Construction of Hadoop cluster big data visualization platform based on blockchain Technology

Qiang Gao
Shandong Management University, School of Labor Relations, Jinan, 250357, Shandong, China

Abstract:

Due to the problems of low data acquisition accuracy, large error and low data throughput in the construction of Hadoop cluster big data visualization platform, this paper proposes a construction method of Hadoop cluster big data visualization platform based on blockchain technology. The FCM clustering method is used to classify the power users, and the wavelet neural network is used to predict the load of the classified data, which is realized in parallel on the distributed platform. The data visualization is realized through the front-end language, visualization tools and visualization AP. The information of the data acquisition module is obtained through the interface, and the data is transmitted through the wireless transmission module. The latter is a simple scheme, and the machine communicates directly with the internal integrated single chip microcomputer. Collect hot list data of major mainstream news media by using distributed multi process crawler; Then preprocess the data inside the crawler. The experimental results show that the data acquisition accuracy of this method is 8.7% and the data throughput is 2.3%, the data transmission error is 1.9%. Using this method to build a big data visualization platform has a better effect.