JD Retail Traffic Data Warehouse Architecture and Processing Practices
This article presents a comprehensive technical overview of JD.com’s retail traffic data processing pipeline, detailing the multi‑layer data warehouse architecture, real‑time and offline data flows, a large‑scale back‑fill case using Iceberg and OLAP, data‑skew detection and mitigation techniques, and future directions involving unified Flink‑Spark streaming‑batch solutions.