JMeter学习-010-JMeter 配置元件实例之 - CSV Data Set Config 参数化配置

众所周知，在进行接口测试的过程中，需要创建不同的场景（不同条件的输入，来验证不同的入参的返回结果）。因而，在日常的自动化接口监控或商品监控等线上监控过程中，需要配置大量的入参来监控接口的返回是否正确。

日常常见的线上监控几个简单的监控示例场景如下：

• 监控电商网站某个类目下的商品数量。若类目中商品的数量小于一定的数量，则认为需要认为查看商品池的商品是否正确；
• 监控商品的价格。当商品价格出现超出限定的波动幅度时，通知相应的商品负责人，对其进行确认，从而保证商品价格的正确无误。
• 监控商品在某一地域是否有货。当地域存货达到最低库存时，通知负责人进行货源补充；或者当某地域限制出售或未配置地域库存时，若发现存在相应库存，则可通知相关人员查验等。

那么，在 JMeter 中改如何对 HTTP请求进行参数化呢？

在 JMeter 的配置原件中就为我们提供了参数化需要的配置，下面以 CSV Data Set Config 进行参数化演示示例的配置，路径如下图所示：

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" alt="" />

PS：通过上图可以看出我们可以进行各种各样的参数化设置，例如用户自定义变量、计数器、HTTP Cookie 管理器等，同时也可以通过 JDBC 读取数据库中保存的测试数据（需要相应的 jar 文件支持）。

CSV Data Set Config 读取的文件不仅仅限于 csv 文件，其可以读取文本文件，文件内容需以英文半角 "," 隔开，每一行为一条测试用例数据。

下面开始以大家都熟悉的搜索功能展开 HTTP请求 参数化配置实例演示，具体的操作步骤如下所示：

第一步、获取搜索的 HTTP请求

获取搜素的 HTTP请求如下图所示（此步不再赘述，不知如何获取 HTTP请求 的小主，敬请参阅之前的博文，非常感谢！）：

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" alt="" width="766" height="548" />

第二步、通过 HTTP请求，确定需要参数化的变量

通常根据实际的参数化需求，选取符合测试需求且经常变化或未来会变化的变量为需要参数化的变量，例如本例中的查询关键字、配送区域、大区、产品源（或产品平台，例如：PC、Android、iPhone等）、产品版本，均可作为参数化的变量。

第三步、创建参数化文件，并填充测试用例数据

创建参数文件 mobileApp-IDC-0-searchGoods.txt，参数文件内容如下所示（注意参数文件编码方式建议选择 UTF-8）：

101-006-78945,29313,1,2169256,489349159815,android,45
101-005-31058,29313,1,1903913,472108827742,android,45
101-005-98536,29357,1,1993575,477948510289,android,45
101-006-88137,29358,1,2184120,490316513802,iphone,45
101-006-99103,29358,1,2201898,491473066849,iphone,45
101-005-84629,29358,1,1978716,476978170298,android,32
101-006-25777,29358,1,2035074,480647572701,android,45

第四步、通过 【配置元件/CSV Data Set Config】读取参数化文件，并对变量进行赋值。

最终的配置如下图所示：

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" 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• Filename：参数文件名，可以写绝对路径，个人强烈建议采用相对路径，避免脚本迁移时需要修改路径。
• File encoding：参数文件的编码格式。推荐选择 UTF-8。
• Variable Names：对对应参数文件每列的变量名。类似于 Excel 文件的文件头，起到标示的作用，同时也是后续引用的标识符，建议采用有意义的英文标示。
• Delimiter：参数文件分隔符。与参数文件中的分隔符保持一致即可。
• Allow quoted data？：是否允许引用数据。默认设置为 false。例如数据样式为："101-005-98536","29357","1","1993575","477948510289","android","45" 时，此处需设置为 true，一般默认为 false 即可。
• Recycle on EOF?：是否循环读取参数文件内容。默认设置为 true。设置为 true 时，当已经读取完参数文件内的测试用例数据，还需要继续获取用例数据时，此时会循环读取参数文件数据；设置为 false 时，若已至文件末尾，则不再继续读取测试数据。通常在 线程组的线程数 * 线程组的循环次数 > 参数文件行数时，才需要将此项设置为 true。
• Sotp thread on EOF?：当读取到参数文件末尾时，是否停止读取线程。默认为 false。当 Recycle on EOF?  设置为 true 时，此项不起任何作用。当且仅当 Recycle on EOF? 为 false 时，此项配置才生效。
• 若为 true，则在读取到参数文件行末尾时，终止参数文件读取线程。例如：线程组的线程数 * 线程组的循环次数 = 10，参数文件行数 = 7，那么将在第 8 次开始停止线程。
• 若为 false，此时线程会继续读取，但是会请求错误，因此时读取的数据为 EOF。以上同例，自第 8 次开始，线程的请求数据为 EOF。
• Sharing mode：共享模式，即参数文件变量作用域。主要有以下几种方式：
• All threads：当前测试计划中的所有线程组中的所有的线程均有效。默认。
• Current thread group：当前的线程组中的线程有效。
• Current thread：当前线程有效。
• 编辑：（俺暂时没有用过，嘿嘿 ^_^）

第五步、修改 HTTP请求 中对应的参数为参数变量

将如下部分中值替换为参数文件的值，即对应的 Variable Names，应用方式类似于 shell 脚本的变量引用，例如：${goodsNo}。

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" alt="" width="765" height="158" />

第六步、设置 HTTP请求 断言

将参数文件中的第 5 列（即商品的 skuid 设置为校验数据，通过此判断单品是否正确），测试数据如下所示：

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" 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设置断言如下所示：

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" alt="" width="764" height="263" />

第七步：执行脚本，查看结果

参数文件用例数据 101-006-25777,29358,1,2035074,480647572731,android,45 对应的 skuid：480647572731 设置的是错误的（方便对比断言结果）。执行结果如下所示：

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" alt="" width="763" height="212" />

第八步：脚本改进

其实，有些朋友看到这儿，可能会问执行结果列的标题均为线程标题，都是相同的无法区分，不方便阅读？其实，我们可以将脚本中的变量添加到线程名的后面（PS：需要考虑变量的作用域）即可简洁明了的区分每个线程，同时也可查看不同的入参，非常的方便。

将上述 HTTP 请求的线程名稍作修改，如下所示：

aaarticlea/png;base64,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" alt="" />

再次执行脚本，执行结果如下所示，通过下图是否可以非常直观简洁的执行结果，及对应的入参了 ^_^

aaarticlea/png;base64,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" alt="" width="763" height="210" />

附录（一）：

 <?xml version="1.0" encoding="UTF-8"?>
 <jmeterTestPlan version="1.2" properties="2.7" jmeter="2.12 r1636949">
   <hashTree>
     <TestPlan guiclass="TestPlanGui" testclass="TestPlan" testname="接口自动化测试实例 - 参数化" enabled="true">
       <stringProp name="TestPlan.comments"></stringProp>
       <boolProp name="TestPlan.functional_mode">false</boolProp>
       <boolProp name="TestPlan.serialize_threadgroups">false</boolProp>
       <elementProp name="TestPlan.user_defined_variables" elementType="Arguments" guiclass="ArgumentsPanel" testclass="Arguments" testname="用户定义的变量" enabled="true">
         <collectionProp name="Arguments.arguments"/>
       </elementProp>
       <stringProp name="TestPlan.user_define_classpath"></stringProp>
     </TestPlan>
     <hashTree>
       <ThreadGroup guiclass="ThreadGroupGui" testclass="ThreadGroup" testname="008-搜索商品" enabled="true">
         <stringProp name="ThreadGroup.on_sample_error">continue</stringProp>
         <elementProp name="ThreadGroup.main_controller" elementType="LoopController" guiclass="LoopControlPanel" testclass="LoopController" testname="循环控制器" enabled="true">
           <boolProp name="LoopController.continue_forever">false</boolProp>
           <stringProp name="LoopController.loops">3</stringProp>
         </elementProp>
         <stringProp name="ThreadGroup.num_threads">3</stringProp>
         <stringProp name="ThreadGroup.ramp_time">0</stringProp>
         <longProp name="ThreadGroup.start_time">1419232321000</longProp>
         <longProp name="ThreadGroup.end_time">1419232321000</longProp>
         <boolProp name="ThreadGroup.scheduler">false</boolProp>
         <stringProp name="ThreadGroup.duration"></stringProp>
         <stringProp name="ThreadGroup.delay"></stringProp>
       </ThreadGroup>
       <hashTree>
         <CSVDataSet guiclass="TestBeanGUI" testclass="CSVDataSet" testname="参数化列表文件 - 待搜索的商品列表" enabled="true">
           <stringProp name="filename">./mobileApp-IDC-0-searchGoods.txt</stringProp>
           <stringProp name="fileEncoding">UTF-8</stringProp>
           <stringProp name="variableNames">goodsNo,districtId,areacode,sysNo,skuid,appSource,appVersion</stringProp>
           <stringProp name="delimiter">,</stringProp>
           <boolProp name="quotedData">false</boolProp>
           <boolProp name="recycle">true</boolProp>
           <boolProp name="stopThread">false</boolProp>
           <stringProp name="shareMode">shareMode.all</stringProp>
         </CSVDataSet>
         <hashTree/>
         <HTTPSamplerProxy guiclass="HttpTestSampleGui" testclass="HTTPSamplerProxy" testname="008-01-搜索商品 【${goodsNo} - ${districtId} - ${appSource} - ${appVersion}】" enabled="true">
           <elementProp name="HTTPsampler.Arguments" elementType="Arguments" guiclass="HTTPArgumentsPanel" testclass="Arguments" enabled="true">
             <collectionProp name="Arguments.arguments">
               <elementProp name="q" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.value">${goodsNo}</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
                 <stringProp name="Argument.name">q</stringProp>
               </elementProp>
               <elementProp name="districtId" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.value">${districtId}</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
                 <stringProp name="Argument.name">districtId</stringProp>
               </elementProp>
               <elementProp name="areacode" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.value">${areacode}</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
                 <stringProp name="Argument.name">areacode</stringProp>
               </elementProp>
               <elementProp name="dtype" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.value">list|page|classes</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
                 <stringProp name="Argument.name">dtype</stringProp>
               </elementProp>
               <elementProp name="districtId" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.name">districtId</stringProp>
                 <stringProp name="Argument.value">${districtId}</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
               </elementProp>
               <elementProp name="exAppTag" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.name">exAppTag</stringProp>
                 <stringProp name="Argument.value">2045191607</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
               </elementProp>
               <elementProp name="appSource" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.value">${appSource}</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
                 <stringProp name="Argument.name">appSource</stringProp>
               </elementProp>
               <elementProp name="appVersion" elementType="HTTPArgument">
                 <boolProp name="HTTPArgument.always_encode">false</boolProp>
                 <stringProp name="Argument.value">${appVersion}</stringProp>
                 <stringProp name="Argument.metadata">=</stringProp>
                 <boolProp name="HTTPArgument.use_equals">true</boolProp>
                 <stringProp name="Argument.name">appVersion</stringProp>
               </elementProp>
             </collectionProp>
           </elementProp>
           <stringProp name="HTTPSampler.domain">mb.51buy.com</stringProp>
           <stringProp name="HTTPSampler.port"></stringProp>
           <stringProp name="HTTPSampler.connect_timeout"></stringProp>
           <stringProp name="HTTPSampler.response_timeout"></stringProp>
           <stringProp name="HTTPSampler.protocol">http</stringProp>
           <stringProp name="HTTPSampler.contentEncoding">GB2312</stringProp>
           <stringProp name="HTTPSampler.path">/json.php?mod=Search&amp;act=page&amp;p=1&amp;pp=20</stringProp>
           <stringProp name="HTTPSampler.method">POST</stringProp>
           <boolProp name="HTTPSampler.follow_redirects">true</boolProp>
           <boolProp name="HTTPSampler.auto_redirects">false</boolProp>
           <boolProp name="HTTPSampler.use_keepalive">true</boolProp>
           <boolProp name="HTTPSampler.DO_MULTIPART_POST">false</boolProp>
           <boolProp name="HTTPSampler.monitor">false</boolProp>
           <stringProp name="HTTPSampler.embedded_url_re"></stringProp>
         </HTTPSamplerProxy>
         <hashTree>
           <HeaderManager guiclass="HeaderPanel" testclass="HeaderManager" testname="HTTP信息头管理器" enabled="true">
             <collectionProp name="HeaderManager.headers">
               <elementProp name="Charset" elementType="Header">
                 <stringProp name="Header.name">Charset</stringProp>
                 <stringProp name="Header.value">UTF-8</stringProp>
               </elementProp>
               <elementProp name="Content-Type" elementType="Header">
                 <stringProp name="Header.name">Content-Type</stringProp>
                 <stringProp name="Header.value">application/x-www-form-urlencoded</stringProp>
               </elementProp>
               <elementProp name="Accept-Encoding" elementType="Header">
                 <stringProp name="Header.name">Accept-Encoding</stringProp>
                 <stringProp name="Header.value">gzip</stringProp>
               </elementProp>
               <elementProp name="User-Agent" elementType="Header">
                 <stringProp name="Header.name">User-Agent</stringProp>
                 <stringProp name="Header.value">Dalvik/1.6.0 (Linux; U; Android 4.4.2; GT-I9502 Build/KOT49H)</stringProp>
               </elementProp>
             </collectionProp>
           </HeaderManager>
           <hashTree/>
           <ResponseAssertion guiclass="AssertionGui" testclass="ResponseAssertion" testname="响应断言" enabled="true">
             <collectionProp name="Asserion.test_strings">
               <stringProp name="365072765">${goodsNo}</stringProp>
               <stringProp name="-781931418">${sysNo}</stringProp>
               <stringProp name="-794775524">${skuid}</stringProp>
             </collectionProp>
             <stringProp name="Assertion.test_field">Assertion.response_data</stringProp>
             <boolProp name="Assertion.assume_success">false</boolProp>
             <intProp name="Assertion.test_type">16</intProp>
           </ResponseAssertion>
           <hashTree/>
         </hashTree>
       </hashTree>
       <ResultCollector guiclass="AssertionVisualizer" testclass="ResultCollector" testname="断言结果" enabled="true">
         <boolProp name="ResultCollector.error_logging">false</boolProp>
         <objProp>
           <name>saveConfig</name>
           <value class="SampleSaveConfiguration">
             <time>true</time>
             <latency>true</latency>
             <timestamp>true</timestamp>
             <success>true</success>
             <label>true</label>
             <code>true</code>
             <message>true</message>
             <threadName>true</threadName>
             <dataType>true</dataType>
             <encoding>false</encoding>
             <assertions>true</assertions>
             <subresults>true</subresults>
             <responseData>false</responseData>
             <samplerData>false</samplerData>
             <xml>false</xml>
             <fieldNames>false</fieldNames>
             <responseHeaders>false</responseHeaders>
             <requestHeaders>false</requestHeaders>
             <responseDataOnError>false</responseDataOnError>
             <saveAssertionResultsFailureMessage>false</saveAssertionResultsFailureMessage>
             <assertionsResultsToSave>0</assertionsResultsToSave>
             <bytes>true</bytes>
             <threadCounts>true</threadCounts>
           </value>
         </objProp>
         <stringProp name="filename"></stringProp>
       </ResultCollector>
       <hashTree/>
       <ResultCollector guiclass="ViewResultsFullVisualizer" testclass="ResultCollector" testname="察看结果树" enabled="true">
         <boolProp name="ResultCollector.error_logging">false</boolProp>
         <objProp>
           <name>saveConfig</name>
           <value class="SampleSaveConfiguration">
             <time>true</time>
             <latency>true</latency>
             <timestamp>true</timestamp>
             <success>true</success>
             <label>true</label>
             <code>true</code>
             <message>true</message>
             <threadName>true</threadName>
             <dataType>true</dataType>
             <encoding>false</encoding>
             <assertions>true</assertions>
             <subresults>true</subresults>
             <responseData>false</responseData>
             <samplerData>false</samplerData>
             <xml>false</xml>
             <fieldNames>false</fieldNames>
             <responseHeaders>false</responseHeaders>
             <requestHeaders>false</requestHeaders>
             <responseDataOnError>false</responseDataOnError>
             <saveAssertionResultsFailureMessage>false</saveAssertionResultsFailureMessage>
             <assertionsResultsToSave>0</assertionsResultsToSave>
             <bytes>true</bytes>
             <threadCounts>true</threadCounts>
           </value>
         </objProp>
         <stringProp name="filename">${__property(JmeterAuto_LogFile)}</stringProp>
       </ResultCollector>
       <hashTree/>
     </hashTree>
   </hashTree>
 </jmeterTestPlan>

JMeter 配置元件 - CSV Data Set Config 参数化演示实例脚本源码

至此， JMeter学习-010-JMeter 配置元件实例之 - CSV Data Set Config 参数化配置 顺利完结，希望此文能够给初学 JMeter 的您一份参考。

最后，非常感谢亲的驻足，希望此文能对亲有所帮助。热烈欢迎亲一起探讨，共同进步。非常感谢！ ^_^