Apache JMeter is a test tool that is used to analyze and measure the performance of a variety of software products and services. This is purely a Java-free software used to test the FTP application or Web application. It is used to carry out performance tests, load tests and functional tests of Web applications. JMeter can simulate a heavy load on the server by creating many virtual users at the same time on a web server. In this blog, let us understand an important topic related to JMeter' JMeter Correlation'. So, Let's begin with understanding what exactly is Correlation means.
Correlation is the process in which a certain value is extracted from one step response to the other step request. It will capture and store the server's dynamic response and forwards it to later requests. A response is regarded as dynamic when it sends back different data for each iterative request, affecting successive requests from time to time. Correlation is an important process during the performance load test script. It is because if we don't deal with it care, the script will become worthless.
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Correlation is an important aspect of the script. It retrieves the dynamic data of previous requests and displays them in the next requests.
From a test perspective, it is required to identify what response is dynamic and what is static (the data will remains the same for iterative queries). In general, each HTTP web performance test implies a data correlation. You may skip the correlation only when you are testing pages with static content, such as certain home pages and contacts. Sometimes, you may not be able to avoid the correlation handling at any given moment of the test.
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In Manual correlation, the developer will discover the correlation points in the test flow manually and will map the values to be substituted in consecutive requests.
The correlation in Apache JMeter consists of two stages:
Now you will be able to see "Regular Expression Extractor" that will retrieve data from the previous sample's body. As a result of this component, successive queries may use the variable ${data-cmsid}, that will be mapped dynamically while running. It is the most commonly used means of manually correlating with JMeter. The application needs to be examined in depth to see where a correlation is needed.
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If you are having a little script with just a couple of correlation points, you may set a correlation manually. But if your script is big and has many correlations, then handling tends to be tedious and prone to errors for manual correlation. It is preferable to enhance the analysis of the test requirements prior to working on the large scripts with many points of correlation. This can be accomplished by dividing the large test into smaller subsets of test requirements. As far as possible, every subset must be atomic in terms of development and implementation.
The final scope of the breakdown process is to have a small script which can be aggregated or sequenced in a final execution scenario, possibly even directly in the JMeter user interface. This breakdown process, however, takes time and effort and is expensive. A much easier way would be to automate the correlation.
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JMeter provides no native autocorrelation function for the desktop application. But, We may use the free BlazeMeter SmartJMX, that is part of the BlazeMeter Proxy Recorder. The recorder has produced a JMX script, according to the saved script, that is correlated automatically.
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In this blog, we have learnt about JMeter Correlation and the types of correlations- Manual JMeter Correlation and JMeter Auto-Correlation. We hope you found this information useful. For more information related to JMeter, stay tuned to HKR trainings blogs.
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