By Scott Oaks
Coding and trying out are usually thought of separate parts of craftsmanship. during this entire advisor, writer and Java professional Scott Oaks takes the procedure that anybody who works with Java could be both adept at figuring out how code behaves within the JVM, in addition to the tunings more likely to support its performance.
You'll achieve in-depth wisdom of Java program functionality, utilizing the Java digital laptop (JVM) and the Java platform, together with the language and API. builders and function engineers alike will study quite a few good points, instruments, and tactics for bettering the best way Java 7 and eight purposes perform.
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Coding and checking out are frequently thought of separate parts of craftsmanship. during this finished consultant, writer and Java professional Scott Oaks takes the strategy that anybody who works with Java may be both adept at realizing how code behaves within the JVM, in addition to the tunings more likely to support its functionality.
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Extra info for Java Performance: The Definitive Guide
Testing an entire application is the only way to know how code will actually run. 3. Isolating performance at a modular or operational level—a mes‐ obenchmark—offers a reasonable compromise but is no substi‐ tute for testing the full application. Common Code Examples Many of the examples throughout the book are based on a sample application that calculates the “historical” high and low price of a stock over a range of dates, as well as the standard deviation during that time. Historical is in quotes here because in the application, all the data is fictional; the prices and the stock symbols are randomly generated.
A performance test is only repeatable if the envi‐ ronment is the same from run to run; the automation must take care of that. Measure everything The automation must gather every conceivable piece of data that will be useful for later analysis. This includes system information sampled throughout the run: CPU usage, disk usage, network usage, memory usage, and so on. It includes logs from the application—both those the application produces, and the logs from the garbage collector. Ideally it can include Java Flight Recorder (JFR) recordings (see Chap‐ ter 3) or other low-impact profiling information, periodic thread stacks, and other heap analysis data like histograms or full heap dumps (though the full heap dumps, in particular, take a lot of space and cannot necessarily be kept long term).
The typical development cycle does not make things any easier. A project schedule often establishes a feature-freeze date: all feature changes to code must be checked into the repository at some early point in the release cycle, and the remainder of the cycle is devoted to shaking out any bugs (including performance issues) in the new release. This causes two problems for early testing: 1. Developers are under time constraints to get code checked in to meet the schedule; they will balk at having to spend time fixing a performance issue when the schedule has time for that after all the initial code is checked in.