Data processing method, data query method and associated equipment

Abstract

The invention discloses a data processing method. The data processing method comprises the following steps: obtaining traffic monitoring data of equipment such as a camera and the like, wherein the traffic monitoring data comprises time data, location data, and identification data; determining the target data granularity; performing partition analysis on the traffic monitoring data according to atleast one of the time data, the location data and the identification data, and the target data granularity to obtain a first analysis result; and performing statistics on monitoring records in the traffic monitoring data that meet a screening condition according to the screening condition set based on the first analysis result to obtain a second analysis result. In the scheme, the second analysisresult can be directly applied to a data query process of a data analysis model, and the data query does not need to analyze the traffic monitoring data; therefore, the query time is greatly reduced,and the query efficiency is improved.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to a data processing method, a data query method and related equipment. Background technique [0002] Checkpoint is the abbreviation of road traffic security checkpoint monitoring system. It refers to relying on specific places on the road, such as toll stations, traffic or public security checkpoints and other checkpoints, to take pictures of all motor vehicles or pedestrians passing through the checkpoint. A road traffic on-site monitoring system for recording and processing. [0003] Take vehicle checkpoints as an example. In a second-tier city, the number of vehicle checkpoints is generally more than 10,000. These checkpoints record about 50 million vehicle passing records every day, and the total number of pictures taken is about 23 terabytes (TB). The number of passing records captured in the camera can reach tens of billions. For the amount of data above t...

AI Technical Summary

Problems solved by technology

However, when the query time and space range is large, for example, the amount of data that needs to be queried by the peer vehicle analysis model is more than 10 billion, the system cannot meet the query requirements based on the data volume of a single index, and the data of more than 10 billion The time required to analyze and query the volume is more than ten seconds, and this query efficiency cannot meet business needs

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