Technology sharing on Kuaishou Big Data, covering big‑data architectures (Hadoop, Spark, Flink, ClickHouse, etc.), data middle‑platform (development, management, services, analytics tools) and data warehouses. Also includes the latest tech updates, big‑data job listings, and information on meetups, talks, and conferences.
Kuaishou tackles massive live‑e‑commerce flash‑sale traffic by combining an elastic Docker‑based container cloud with a hybrid private‑public cloud architecture, enabling rapid scaling, high concurrency handling, and cost‑effective resource management.
This article details how Kuaishou’s Data Application Factory tackles the challenges of rapid BI delivery, data accuracy, and service stability by leveraging low‑code development, unified query services, standardized configurations, and service isolation to achieve efficient, high‑quality data products across multiple business lines.
This article introduces OAX (Open Analysis eXpressions), Kuaishou’s unified open‑analysis language, detailing its design background, guiding principles, five‑layer language model, syntax—including data types, compute capabilities and five analysis elements—its access protocol, runtime architecture, optimization steps, and the benefits it brings to the company’s big‑data analytics ecosystem.
This article details Kuashou's metric middle platform, covering its role as a semantic layer, the unified architecture of OneMetric and OneService, metric standardization processes, automated modeling techniques, the Headless BI concept, and future directions for intelligent modeling and acceleration.
This article details Kuaishou’s three‑year evolution of its metric middle platform, covering the data infrastructure, key challenges of data inconsistency and low analysis efficiency, the enterprise‑level OneMetric solution, architectural design, development phases, practical lessons, system implementation, and real‑world applications.
This article details Kuaishou's end‑to‑end big data platform, describing its organizational model, unified data governance framework, comprehensive data‑quality solution, the design of a headless metric platform, key technologies such as automatic modeling and code generation, and future directions toward a decentralized, smart data fabric.
This article outlines Kuaishou's evolution of metadata management from its early Hive‑centric stage to a unified 2.0 platform, detailing system architecture, key technologies, challenges, and future 3.0 vision for low‑code, automated, and intelligent data governance.
The article details Kwai’s OneService platform—a low‑code, self‑service data platform that streamlines API creation, deployment, and operation, covering its background, architecture, key technologies such as API matrix and configuration‑as‑code, high‑availability and performance strategies, achieved results, and future roadmap.
This article details the design, evolution, and optimization of Kuaishou's data synchronization platform, covering business overview, architecture, key technologies, performance tuning, data source protection, incremental data lake integration, and future roadmap for a unified data fabric.
This article explains Kuaishou's comprehensive approach to data governance, detailing the background challenges, a standardized evaluation framework, practical solutions for model, quality, and cost issues, scoring strategies, operational mechanisms, measurable benefits, and future plans for continuous improvement.
