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JD Cloud Developers
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JD Cloud Developers

JD Cloud Developers (Developer of JD Technology) is a JD Technology Group platform offering technical sharing and communication for AI, cloud computing, IoT and related developers. It publishes JD product technical information, industry content, and tech event news. Embrace technology and partner with developers to envision the future.

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Recent Articles

Latest from JD Cloud Developers

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JD Cloud Developers
JD Cloud Developers
Apr 30, 2025 · Artificial Intelligence

How to Keep Recommendation Systems Stable During Sudden Traffic Surges

This article examines the challenges of handling high‑frequency, instantaneous traffic spikes in JD Alliance's recommendation system during major sales events and presents an adaptive, automated degradation and recovery framework that minimizes recommendation loss while maintaining system stability.

Linear Programmingadaptive degradationreal-time monitoring
0 likes · 11 min read
How to Keep Recommendation Systems Stable During Sudden Traffic Surges
JD Cloud Developers
JD Cloud Developers
Apr 29, 2025 · Backend Development

How to Safely Use Java Shutdown Hooks to Clean Up Resources on JVM Exit

This article explains the purpose and inner workings of Java's Runtime.addShutdownHook, walks through the Runtime and ApplicationShutdownHooks source code, demonstrates practical usage with examples, discusses common scenarios, potential risks, and best‑practice solutions for reliable resource cleanup during JVM shutdown.

JVMShutdownHookbackend
0 likes · 9 min read
How to Safely Use Java Shutdown Hooks to Clean Up Resources on JVM Exit
JD Cloud Developers
JD Cloud Developers
Apr 27, 2025 · Artificial Intelligence

Overcoming the Hourglass Effect in Residual Quantization for Generative Retrieval

This paper investigates the “hourglass” phenomenon in residual‑quantized semantic identifiers for generative search and recommendation, revealing that token concentration in intermediate codebooks causes path sparsity and long‑tail distributions, and proposes heuristic layer removal and adaptive token‑pruning strategies that markedly improve model performance.

Generative RetrievalToken Pruninghourglass phenomenon
0 likes · 13 min read
Overcoming the Hourglass Effect in Residual Quantization for Generative Retrieval
JD Cloud Developers
JD Cloud Developers
Apr 25, 2025 · Fundamentals

How Does Go Differ from Java? A Deep Dive into Language Features

This article compares Go and Java across core language features—code organization, visibility, variable and constant declarations, functions, interfaces, data types, reference types, error handling, and control structures—providing Java developers with practical insights for adopting Go in cloud‑native development.

Error HandlingGenericsGo
0 likes · 22 min read
How Does Go Differ from Java? A Deep Dive into Language Features
JD Cloud Developers
JD Cloud Developers
Apr 23, 2025 · Frontend Development

Cut Development Time 40% by Reusing H5 Pages with a Monorepo

This article explains how reusing H5 marketing activity pages with a monorepo workspace can accelerate development by up to 40%, outlines five technical solutions, shows workspace structure and package configuration, and discusses central repository management and its suitability for similar projects.

DevelopmentFrontendH5
0 likes · 3 min read
Cut Development Time 40% by Reusing H5 Pages with a Monorepo
JD Cloud Developers
JD Cloud Developers
Apr 22, 2025 · Artificial Intelligence

How AI Turns 2D Videos into Immersive 3D Spatial Content at Scale

Leveraging 3D vision and AIGC, JD Retail’s R&D team converts abundant 2D video assets into high‑quality stereoscopic 3D space videos through a pipeline that includes monocular depth estimation, novel view synthesis, multi‑branch inpainting, and MV‑HEVC encoding, validated by ICME 2025 and a new StereoV1K dataset.

3D videoAIGCDepth estimation
0 likes · 26 min read
How AI Turns 2D Videos into Immersive 3D Spatial Content at Scale
JD Cloud Developers
JD Cloud Developers
Apr 21, 2025 · Databases

How ClickHouse Local Join Cuts Query Time and Memory Usage in Supply‑Chain Planning

This article explains how moving aggregation logic from in‑memory processing to ClickHouse SQL, synchronizing configuration data, and leveraging ClickHouse ReplacingMergeTree tables with local joins dramatically reduces query latency and memory consumption for large‑scale supply‑chain planning workloads.

ClickHouseDatabase EngineeringLocal Join
0 likes · 13 min read
How ClickHouse Local Join Cuts Query Time and Memory Usage in Supply‑Chain Planning
JD Cloud Developers
JD Cloud Developers
Apr 16, 2025 · Backend Development

Master Spring Cache Annotations: @EnableCaching, @Cacheable, @CachePut, @CacheEvict Explained

This article explains how Spring's caching annotations—@EnableCaching, @Cacheable, @CachePut, and @CacheEvict—work together to simplify cache management, includes Maven dependency setup, configuration class, entity and service code, a full Spring Boot example, test cases, and visual illustrations of cache miss, hit, update, and eviction.

CacheRedisannotations
0 likes · 13 min read
Master Spring Cache Annotations: @EnableCaching, @Cacheable, @CachePut, @CacheEvict Explained