Internet of Vehicles data analysis platform based on big data architecture
A data analysis and big data technology, applied in the field of big data car networking data analysis, can solve problems such as undocking, low stand-alone processing performance, irregular model training and analysis process, etc., and achieve the effect of visual data analysis
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Embodiment 1
[0051] Such as figure 1 Shown is a platform architecture diagram of a big data architecture-based Internet of Vehicles data analysis platform proposed by the present invention. The Internet of Vehicles data analysis platform includes a data receiving module, a data analysis task management module, and a data push module;
[0052] The data receiving module is used to receive the real-time data reported by the terminal, and perform preprocessing operations such as null value checking, missing value filling, abnormal value detection and other preprocessing operations on the data, and carry out segmentation packaging and writing to the message according to the driving cycle for the data that meets the conditions Middleware Kafka and distributed file system HDFS;
[0053] The data analysis task management module assembles the data analysis tasks according to different task types, and submits the data analysis tasks to the Spark distributed computing engine for calculation according...
Embodiment 2
[0056] Such as Figure 2-4 Shown is a task execution flow chart of an Internet of Vehicles data analysis platform based on a big data architecture proposed by the present invention, wherein the data analysis tasks are divided into three categories: offline training tasks, online analysis tasks, and offline analysis tasks. According to the task type The corresponding execution process is also different.
[0057] Offline training task execution steps: the first step is to upload the task code jar package for offline training; the second step is to associate the target vehicle number set to be analyzed; the third step is to select the range of the data set to be analyzed, that is, the date directory on HDFS; the fourth step The first step is to customize the visual dashboard in the data visualization module and associate it with the analysis task; the fifth step is to adjust the relevant parameters of the analysis task according to actual needs before starting the task; the sixth...
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