Research on the off-line processing data platform of automobile international big data based on Hadoop
This paper aims to build an offline processing data platform for automobile internationalization big data based on 10 databases. Firstly, four important modules of Hadoop such as Hadoop Common, Map Reduce, Yarn and HDFS are studied. Then, the flow chart of the platform's business engine is studied based on business execution and business monitoring. Then, the system adopts the top-down hierarchical thought architecture design, encompassing seven business layers including the application layer, gateway layer, service layer, distributed operation layer, cluster scheduling layer, storage layer, and data layer; Finally, the function test and the performance test of the platform are carried out. The results show that the various business functions and comprehensive performance of the platform can meet the large-scale use of individuals, enterprises, and organizations. This platform can help users deal with international automobile businesses and promote the internationalization of automobile products.
Authors
- Qian Ding (ORCID: https://orcid.org/0000-0001-8024-5064)
- Fan Zhang (ORCID: https://orcid.org/0000-0002-3643-018X)
- Zhao Sixu
- He Hongjing
Institutions
- China Automotive Technology and Research Center (CN)
Publication Details
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1109/icedcs64328.2024.00101
- Primary Topic
- E-commerce and Technology Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.00