Construction of Parking Space Recommendation Model Based on Big Data and Multi attribute Decision Algorithm

this paper studies the construction of parking recommendation model based on Hadoop under big data. In order to solve the problem of real-time monitoring and recommendation of traditional parking spaces, this paper proposes to use Hadoop technology to analyze and process unstructured data. The system uses large-scale parallel database Greenplum technology for data storage and processing, realizes the rapid query of data, and constructs the technical model of parking recommendation analysis system. The system uses multi-attribute optimal decision-making algorithm to achieve real-time recommendation of massive parking spaces.