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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 track online users using Redis sorted sets by describing the core ZSET commands (zadd, zrangeByScore, zremrangeByScore, zrem), showing code examples for adding, querying, and cleaning up user sessions, and discussing fingerprint-based identification methods.
By leveraging Redis sorted sets for ordered pagination and hash fields with HSCAN for multi‑condition fuzzy matching, the article shows how to build a cached query pipeline that creates temporary ZSets keyed by pattern, supports efficient page retrieval, and uses expirations and refresh strategies to balance freshness and performance.
This article explains how to build an online user counting feature by leveraging Redis sorted sets (zset) in Java, covering user identification, the core Redis commands (zadd, zrangeByScore, zremrangeByScore, zrem), code examples, and periodic cleanup logic.
This article explains how to build an online user counting feature using Redis sorted sets (ZSET) by detailing the core commands (zadd, zrangeByScore, zremrangeByScore, zrem), user identification methods, and providing Java and JavaScript code examples, while also noting unrelated promotional content at the end.
This article explains how to track online users by assigning each user a unique identifier, storing it in a Redis sorted set with an expiration timestamp, and using zadd, zrangeByScore, zremrangeByScore, and zrem commands together with browser fingerprinting to reliably count and clean up active sessions.
This article explains three common methods for implementing delayed queues with Redis—using key expiration notifications, Zset with scheduled tasks, and Redisson’s RDelayedQueue—detailing their concepts, core code examples, advantages, and limitations for backend developers.
This article explains how to use Redis' Sorted Set and Hash structures to achieve efficient pagination, multi‑condition fuzzy queries, and their combination, while also discussing performance optimizations such as expiration handling and data synchronization strategies.
This article explains how to use Redis Sorted Sets for efficient pagination, leverages Hashes and HSCAN for multi‑condition fuzzy searches, and combines both techniques with optimization strategies such as temporary ZSet expiration and real‑time update handling to build a practical caching‑layer query solution.
This article explains how to use Redis Sorted Sets and Hashes to achieve pagination, fuzzy multi‑condition queries, and their combination, while also discussing performance optimizations such as expiration and update strategies for generated ZSet collections.
This article explains how to achieve efficient pagination and multi‑condition fuzzy searches in Redis by leveraging Sorted Sets for ordered paging, Hashes with HSCAN for pattern matching, and combining both techniques with caching and expiration strategies to optimize performance.
This article provides a comprehensive English guide to Redis’s ten core data types—including strings, hashes, lists, sets, sorted sets, streams, hyperloglog, bitmap, and bitfield—detailing their definitions, typical application scenarios, underlying storage mechanisms, conversion rules, and sample Redis commands with code examples.
This article explains how to design Redis cache for relational list data such as user timelines or news feeds, covering fixed-length caching, consistency, resource utilization, using ZSET structures, handling additions, deletions, queries, and strategies like preloading, retry mechanisms, and asynchronous rebuilding.
This article explains the concept of delayed queues, outlines typical use cases, compares implementation options, and provides a complete Java Spring Boot example that uses Redis Zset to create, manage, and execute delayed tasks with accompanying code snippets and test results.
This article explains three Redis‑based rate‑limiting strategies—using SETNX, sorted‑set (ZSet) sliding windows, and a token‑bucket algorithm with List—provides Java code examples for each method, discusses their advantages and drawbacks, and shows how to integrate them into backend services.
This article explains three Redis-powered rate‑limiting methods—using SETNX for simple counters, leveraging ZSET for a sliding‑window algorithm, and implementing a token‑bucket scheme with LISTs—providing Java code examples, advantages, and practical considerations for high‑concurrency back‑end services.
This article explains the design and implementation details of Redis's Simple Dynamic String (SDS) and the underlying structures of its core collections—List, Set, Sorted Set (Zset), and Hash—covering their memory layouts, advantages, and the conditions that trigger different internal representations.
This article explains how Redis can be used to implement delayed queues, compares its advantages with other solutions such as RabbitMQ, RocketMQ, Kafka, Netty and Java DelayQueue, and provides practical guidance on using sorted sets and timestamps for time‑based task scheduling.
This article examines the floating‑point nature of Redis ZSET scores, the precision limits of Java double values, how Redis stores and retrieves these scores, and practical guidelines for avoiding precision loss when using timestamps or large numeric scores in backend development.