摘要
在介绍了大数据测试的主要技术后,给出了面向大数据的测试过程,由于ETL(Extract Transform and Load抽取、转换和加载)测试是数据仓库测试中重要且复杂的阶段,给出了ETL测试的主要类型及ETL自动化测试的优势。通过对员工信息表进行数据填充测试及测试结果分析,说明ETL测试是保证数据质量有效性的重要途径。研究表明合理的搭建测试环境,应用自动化测试技术,可以提高测试效率以降低大数据测试的难度。
With the development of information technology,big data has become a new stage in the information age.For software testing,what should be tested,how to test and how to measure product quality for big data system are all problems that need to be solved urgently.Firstly,the paper analyzed several challenges of big data software testing,including testing basic theory,testing process,testing thinking.After introducing the main technology of big data testing,the paper analyzed the process of big data testing.Since ETL(Extract Transform and Load)testing is an important and complex stage in data warehouse testing,the main contents of ETL testing and the advantages of automated ETL testing were discussed.Through data filling test and test result analysis on employee table,it is shown that ETL test can improve the validity of data quality.The research shows that reasonable test environment construction and application of automated test technology can improve test efficiency and reduce the difficulty of big data test.
作者
刘珊艳
胡秀
严武
LIU Shanyan;HU Xiu;YAN Wu(Department of Computer Engin.,Jingchu Univ.Sci.and Engin.,Jingmen 448000,China;Jingmen Yousi Information Technology co.LTD,Jingmen 448000,China)
出处
《湖北工业大学学报》
2020年第5期55-61,共7页
Journal of Hubei University of Technology
基金
湖北省教育厅科研项目(B2018242,B2020193)
荆门市科技局科研项目(2019YFZD010,2018YDKY071)。
