摘要
面对智慧交通广泛的大数据应用场景和技术需求,一般大数据系统难以适应多种处理情况并做出快速响应。针对这一问题,首次提出了敏捷大数据方法论,对其概念、处理流程、核心原则与关键技术等进行了研究和探索。基于数据科学迭代性本质,设计了面向微服务的敏捷大数据架构,对交通大数据微服务化、交通大数据融合等关键环节进行了详细设计和论述。敏捷大数据架构的提出为交通大数据环境下的高效、灵活数据挖掘和机器学习提供了新思路、新方法。
Faced with a wide range of intelligent transportation application scenarios and technical requirements, the general big data system is difficult to adapt to a variety of processing and make a quick response. In order to solve this problem, the methodology of agile big data for the first time was put forward. Based on the iterative nature of data science, the agile big data architecture based on micro service was designed, and the key points of the traffic oriented micro service and data fusion technology were discussed. The agile big data architecture provides new idea and method for efficient and flexible data mining and machine learning under the environment of traffic big data.
作者
杜圣东
杨燕
滕飞
DU Shengdong YANG Yan TENG Fei(School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China)
出处
《大数据》
2017年第3期53-67,共15页
Big Data Research
基金
国家重点研发计划基金资助项目(No.2016YFC0802209)
国家科技支撑计划基金资助项目(No.2015BAH19F02)~~
关键词
敏捷大数据
微服务
大数据架构
容器
大数据融合
agile big data, micro service, big data architecture, container, big data fusion
