java qr code generator example Results: how to reduce memory footprint 150-fold in Java

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8.4.3 Results: how to reduce memory footprint 150-fold
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Running the stress test we just described under various combinations of patterns yielded radically different values of memory consumption, as reported by the Windows Task Manager. These are summarized in table 8.4.
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Table 8.4 ID A B C D E Benchmark results for ClickBox example code Reuse DOM Nodes N N N Y Y Unlink On Hide N N Y N N Break Cyclic Refs N Y N N Y Final Memory Use (IE) 166MB 84.5MB 428MB 14.9MB 14.6MB continued on next page
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Table 8.4 ID F G Benchmark results for ClickBox example code (continued) Reuse DOM Nodes Y Y Unlink On Hide Y Y Break Cyclic Refs N Y Final Memory Use (IE) 574MB 14.2MB
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The results in table 8.4 were recorded for the stress test on a fairly unremarkable workstation (2.8GHz processor, 1GB of RAM) for Internet Explorer v6 on Windows 2000 Workstation under various permutations of patterns. Initial memory use was approximately 11.5MB in all cases. All memory uses reported are the Mem Usage column of the Processes tab of the Task Manager application (see section 8.4.1). Since we re confronting real numbers for the first time, the first thing to note is that the application consumes quite a bit of memory. Ajax is often described as a thin client solution, but an Ajax app is capable of hogging a lot of memory if we make the right combination of coding mistakes! The second important point about the results is that the choice of design patterns has a drastic effect on memory. Let s look at the results in detail. Three of our combinations consume less than 15MB of RAM after rendering and unrendering all the ClickBox widgets. The remaining combinations climb upward through 80MB, 160MB, to a staggering 430MB and 580MB at the top end. Given that the browser was consuming 11.5MB of memory, the size of additional memory consumed has varied from 3.5MB to 570MB that s a difference of over 150 times, simply by modifying the combination of design patterns that we used. It s remarkable that the browser continued to function at all with this amount of memory leaking from it. No particular pattern can be identified as the culprit. The interaction between design patterns is quite complex. Comparing runs A, D, and F, for example, switching on the Reuse DOM pattern resulted in a huge decrease in memory usage (over 90 percent), but switching on Unlink On Hide at the same time generated a threefold increase! In this particular case, the reason is understandable because the DOM nodes have been unlinked, they can t be found by a call to document.getElementById() in order to be reused. Similarly, switching on Unlink On Hide by itself increased memory usage against the base case (comparing runs C to A). Before we discount Unlink On Hide as a memory hog, look at runs E and G in the right context, it does make a small positive difference. Interestingly, there is no single clear winner, with three quite different combinations all resulting in only a small increase in memory. All three of these reuse
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DOM nodes, but so does the combination that results in the highest memory
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increase. We can t draw a simple conclusion from this exercise, but we can identify sets of patterns that work well together and other sets that don t. If we understand these patterns and have names for them, then it is much easier to apply them consistently throughout an application and achieve reliable performance. If we weren t using a fixed set of patterns but coding each subsystem s DOM lifecycle in an ad hoc fashion, each new piece of code would be a gamble that might introduce a large memory leak or might not. This benchmarking exercise has provided an overview of the issues involved in developing a DHTML rich client that plays well with your web browser for extended periods of time, and it identified places where errors may occur, both in general and in some of the patterns discussed elsewhere in this book. To really stay on top of memory issues, you must give them a place in your development methodology. Always ask yourself what the effect on memory usage will be as you introduce changes to your code, and always test for memory usage during implementation of the change. Adopting a pattern-based approach to your codebase will help here, as similar memory issues will crop up repeatedly with the same patterns. We know, for example, that backing objects create cyclic references between DOM and nonDOM nodes, and that Remove By Detachment patterns interfere with Create If Not Exists patterns. If we use patterns consciously in our designs, we are less likely to run into these sorts of problems. It can help to write and maintain automated test scripts and benchmark your changes against them. Writing the test scripts is probably the hardest part of this, as it involves knowledge of how users use your application. It may be that your app will have several types of user, in which case you would do well to develop several test scripts rather than a single average that fails to represent anyone. As with any kind of tests, they shouldn t be seen as set in stone once written but should be actively maintained as your project evolves.
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Performance of any computer program is a combination of execution speed and resource footprint. With Ajax applications, we re working within a highly managed environment, far removed from the operating system and the hardware, but we still have the opportunity to affect performance greatly, based on the way we code.
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