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One of the most difficult things in enterprise application development is guaranteeing performance and scalability of an application. Let s define these terms first. Performance is usually considered to be the reaction time of a request/responsebased application. If you click a button, you expect a response in half a second. Or, depending on the use case, you expect that a particular event (or batch operation) can be executed in a reasonable time frame. Naturally, reasonable depends on the case and usage patterns of some application functionality. Scalability is the ability of a system to perform reasonably under higher load. Imagine that instead of 1 person clicking 1 button, 5,000 people click a lot of buttons. The better the scalability of a system, the more concurrent users you can pack on it without performance degradation. We already had much to say about performance. Creating a system that performs well is, in our opinion, synonymous to creating a Hibernate/database application that has no obvious performance bottlenecks. A performance bottleneck can be anything you consider a programming mistake or bad design for example, the wrong fetching strategy, a wrong query, or bad handling of the Session and persistence context. Testing a system for reasonable performance is usually part of the acceptance tests. In practice, performance testing is often done by a dedicated group of end user testers in a lab environment, or with a closed user group in real-world conditions. Pure automated performance tests are rare.

Table 3.9 Property DSTAMP TSTAMP TODAY Properties set by the <tstamp/> task Value format (based on current date/time) yyyymmdd hhmm month day year

You can also find performance bottlenecks with an automated scalability test; this is the ultimate goal. However, we ve seen many stress and load tests in our careers, and most of them didn t consider one or several of the following rules:

The <tstamp/> task also allows any number of nested <format> elements, which define properties given a format specification. For example, to create a property with only the day of the week, use <format property="." pattern=".">: .. ..

Test scalability with real-world data sets. Don t test with a data set that can fit completely into the cache of a hard disk on the database server. Use data that already exists, or use a test data generator to produce test data (for example, TurboData: http://www.turbodata.ca/). Make sure the test data is as close as possible to the data the system will work on in production, with the same amount, distribution, and selectivity. Test scalability with concurrency. An automated performance test that measures the time it takes to do a single query with a single active user doesn t tell you anything about the scalability of the system in production. Persistence services like Hibernate are designed for high concurrency, so a test without concurrency may even show an overhead you don t expect! As soon as you enable more concurrent units of work and transactions, you ll see how features such as the second-level cache help you to keep up performance. Test scalability with real use cases. If your application has to process complex transactions (for example, calculating stock market values based on sophisticated statistical models), you should test the scalability of the system by executing these use cases. Analyze your use cases, and pick the scenarios that are prevalent many applications have only a handful of use cases that are most critical. Avoid writing microbenchmarks that randomly store and load a few thousand objects; the numbers from these kinds of tests are meaningless.

<tstamp> <format property="dayofweek" pattern="EEEE"/> </tstamp> <echo message="It is ${dayofweek}"/>

Creating a test environment for the automatic execution of scalability tests is an involved effort. If you follow all our rules, you need to spend some time analyzing your data, your use cases, and your expected system load first. Once you have this information, it s time to set up automated tests. Typically, a scalability test of a client/server application requires the simulation of concurrently running clients and the collection of statistics for each executed operation. You should consider existing testing solutions, either commercial (such as LoadRunner, http://www.mercury.com/) or open source (such as The Grinder [http://grinder.sourceforge.net/] or JMeter [http:// jakarta.apache.org/jmeter/]). Creating tests usually involves writing control scripts for the simulated clients as well as configuring the agents that run on the

server processes (for example, for direct execution of particular transactions or the collection of statistics). Finally, testing performance and (especially) scalability of a system is naturally a separate stage in the lifecycle of a software application. You shouldn t test the scalability of system in the early stages of development. You shouldn t enable the second-level cache of Hibernate until you have a testing environment that was built following the rules we ve mentioned. At a later stage in your project, you may add automated scalability tests to the nightly integration tests. You should test the scalability of your system before going into production, as part of the regular test cycle. On the other hand, we don t recommend delaying any kind of performance and scalability testing until the last minute. Don t try to fix your performance bottlenecks one day before you go into production by tweaking the Hibernate second-level cache. You probably won t succeed. Consider performance and load testing to be an essential part of your development process, with well-defined stages, metrics, and requirements.

This results in the following:

16.6 Summary