximum value with MySQL on startup, and offers high performance, availability, and low storage overhead.
This article explains how to enable cross‑node WebSocket communication in a distributed Spring application by using a message queue (Redis or Kafka) to broadcast messages, tracking user connections with Redis, and providing a complete step‑by‑step implementation with code samples and configuration details.
Learn how to deploy Alibaba Cloud Tair (Redis) with ECS and RDS, verify caching functionality, conduct Locust performance tests, and clean up resources, all through a step‑by‑step guide that demonstrates significant latency reduction and database load mitigation.
Redis achieves millisecond‑level latency by storing all data in memory, using specially optimized data structures such as SDS, incremental‑rehash hash tables, and ziplists, employing a single‑threaded event‑driven model with epoll‑based I/O multiplexing, and streamlining network communication through the compact RESP protocol, compression, and batching, while also offering flexible eviction and persistence strategies.
The article explains how to detect and troubleshoot Redis latency spikes by measuring baseline performance, using slowlog and latency‑monitor, checking network RTT, fork‑induced pauses, huge pages, swap usage, AOF settings, expiration handling, and big‑key problems, providing concrete commands and mitigation steps.
This article recounts five successive performance optimizations applied to a SpringBoot‑Thymeleaf category‑tree API—adding Redis caching, scheduled async refresh jobs, local Caffeine memory cache, gzip compression via Nginx, and Redis data slimming—transforming query latency and scaling QPS from around 100 to over 500.
This article explains three backend strategies—session‑cookie, token, and JWT—to ensure an account can only be active on one device at a time, detailing the workflow, data structures, and Redis integration needed to implement forced logout across multiple endpoints.
Redis’s evolution from linked lists to ziplist, quicklist, and the newer listpack is examined in depth, highlighting their structures, memory‑performance trade‑offs, operational details, and practical guidance for Java developers on choosing the right data structure for different workloads.
This article explains how Redis Bitmap stores binary states using bit arrays, details its commands and use cases, then introduces Bloom Filter's probabilistic set membership, compares their advantages, limitations, and typical scenarios such as cache penetration protection and blacklist filtering.
This article explains how to design a live‑streaming danmaku (bullet‑screen) feature by using Redis Zset as the underlying data structure, limiting the list to the latest ten messages, and handling retrieval via polling APIs or WebSocket, with Kafka for message buffering and a distributed lock to avoid ordering issues.
Redis has launched an enhanced, multi‑threaded query engine that dramatically increases throughput and reduces latency for vector similarity searches, enabling vertical scaling and better support for real‑time RAG applications while maintaining sub‑10 ms response times.
This article explains how Redis implements dynamic string expansion using the Simple Dynamic String (SDS) structure, detailing the sdsMakeRoomFor function, its allocation strategy, type handling, and the architectural changes introduced in Redis 7.0.
This article provides a comprehensive guide to using Alibaba's JetCache in Java Spring Boot projects, covering dependency setup, configuration of local and remote caches, annotation‑based caching, API usage, testing procedures, and troubleshooting common integration errors.
This article introduces Alibaba's JetCache Java caching framework, explains how to integrate it with Spring Boot and Redis, provides detailed configuration and code examples for local, remote, and multi‑level caches, and covers testing procedures and common error resolutions.
A detailed post‑mortem of a Redis outage shows how a traffic surge filled bandwidth, caused massive input and output buffers to consume almost all memory, and led to timeouts, while offering step‑by‑step analysis, memory diagnostics, and practical recommendations to prevent similar buffer‑overflow failures.
This article provides a detailed, practical guide for increasing Redis memory on Linux by adjusting Redis configuration, expanding system swap space, tuning kernel overcommit settings, and monitoring usage with command‑line tools.
This article explores several strategies—timestamp with random numbers, MD5 hashing, UUIDs, and an optimized Base62 conversion combined with Redis‑based locking—to generate short, globally unique CDN file names for an OSS upload platform.
The course provides an in‑depth study of processes, socket communication (including TCP/IP), Nginx with FASTCGI, byte‑order conversion, and fundamental Redis operations, targeting backend developers, system administrators, and network engineers to comprehensively boost their backend development expertise.
PHPCreeper is a high‑performance PHP crawler built on Workerman that leverages asynchronous I/O, multi‑process, distributed deployment and headless‑browser support; this guide covers installation via Composer, core architecture, producer/downloader/parser implementation, Redis configuration and how to start the service to fetch dynamic pages such as weather forecasts.
This guide explains how to implement a Casbin Watcher for distributed policy synchronization using Workerman's asynchronous Redis client in PHP, covering the underlying principles, required interfaces, code implementation, and a complete usage example with publish‑subscribe messaging.
The article describes how an automated resource‑balancing system continuously monitors Redis host memory usage, selects optimal nodes, safely migrates them through a multi‑step process (adding slaves, verifying replication, promoting masters, deleting old nodes), and provides task management and notification features to maintain high availability and reduce manual DBA effort.
Redis 4.0 offers three persistence options—RDB snapshotting, AOF command logging, and a hybrid RDB‑AOF mode—each with distinct configurations, trigger conditions, and trade‑offs, and this guide walks through their principles, practical commands, performance impacts, and recovery procedures with detailed examples.
The article explains how to store and deduplicate billions of identifiers efficiently by using a bitmap backed by Redis and extending it with a Bloom filter implementation in Java, highlighting memory calculations, practical commands, and code examples.
This article demonstrates how to build a flexible API rate‑limiting solution in Spring Boot by combining a HandlerInterceptor, Redis counters, and custom annotations with reflection, covering configuration, code examples, mapping rules, time‑window nuances, path‑parameter handling, and real‑IP considerations.
