一、etl测试概念
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etl分别是Extraction, Transformation, and Loading。
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etl处理过程

二、 ETL测试过程
测试过程如下:
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确定业务逻辑
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测试计划
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设计测试样例和测试数据
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执行测试和测试bug报告
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汇总报告
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测试结束
三、测试内容
3.1 一致性测试验证
关键值验证。
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NOT NULL(空值)
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UNIQUE(唯一性)
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Primary Key(主键)
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Foreign Key(外键)
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Check(校验)
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NULL(空值)
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Default(默认值)
其他测试
- 边界条件测试
- 数据记录数测试
- 根据数据类型测试(float、int测试最大最小值,string、int枚举型数据测试枚举值记录数)
3.2 重复值验证
3.3 初始化验证
程序初始化时,测试软硬件是否正常。
Given below is the table showing the list of ETL Bugs:
Type of bug | Description |
---|---|
Calculation Bugs | Final output wrong due to mathematical error |
Input/output Bugs | Accepts invalid values and rejects valid values |
H/W bugs | Device is not responding due to hardware issues |
User Interface bugs | Related to GUI of an application |
Load condition bugs | Denies multiple users |
四、在etl测试中创建etl测试用例
etl测试需要两个文档:
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etl源数据表到目标数据表映射文档。文档提供了目标表和数据来源情况。
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源表和目标表的表结构文档。文档应该在验证过程中和映射文档同时更新。
Given below is the list of the top ETL Testing Tools(etl自动化测试工具):
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Informatica Data Validation
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QuerySurge
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ICEDQ
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Datagaps ETL Validator
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QualiDI
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Talend Open Studio for Data Integration
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Codoid’s ETL Testing Services
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Data Centric Testing
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SSISTester
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TestBench
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GTL QAceGen
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Zuzena Automated Testing Service
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DbFit
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AnyDbTest
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99 Percentage ETL Testing
Some of them are listed below(测试成功的关键):
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Apply suitable business transformation logic.
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Execute backend data-driven tests.
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Create and execute absolute test cases, test plans, and test harness.
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Assure accuracy of data transformation, scalability and performance.
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Make sure E(确保抽取数据正确)
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TL application reports invalid values.(转换和加载报告错误值)
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Unit tests should be created as targeted standards.
备注:翻译自https://www.softwaretestinghelp.com/top-4-etl-testing-tools/。
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