Flow detection method and device, equipment and medium

Abstract

The embodiment of the invention relates to a flow detection method and device, equipment and a medium, and the method comprises the steps: obtaining a first process identifier for calling a flow statistical function and a corresponding current consumed flow in response to a calling request for the preset flow statistical function in a kernel space; calling a preset network data packet to filter a query interface of an eBPF module, and querying whether the first process identifier is included according to a preset corresponding relation in a preset virtual file system; if the first process identifier is included, querying and obtaining historical total consumed flow corresponding to the first process identifier in the corresponding relationship through the query interface; and calculating the sum of the historical total consumption flow and the current consumption flow to obtain the current total consumption flow, and calling a write-in interface of the eBPF module to write the historical total consumption flow of the corresponding relationship into the current total consumption flow. In the method of the invention, the current total consumed flow can be counted by taking the process as the granularity, so that the accuracy of flow statistics can be improved.

Description

Technical field [0001] The present disclosure relates to computer technology, and in particular, to a method for detecting the flow rate, means, devices and media. Background technique [0002] With the development of computer technology, increasingly diverse types of applications, in order to facilitate the application management, application traffic consumption statistics and other more common. [0003] In the related art, each application is acquired long run, and the average length of the corresponding network speed operation, the consumption flow is determined for each application based on the average speed and long running product. [0004] However, the above statistics consumption flow-based product applications running duration and average speed, since the same time multiple applications may have differences in the use of network resources, and applications in real-time speed and average speed, therefore, lead to lower traffic statistics accuracy. Inventive content [00...

AI Technical Summary

Problems solved by technology

[0004] However, in the above-mentioned method of counting traffic consumption based on the product of the running time of the application and the average network speed, since multiple applications may be using network resources at the same time, and the real-time network speed of the application is different from the average network speed, therefore, resulting in The accuracy of traffic statistics is low

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