Construction and Architecture of JD One-Service Data Service System
This article details JD's three‑stage evolution of its data service platform, explains thematic (topic‑based) data services, introduces the One‑Service unified architecture, and outlines future plans for standardization, low‑code front‑end, and operational improvements.
The presentation introduces JD One‑Service data service system, describing the three development stages of JD's data service platform: rapid response to explosive business data needs, consolidation into thematic services, and the final One‑Service unified service that aims to serve all topics with a single query interface.
It then explains thematic data services, which consist of front‑end, middle‑ware, and back‑end modules: the front‑end provides various channel formats, the middle‑ware performs request analysis and routing based on topic, and the back‑end delivers topic‑specific data services such as transaction, traffic, and user domains.
The article showcases the fusion service architecture that standardizes templates, uses model adapters, and abstracts protocol, permission, business, adaptation, cache, query, execution, connection, and dynamic configuration layers to achieve a unified and low‑risk data service platform.
Key practical features of thematic services are highlighted: code templating, data configurability, metric fusion, cache granularity, standardized protocols, and asset management through an indicator market that supports registration, management, access, inspection, and routing.
One‑Service data service standards are defined using a 5W2H model (business domain, theme, process, entity, measure, update cycle, granularity, storage mode, etc.) and a 4W1H metric standard, enabling consistent definition and querying of indicators.
The architecture includes a dimension center for standardized dimension views, a definition‑driven query engine that assembles SQL from configurations, and a complete service chain covering low‑code front‑end, service query routing, protection layers (rate limiting, circuit breaking, failover), and dynamic protection mechanisms.
Future planning focuses on reducing underwater capabilities, strengthening workflow chains, layering alarms, automating dynamic protection, and lightweight server consolidation to improve performance and maintainability.
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