Java Performance Tuning

System Limitations and What to Tune

Three resource s limit all applications:

• CPU speed and availability

• System memory

• Disk (and network) input/output (I/O)

When tuning an application, the first step is to determine which of these is causing your application to run too slowly.

If your application is CPU-bound, you need to concentrate your efforts on the code, looking for bottlenecks, inefficient algorithms, too many short-lived objects (object creation and garbage collection are CPU-intensive operations), and other problems, which I will cover in this book.

If your application is hitting system-memory limits, it may be paging sections in and out of main memory. In this case, the problem may be caused by too many objects, or even just a few large objects, being erroneously held in memory; by too many large arrays being allocated (frequently used in buffered applications); or by the design of the application, which may need to be reexamined to reduce its running memory footprint.

On the other hand, external data access or writing to the disk can be slowing your application. In this case, you need to look at exactly what you are doing to the disks that is slowing the application: first identify the operations, then determine the problems, and finally eliminate or change these to improve the situation.

For example, one program I know of went through web server logs and did reverse lookups on the IP addresses. The first version of this program was very slow. A simple analysis of the activity being performed determined that the major time component of the reverse lookup operation was a network query. These network queries do not have to be done sequentially. Consequently, the second version of the program simply multithreaded the lookups to work in parallel, making multiple network queries simultaneously, and was much, much faster.

In this book we look at the causes of bad performance. Identifying the causes of your performance problems is an essential first step to solving those problems. There is no point in extensively tuning the disk-accessing component of an application because we all know that “disk access is much slower than memory access” when, in fact, the application is CPU-bound.

Once you have tuned the application’s first bottleneck, there may be (and typically is) another problem, causing another bottleneck. This process often continues over several tuning iterations. It is not uncommon for an application to have its initial “memory hog” problems solved, only to become disk-bound, and then in turn CPU-bound when the disk-access problem is fixed. After all, the application has to be limited by something, or it would take no time at all to run.

Because this bottleneck-switching sequence is normal—once you’ve solved the existing bottleneck, a previously hidden or less important one appears—you should attempt to solve only the main bottlenecks in an application at any one time. This may seem obvious, but I frequently encounter teams that tackle the main identified problem, and then instead of finding the next real problem, start applying the same fix everywhere they can in the application.

One application I know of had a severe disk I/O problem caused by using unbuffered streams (all disk I/O was done byte by byte, which led to awful performance). After fixing this, some members of the programming team decided to start applying buffering everywhere they could, instead of establishing where the next bottleneck was. In fact, the next bottleneck was in a data-conversion section of the application that was using inefficient conversion methods, causing too many temporary objects and hogging the CPU. Rather than addressing and solving this bottleneck, they instead created a large memory allocation problem by throwing an excessive number of buffers into the application.