So, you are persuaded that SQL tuning is a good idea. Should you be the one to do it, on your system? Chances are that you originated at most a small fraction of the SQL on your system, since good-sized teams develop most systems. You might evenlike me, in most of my own historybe looking at an application for which you wrote none of the SQL and were not even responsible for the database design. I assumed for years that the developers of an application, who wrote the SQL, would always understand far better than I how to fix it. Since I was responsible for performance, anyway, I thought the best I could do was identify which SQL statements triggered the most load, making them most deserving of the effort to tune them. Then it was (I thought) my job to nag the developers to tune their own highest-load SQL. I was horribly, embarrassingly, wrong.
As it turns out, developers who tune only their own SQL are at a serious disadvantage, especially if they have not learned a good, systematic approach to tuning (which has been lacking in the literature). It is hard to write a real-world application that works, functionally, even without worrying about performance at all. The time left over for the average developer to tune SQL is low, and the number of self-built examples that that developer will have to practice on to build tuning expertise is also low.
The method this book teaches is the best I know, a method I designed myself to meet my own needs for tuning SQL from dozens of applications other people wrote. However, if you really want to be a first-rate SQL tuner, the method is not enough. You also need practicepractice on other people's SQL, lots of other people's SQL, whole applications of SQL. But how do you cope with the sheer complexity of entire applications, even entire applications you hardly know? Here is where SQL delivered me, at least, a great surprise: you do not need to understand other people's SQL to tune it!
Treat SQL as a speca clear and unambiguous declaration of which rows of which tables the application requires at some particular point in a program. (SQL is clear because it was designed for casual use by nonprogrammers. It is necessarily unambiguous; otherwise, the database could not interpret it.) You do not need to know why the application needs those rows, or even what those rows represent. Just treat the rows and tables as abstract, even mathematical, entities. All you need to know or figure out is how to reach those rows faster, and you can learn this by just examining the SQL, tables, and indexes involved, with simple queries to the database that are completely independent of the semantic content of the data. You can then transform the SQL or the database (for example, by adding indexes) in simple ways that guarantee, almost at the level of mathematical proof, that the transformed result will return exactly the same rows in the same order, but following a much better, faster path to the data.