Official platform of JD Retail Technology, delivering insightful R&D news and a deep look into the lives and work of technologists.
This article presents an in‑depth analysis of Kafka's native throttling mechanisms, identifies their limitations in large‑scale e‑commerce scenarios, and introduces JDQ's multi‑dimensional, dynamic throttling architecture that ensures stable throughput and priority‑aware bandwidth management across broker failures and traffic spikes.
This article details JD's large‑scale HDFS unified storage implementation, covering cross‑region storage challenges, topology design, asynchronous block replication, flow‑control mechanisms, tiered storage strategies, automatic hot‑cold data migration, and the resulting performance and cost improvements for big‑data workloads.
Eight JD Retail engineers recount their career paths, technical challenges, and personal philosophies, covering topics such as data‑flow tooling, large‑scale architecture refactoring, product‑centric design, AI‑driven unit‑test generation, and the enduring passion that drives their work in software development.
This article explains how the Taro framework adapts React applications to run efficiently on HarmonyOS by converting React components into Taro virtual nodes, then into ArkUI nodes through a three‑step rendering pipeline, detailing runtime principles, hostConfig methods, and C++ implementation examples.
The article examines how large language models are reshaping JD Retail's e‑commerce search and recommendation pipelines, detailing industry evolution, technical challenges such as knowledge hallucination, intent understanding, personalization, cost, and safety, and presenting JD's end‑to‑end AIGC architecture, data preprocessing, alignment, evaluation, and next‑generation AI search solutions.
This article presents JD Retail's data lake architecture overhaul, detailing the shortcomings of the Lambda model, the migration to Flink‑Hudi‑Spark pipelines, performance gains, storage savings, unified APIs, and upcoming improvements for resilience and automation.
The article introduces AIGCDesign, an open‑source cross‑platform AI component solution that combines traditional frontend libraries with large‑language‑model capabilities, outlines its design goals, technical architecture, lifecycle hooks, configuration examples, multi‑framework support, and real‑world business integration cases.
The article narrates the author’s 30‑year programming career and shares technical reflections on building business‑agnostic, configurable data platforms, covering batch, streaming, interactive computing, big‑data sharding, Spark, Flink, cloud migration, and the philosophy of software architecture.
This article chronicles the multi‑generation architectural evolution of JD's advertising platform, explaining why a good code architecture must be extensible, reusable, maintainable and stable, and describing how domain‑driven design, aggregates, and ability orchestration were introduced to solve the challenges of complex, multi‑scenario business requirements.
The article details JD's adoption of the Taro cross‑platform framework to build a HarmonyOS native app, describing the technical architecture, CSS and rendering optimizations, performance gains over native ArkTS, and future plans for further speed and flexibility improvements.
