Java Performance Tuning

Chapter 8. I/O, Logging, and Console Output

I/O, I/O, it’s off to work we go.

—Ava Shirazi

I/O to the disk or the network is hundreds to thousands of times slower than I/O to computer memory. Disk and network transfers are expensive activities, and are two of the most likely candidates for performance problems. Two standard optimization techniques for reducing I/O overhead are buffering and caching.

For a given amount of data, I/O mechanisms work more efficiently if the data is transferred using a few large chunks of data, rather than many small chunks. Buffering groups data into larger chunks, improving the efficiency of the I/O by reducing the number of I/O operations that need to be executed.

Where some objects or data are accessed repeatedly, caching those objects or data can replace an I/O call with a hugely faster memory access (or replace a slow network I/O call with faster local disk I/O). For every I/O call that is avoided because an item is accessed from a cache, you save a large chunk of time equivalent to executing hundreds or thousands of simple operations.^[52]

There are some other general points about I/O at the system level that are worth knowing. First, I/O buffers throughout the system typically use a read-ahead algorithm for optimization. This normally means that the next few chunks are read from disk into a low-level buffer somewhere. Consequently, reading sequentially forward through a file is usually faster than other orders, such as reading back to front through ...