In the era of big data, DBAs face higher demands and NoSQL technologies have risen, so this article shares GeTui's KV storage architecture evolution, operational challenges, NoSQL selection criteria, Codis+ enhancements, Aerospike evaluation, monitoring practices, and best‑practice recommendations for scalable database operations.
This article provides a concise overview of three data storage solutions—Hive, MongoDB, and Redis—detailing their core concepts, operational principles, typical use cases, and key characteristics to help developers choose the appropriate technology for various workloads.
The article details Zhihu's internally built Redis platform, covering its architecture, instance types, high‑availability mechanisms, migration from client‑side sharding to Twemproxy, deployment on Kubernetes, scaling strategies, monitoring tools, and future upgrades, providing valuable insights for backend engineers.
The Redis community is urging a rename of the master‑slave replication terminology due to social concerns, but the project's lead highlights significant compatibility costs, outlining short‑term compromises and long‑term redesigns while balancing technical feasibility and community expectations.
This article explains the principles, requirements, and implementation details of distributed lock services, comparing Redis and ZooKeeper approaches, and introduces SharkLock's design built on SharkStore with Raft-based replication, covering lock acquisition, release, reliability, scaling, and failover mechanisms.
This article explains the principles of distributed locks, compares Redis‑based and ZooKeeper‑based implementations, discusses their limitations, and introduces the SharkLock system built on SharkStore with Raft‑based replication, detailing its reliability, dead‑lock prevention, and safety mechanisms.
This article explains the architecture and step‑by‑step workflow of QR code login, covering how the web front‑end, mobile client, and server (including Redis storage and token verification) cooperate to generate a QR code, poll for authentication, and complete a secure user login.
This article provides a comprehensive overview of Redis as a high‑performance, in‑memory key‑value store, explaining its data structures, persistence options, replication, benchmark results, and a wide range of real‑world scenarios where Redis excels over traditional databases.
This article describes the end‑to‑end evolution of a large‑scale order dispatch architecture, covering the shift from simple pool display to algorithmic assignment using data mining, genetic algorithms, timing‑wheel scheduling, and a Redis‑backed implementation to improve delivery efficiency and rider experience.
A comprehensive collection of over 70 interview questions covering Java concurrency, Spring framework, MySQL optimization, JVM internals, Linux command-line tricks, Redis usage, and system monitoring, designed to help backend engineers prepare for technical interviews across major Alibaba subsidiaries.
This article explains how to monitor Redis memory usage with the INFO command, interprets key metrics such as used_memory, used_memory_rss, and mem_fragmentation_ratio, and dives into Redis's internal memory layout, including allocators, redisObject, SDS, and the various object types and their encodings.
This article compiles the most frequently asked Java interview questions—from basic introductions and multithreading concepts to JVM internals, Spring framework details, middleware, database fundamentals, and Redis—providing a comprehensive study guide for job seekers.
This article reviews the common Redis deployment patterns—including single‑instance, master‑slave replication, Sentinel, Cluster and custom solutions—analyzes their strengths and weaknesses, and provides practical configuration tips and recommendations for building reliable, scalable Redis services in production environments.
This article explains Redis’s core concepts, data structures, persistence options, and the reasons behind its exceptional speed—including in‑memory operations, simple data models, single‑threaded design, and efficient I/O multiplexing—while also covering common interview questions about caching and Redis’s threading model.
This article examines five common Redis deployment patterns—single instance, master‑slave replication, Sentinel, Cluster, and custom high‑availability solutions—detailing their architectures, advantages, drawbacks, and practical configuration tips to help engineers choose the most suitable setup for their workloads.
This guide explains how Spring Cloud Gateway replaces Zuul and provides Redis‑based multi‑dimensional rate limiting, covering Maven dependencies, YAML configuration, custom key resolver beans, stress testing, Redis key monitoring, core Java implementation, and the underlying Lua script.
This article explains Redis's core concepts, data structures, persistence options, and why its in‑memory, single‑threaded design combined with multiplexed I/O makes it exceptionally fast, while also covering common interview questions and practical scaling tips.
On August 4 2018, Didi Open Source and the Open Source Database Forum hosted a salon where five industry experts presented the latest advances in open‑source databases—covering Redis multi‑data‑center deployment, MySQL InnoDB Cluster, streaming‑processing architecture, PostGIS GIS solutions, and Redis 5.0 features—followed by a Q&A, a prize draw, and a showcase of Didi’s growing open‑source portfolio.
This article provides a comprehensive overview of caching in large distributed systems, covering CDN, reverse‑proxy, local and distributed caches, popular implementations such as Ehcache, Guava, Memcached and Redis, common pitfalls like consistency and avalanche, and practical solutions with real‑world case studies.
The article presents a detailed case study of the 58 Cloud DB Platform, describing its architecture, automated workflow using Celery and Ansible, and intelligent features such as server selection and alarm merging powered by machine‑learning, highlighting how it streamlines MySQL, Redis, and MongoDB operations for developers and DBAs.
This article explains why distributed caching is essential for high‑concurrency systems, outlines typical use cases, compares Memcached and Redis across features and performance, and discusses common problems such as cache avalanche, penetration, warm‑up, update strategies, and degradation.
Redis Cluster is a distributed system that partitions its keyspace into 16,384 hash slots across up to 16,384 nodes, enabling automatic sharding, slot migration, replication, and high‑availability features such as automatic node discovery, master‑slave election, and online resharding without service interruption.
This article explains the structure of magnet links, the role of DHT in BitTorrent, and provides a step‑by‑step guide to creating a Python‑based magnet link crawler that stores results in Redis and converts them to torrent files using aria2.
Pika 3.0 introduces a new Blackwidow engine, an efficient write‑to‑file binlog, and a streamlined server layer, all designed to boost performance, reduce storage costs, and fully maintain Redis‑compatible functionality for large‑scale deployments.
This article analyzes the principles, advantages, and drawbacks of distributed locking with Redis and Zookeeper, comparing single‑node and cluster scenarios, discussing RedLock, EPHEMERAL znodes, and practical failure cases to help engineers choose the right solution.
This article explains Redis high‑availability concepts, focusing on persistence mechanisms—RDB snapshots and AOF logging—detailing their triggers, execution flows, file formats, configuration options, performance trade‑offs, and practical guidance for choosing and tuning persistence in production environments.
The paper presents a real‑time computation architecture on Alibaba Cloud Blink that scores and ranks non‑timeline feed items within a sliding 72‑hour window, updating rankings every few minutes, using Redis ZSET for fast retrieval, and discusses scaling optimizations such as interval tuning and external join‑and‑rank services.
The article details how Redis’s incremental rehashing can double memory usage and trigger massive key eviction and scan inconsistencies in large‑scale clusters, explains the underlying dictionary structures, demonstrates the cursor bug when tables shrink, and presents a memory‑guard and scan‑cursor patch that resolves both problems.
This article outlines seven frequent misuse patterns in Redis development—such as improper use of collection types, missing expirations, oversized values, inefficient batch operations, unnecessary requests, poor key naming, and unsafe commands—provides real‑world case analyses, and offers practical recommendations to improve Redis health and performance.
This article explores Redis’s advanced features—including data types, master‑slave, sentinel, and cluster architectures, transaction handling, RDB/AOF persistence, pub/sub messaging, and a practical e‑commerce search case study—providing design insights and best‑practice configurations for high‑availability and performance.
This comprehensive guide explains what Redis is, its advantages over memcached, supported data structures, eviction policies, clustering options, persistence mechanisms, memory optimization techniques, and practical use‑cases such as caching, queues, leaderboards, and pub/sub, providing essential knowledge for developers and architects.
This article explains how to design and implement a high‑throughput, second‑level accurate coupon push notification service using Redis Sorted Sets, a distributed task cluster, dynamic queue configuration, and load‑balancing to handle millions of users within a minute.
This article provides a comprehensive overview of Redis, covering why it is used, its performance advantages, data structures, expiration and eviction strategies, cache‑database consistency, handling cache penetration and avalanche, and approaches to concurrent key competition.
This article explains why auto‑increment primary keys are preferred in MySQL, how B+Tree and hash indexes differ, the benefits of composite and partitioned indexes, isolation levels, MVCC, row‑level locking, triggers, stored procedures, optimization tips, MyISAM vs InnoDB, table design guidelines, and also covers Redis architecture, persistence, replication, and eviction policies.
This article explains how to design and deploy a fault‑tolerant Redis architecture using master‑slave replication, multiple Sentinel instances, and a virtual IP so that the service remains available despite process crashes, server outages, or network partitions.
This guide explains how to implement global rate limiting for high‑traffic Spring Boot applications by using Redis caches and MySQL storage, covering request interception, Redis key structures for limits and counters, and dynamic configuration for adding, updating, or deleting limits.
This article provides a comprehensive overview of Redis, covering its performance benefits, single‑threaded speed, data types, expiration policies, memory eviction strategies, consistency challenges with databases, and practical techniques for handling cache penetration, snowball effects, and concurrent key conflicts.
This tutorial explains how to set up a six‑node Redis cluster (three masters and three slaves) on one Linux VM by creating separate directories and configuration files for each instance, installing Ruby tools, starting the instances, and using the redis‑trib.rb script to create and verify the cluster.
This article explains how to build a highly available Redis service using Sentinel, discusses failure scenarios, compares single‑instance, master‑slave, and multi‑Sentinel architectures, and provides practical guidance on deployment, VIP handling, and operational considerations.
This article explains how to design and implement a highly available Redis deployment using master‑slave replication, multiple Redis Sentinel instances, and a virtual IP to provide seamless failover while maintaining simple client connectivity, covering failure scenarios, architecture choices, and practical configuration tips.
This tutorial demonstrates how to quickly build a modern Java web application using Spring Boot, integrate MyBatis as the ORM, configure Redis as a second‑level cache, and write unit tests with H2, providing step‑by‑step code and configuration details for backend developers.
This article shares the design and implementation of a lightweight, robust, and low‑intrusion monitoring management system for microservice traffic, detailing data collection via client filters, Redis‑based structured storage, alerting, rate‑limiting, degradation, and authorization mechanisms, and discusses performance optimizations and future improvements.
This article explains how to design a highly available Redis service using Sentinel, compares four deployment architectures, discusses failure scenarios and quorum requirements, and shows how a virtual IP can provide a single‑point access while ensuring continuous service.
The article outlines Redis 5.0's major new capabilities—including Streams, module APIs, enhanced RDB metadata, cluster management improvements, new sorted‑set commands, active memory defragmentation, HyperLogLog upgrades, better memory reporting, HELP sub‑commands, connection performance, bug fixes, and Jemalloc 5.1—while also detailing important migration notes from version 4.0 and providing a reference link to the Streams introduction.
This article analyzes the recent surge of Redis unauthenticated attacks that install a worm, use pnscan for lateral scanning, modify system settings, and launch cryptocurrency mining, while providing detailed script breakdowns and remediation steps.
This article provides a comprehensive review of Redis, covering why it’s used, its performance advantages, single‑threaded speed, data types and use cases, expiration policies, memory eviction strategies, consistency challenges, and practical solutions for cache penetration, avalanche, and concurrent key competition.
This article outlines Alibaba Cloud Redis development guidelines, covering key naming conventions, value design, command usage, client configuration, lifecycle management, and recommended tools, providing practical recommendations to avoid common pitfalls, improve performance, and ensure reliable operation of Redis in production environments.
This article compares several Redis cluster solutions—including Codis‑style architecture, Alibaba Cloud ApsaraCache, Baidu BDRP 2.0, JD's custom implementation, the official Redis Cluster, AWS ElasticCache, and Baidu Tieba's ksarch‑saas—detailing their components, sharding methods, migration strategies, and deployment scenarios.
This article demonstrates several methods for enabling a web container to communicate with a Redis container in Docker, covering the deprecated link approach, three net-based techniques, and the recommended custom network solution, while highlighting their advantages and limitations.
This article explains how Redis uses a dual‑hashtable structure and a progressive rehash process to handle hash collisions, detailing the rehash conditions, migration steps, and performance implications for in‑memory key‑value storage.
This article explains the principles of distributed locks, discusses why they are needed in distributed applications, and provides a complete Java implementation using Redis’s NX and EX parameters, including lock acquisition, blocking and non‑blocking modes, unlocking with Lua scripts, configuration, usage examples, and testing strategies.
The article investigates massive packet loss in Meituan‑Dianping's Redis service despite 10 Gbps NIC upgrades, traces the issue to kernel receive‑buffer drops and single‑CPU interrupt handling, and presents a step‑by‑step optimization using backlog tuning, CPU and Redis affinity, and NUMA‑aware placement to eliminate drops and improve latency.
This article walks through building a Java‑based flash‑sale (秒杀) service, diagnosing overselling issues, and progressively enhancing it with optimistic locking, distributed rate limiting, Redis caching, and asynchronous Kafka processing to achieve higher throughput and data consistency under heavy concurrency.
This article explains why distributed caching is essential for high‑traffic services, presents three programming approaches (direct code, Spring‑Data‑Redis injection, and annotation‑based), compares three cache‑access patterns, details sharding models, outlines smooth and offline migration steps, and addresses cache penetration, concurrency, avalanche, and transaction support with concrete code examples.
This article explains Redis's memory model—including memory statistics, allocation, object structures, internal encoding, and practical optimization techniques—so developers can accurately estimate memory usage, reduce fragmentation, and choose the most efficient data representations for high‑performance applications.
Meipai’s live‑stream bullet‑comment platform progressed from an initial HTTP‑polling design supporting one million users, through a high‑availability dual‑room architecture, to a scalable long‑connection system with gRPC routing, dynamic degradation, and caching, solving message ordering, Redis bottlenecks, and ensuring seamless user experience.
Ctrip’s real‑time user behavior service, a core foundation for recommendations, ads, and user profiling, was redesigned with a Java‑based stack (Kafka, Storm, Redis, MySQL) to achieve millisecond‑level latency, high availability, and ten‑fold scalability across processing and output flows.
This article explores the concept of short URLs, their practical applications such as social media and QR codes, discusses various generation methods, presents algorithmic designs like incremental ID encoding and caching strategies, and provides a reference implementation for building a reliable URL shortening service.
This article explains Redis’s memory model—including memory statistics, allocation, object structures, internal encodings, and practical optimization strategies—providing detailed insights into how Redis stores data, manages memory fragmentation, and how developers can estimate and reduce memory usage for high‑performance deployments.
This article explains how to implement a shopping cart in Java by handling four login scenarios, defining BuyerCart and BuyerItem beans, using JavaScript and Spring MVC controllers to add items, persisting cart data in cookies or Redis, converting objects to JSON with ObjectMapper, managing sessions, and validating stock before checkout.
The article explains the challenges of protecting long‑connection services from abuse and presents a one‑time secure token architecture—including gateway SDK, token generation, Redis caching, and verification modules—to ensure authentication, prevent replay attacks, and improve service robustness.
This article explains how to define high availability for Redis, enumerates typical failure scenarios, compares four deployment patterns—from a single instance to a three‑sentinel setup—and provides practical steps, diagrams, and tips for achieving reliable Redis service using Sentinel and virtual IP failover.
This step‑by‑step guide walks you through setting up the ELK stack on CentOS 6, covering Elasticsearch repository configuration, Java installation, Elasticsearch tuning, Logstash pipelines, Kibana deployment, Redis integration, and practical log collection for system, Apache, Nginx, and MySQL logs.
This guide explains the session‑sharing problem caused by load balancing, introduces Redis as a shared storage solution, and provides step‑by‑step instructions—including php.ini changes, runtime ini_set calls, and a custom session‑handler class—to configure PHP to store sessions in Redis, with code examples and verification commands.
This article introduces Redis as a key‑value caching system, compares it with MongoDB and Memcache, explains installation, shows how to use the redis‑py Python client—including direct connections, connection pools, and basic data‑type operations—and provides code examples for setting and retrieving values.
This article compares the three most common distributed cache solutions—Redis, Memcached, and Alibaba's Tair—across nine technical dimensions, then dives into Redis fundamentals, high‑availability setups with Sentinel, and cluster sharding to help engineers make informed cache‑selection decisions.
This article explains Redis's two persistence methods—RDB snapshots and AOF append‑only logs—including their operation, configuration options, advantages, disadvantages, and guidance on choosing the appropriate strategy for data durability and recovery.
This article explains Redis's dictionary structure, the conditions that trigger rehashing, the step‑by‑step incremental rehash process, and provides the core C implementation code, illustrating how Redis maintains high performance while resizing its hash tables.
In this interview, Redis China User Group chair Zhang Donghong shares the database’s key features, version history, data types, high‑availability options, clustering mechanics, automation challenges, future trends, and practical advice for beginners, illustrating how Redis powers massive online services.
This guide provides step‑by‑step instructions for securing Redis with a password, recovering MySQL master‑slave replication, redirecting HTTP to HTTPS in Nginx, defending Linux servers against attacks, configuring Zabbix monitoring for MySQL, and various Nginx and MySQL configuration tricks.
This document provides a comprehensive step-by-step guide to installing and configuring Redis on Linux and macOS, covering package download, compilation, service setup, and operational configuration.
This article explains how to correctly configure JedisPool and its underlying GenericObjectPoolConfig, provides Maven dependency details, demonstrates pool initialization and usage patterns, and offers practical recommendations for maxTotal, maxIdle, minIdle, idle monitoring, and warm‑up to ensure stable and efficient Redis operations in Java applications.
This guide explains why a Redis cluster is needed for large data sets, describes the hash‑slot architecture introduced in Redis 3.0, and provides step‑by‑step instructions—including directory creation, configuration changes, instance startup, Ruby gem installation, and cluster creation commands—to build a functional Redis cluster on a Mac.
Through kernel‑level analysis we discovered that Redis packet loss stemmed from rx_dropped buffer exhaustion caused by interrupt‑handling backlogs, and resolved it by assigning NIC interrupts to specific cores on one NUMA node while binding Redis processes to the other, eliminating loss under dual‑10 GbE load.
This article explains common Redis caching problems—including cache avalanche, cache penetration, cache warmup, cache update, and cache downgrade—and offers practical, entry‑level solutions such as distributed locking, random expiration, bloom filters, pre‑loading strategies, and graceful degradation to keep systems stable under load.
This article explains what Redis is, outlines its common data structures and persistence options, and delves into why Redis achieves exceptionally high performance through in‑memory storage, a single‑threaded event loop, multiplexed I/O, and simple data models, providing interview‑ready insights.
This article explains how to avoid data races in high‑traffic distributed systems by comparing pessimistic and optimistic concurrency control, demonstrating RDBMS row locks and a Redis‑based distributed lock implementation with Python code examples.
This guide introduces Redis as an advanced key‑value store, explains how to start the server and use its CLI tools, and provides detailed command references and demos for strings, lists, sets, sorted sets, hashes, transactions, replication, and pub/sub.
This article details a two‑stage approach for creating a geo‑distributed active‑active infrastructure for large‑scale games, covering a pseudo active‑active design with private lines and smart DNS, followed by a true active‑active solution using Redis Sentinel and MySQL clustering with performance comparisons.
This article explains the challenges of high‑concurrency flash‑sale systems, analyzes the overselling problem caused by simultaneous database updates, and presents four optimization strategies—including unsigned fields, MySQL transactions, file locks, and Redis queues—accompanied by complete PHP code examples and test data.
This comprehensive guide introduces Redis fundamentals, covering its core data structures and essential commands, then delves into performance optimization, high‑availability setups with replication and Sentinel, and scaling strategies using Redis Cluster, providing practical examples and best‑practice recommendations for robust in‑memory data management.
Redis and Memcached are compared across network I/O models, supported data structures, memory management, persistence, consistency, and clustering, revealing Redis’s richer feature set and flexibility while highlighting Memcached’s simplicity and speed, helping developers choose the right in‑memory solution for their workloads.
This article introduces Celery, a flexible Python distributed task queue, explains its architecture—including broker, beat, worker, and result backend—then provides a complete, step‑by‑step setup using RabbitMQ and Redis, covering installation, configuration, task definition, worker launch, custom exchanges, and queue routing.
This article explains why distributed locks are needed in Java applications, outlines the essential conditions they must satisfy, and compares three practical implementations—database‑based, Redis‑based, and Zookeeper‑based—providing code snippets and performance considerations for each.
This article explains how to correctly implement a Redis-based distributed lock in Java, covering essential reliability requirements, step‑by‑step code for acquiring and releasing locks, and detailed analyses of common flawed approaches, ensuring atomicity and proper ownership handling.
Envoy’s extensible filters enable detailed access logging and database sniffing for MongoDB, DynamoDB, and Redis, offering customizable log formats, per‑operation statistics, health checks, and future enhancements such as circuit breaking and retries, while providing configuration guidance for each filter.
The article details iQIYI’s Bubble social service cache architecture, comparing Couchbase and Redis, explaining vBucket design and management UI, and presenting three real‑world optimizations—like‑system key redesign, voting‑system aggregation, and SDK upgrade—along with migration, synchronization, and operational best‑practice recommendations.
This article introduces RDR, an open-source visualization platform developed by Xueqiu's SRE team to safely and efficiently analyze Redis memory consumption by parsing RDB files, estimating key-level memory usage based on internal data structures, and generating intuitive statistical reports for operational optimization.
This article explains how to replace traditional in‑process locks with a Redis‑backed distributed lock service, detailing the overall architecture, server and client designs, management features, lock lifecycle, grading strategies, and fallback options such as database and Zookeeper solutions.
This guide explains Redis’s core features, shows how to design clear key naming conventions, and demonstrates practical applications of the string, hash, list, set, and sorted‑set data types with concrete commands and examples for building fast, memory‑based caches.
This article explains the design and implementation of a space‑efficient Bloom filter using Redis bit operations, covering theory, false‑positive calculations, PHP code, performance testing on billions of daily logs, and optimizations such as pipelining and sharding for large‑scale deduplication.
This article explains the necessity of globally unique and trend‑ordered identifiers for business systems, compares database auto‑increment, UUID, Redis, Snowflake, and MongoDB ObjectId solutions, and outlines their advantages, drawbacks, and best‑practice design criteria.
This article explains Ctrip's design of a globally unique, high‑concurrency user ID generator for sharded MySQL databases, reviews common industry solutions, and details the final optimized approach that combines a MySQL auto‑increment table with in‑memory segment allocation to achieve millisecond‑level response times.
This guide explains Redis's core characteristics, practical key‑naming conventions, and detailed application scenarios for each data type—including strings, hashes, lists, sets, and sorted sets—complete with code examples and performance tips.
This article details the evolution of Qunar's TTS pricing engine from a monolithic V1 implementation with dual-level caching and blocking HTTP interfaces to a scalable V2 architecture featuring service separation, asynchronous processing, CQRS-based rule storage, canal synchronization, Solr and Redis indexing, and Kafka-driven data pipelines.
This article explains why rate limiting is essential for high‑traffic services, describes the token‑bucket algorithm, shows how to use Guava's RateLimiter and Cache for single‑node limits, and presents a Redis‑based solution that works across distributed instances.
This article outlines the shortcomings of using crontab for large‑scale job execution, defines the requirements for a custom distributed scheduler, describes its three‑component architecture (trigger, monitor, management), and details key technical solutions such as process isolation, distributed locking, and log aggregation.
This article describes Ctrip's design of a distributed, globally unique user ID generator for MySQL migration, covering requirements, evaluation of common approaches such as auto‑increment, UUID, Snowflake and Redis, and detailing the final Flicker‑based solution with segment caching using AtomicLong to achieve high concurrency and reliability.
This article shares practical experiences and step‑by‑step guidance on tuning Redis server settings, choosing appropriate eviction policies, limiting client output buffers, disabling risky commands, handling Sentinel‑based master‑slave failover, and selecting the right persistence strategy for reliable and high‑performance deployments.
This article explains how to build reliable distributed locks with Redis, covering essential commands, common pitfalls, improvements using GETSET, Lua scripting for atomicity, and complete Java code examples that address deadlock and unlock vulnerabilities.
