Performance continuous integration data processing method and device

Abstract

The invention provides a performance continuous integration data processing method and device. The method includes acquiring a performance continuous integration test result document stored in a disk, wherein the performance continuous integration test result document comprises a plurality of performance continuous integration test records; reading the plurality of performance continuous integration test records into a memory one by one; analyzing the performance continuous integration test records in the memory to obtain corresponding middle performance index data; deleting the analyzed performance continuous integration test records in the memory; judging whether analyzing of the plurality of performance continuous integration test records in the performance continuous integration test result document is completed; if analyzing of the plurality of performance continuous integration test records in the performance continuous integration test result document is completed, acquiring final performance index data and deleting the performance continuous integration test result document in the disk; storing the final performance index data to the memory and the disk. According to the performance continuous integration data processing method and device, space usage of the disk can be reduced, and analyzing and reading efficiency of regression result data is improved.

Description

technical field [0001] The present application relates to the technical field of performance testing, and in particular to a method for continuous performance integration data processing, and a performance continuous integration data processing device. Background technique [0002] Performance continuous integration is a process of continuously collecting performance indicators and analyzing the data after being triggered based on a certain condition (such as timing trigger, manual trigger, or trigger after main code change, etc.). After defining and controlling appropriate trigger conditions, performance indicators can be collected as continuous integration results, which mainly include response time (Response Time, RT for short), throughput (successful transactions per second, TPS for short) and integration status, etc. Data, it can detect performance problems caused by changes in certain conditions in time. [0003] Jmeter is a pure Java open source project based on the ...

AI Technical Summary

Problems solved by technology

Data analysis of a regression result needs to be loaded with 300M data, so the analysis results of 10 construction information will require nearly 3G of memory space, which will not only cause the JVM (Java Virtual Machine) to perform garbage collection frequently, but may even cause memory overflow risks of

In actual scenarios, it has been found that when parsing a regression task with a build count of 15, or parsing more than 5 regression tasks together, it will directly cause Hudson to fail to provide services

Images