My past as a DBA probably makes me a bit biased, but the reaction I’ve seen the most when a database application isn’t performing as well as would be liked seems to focus on the database side of things. The search for a solution usually seems to center around tuning db parameters, the building (or removal) of indexes and if the budget allows, throwing hardware at the problem. In their new work, Refactoring SQL Applications, Faroult and L’Hermite bring a much wider range of options to the table. There is a lot in this little book for the developer charged with fixing an existing application and I think a lot of good information that could save one from making a number of head-ache inducing mistakes on a new application.
The book is divided into eight chapters the first two deal with how to approach a problematic application in general. In the preface the authors say, “This book tries to take a realistic and honest view of the improvement of applications with a strong SQL component, and to define a rational framework for tactical maneuvers.” I found this to be true throughout the entire book and was impressed by how well the examples, suggestions and problems echoed my real life experience. This book is first and foremost practical. There is really almost nothing in the book that does not come immediately to bear upon the problem at hand. I’ve seen others do a lot less with many more pages.
The examples and benchmarks are compared across three different popular relational database management systems. They are MySQL, Oracle RDBMS and Microsoft SQL Server. I thought that this brought up a couple interesting issues that are not directly addressed in the book. First is that the authors are talking about how to improve performance, not comparing platforms but the numbers are there and may be of some interest to people who would like to compare them. Secondly, I’ve met a number of people over the years who get quite animated about insisting that a good DBA does not need to know any certain solution, but rather just the fundamentals. I think Faroult and L’Hermite put this idea to rest, though unintentionally. In order to discuss how to best understand what exactly is happening and how best remedy issues, they show that it is necessary to have an understanding of platform specific issues and tools. This is true on two levels. The first is that the location of use of the built in tools for each platform are different. The second is that what works for one platform does not necessarily work for another.
For example, Chapter Two “Sanity Checks” contains a section on parsing and bind variables. The authors compare performance when queries are hard coded, with new prepared statements on each iteration (firm coded) and with one prepared statement and changing the parameter value on each iteration in a loop (soft coded). On Oracle and SQL Server the performance was poorest with hard coded, better with firm coded and best with soft coded. MySQL did best with soft coded as well but actually took a performance hit moving from hard coded to firm coded. This had to do with differences in how MySQL server caches statements. The authors took the time to rewrite their code from java to c in order to ensure that the issue was not related to language or driver issues. This is not to say that one can ignore RDBMS and SQL fundamentals, but rather that to get top performance requires knowledge of platform specific issues. This also comes out again when dealing with optimizers.
With that in mind, the authors recommend that readers have a solid understanding of SQL and some programming language. Most examples are SQL and code is given in Java and PHP. There are also examples that illustrate SQL extensions showing procedures, functions, etc. written for all three RDBMS products covered. The authors stick primarily to standard SQL but do make note and at times show examples of how things will look in each of the other databases. This information is current and reflects the most recent versions of the each product.
The fourth chapter, “Testing Framework” is incredibly useful. The authors cover generating test data and then checking correctness of outcomes through comparison. This is really useful information for anyone working to improve an application, or writing one for the first time. I think it also a large part of why this book could really appeal to new and experienced developers as well as the developer working on existing or brand new applications. I think there is a good chance that only the most extremely experienced developer would find nothing new here, or at least some new way to approach a problem. New developers can learn quite a bit and avoid some bad habits and assumptions without having to gain that information the hard way. And then the tools for generating random data, large amounts of data and comparing results will provide excellent opportunities for learning and real world application.
The next three chapters cover dealing with specific types of issues and how to improve performance. The last chapter then quickly describes a scenario of just how the authors step into real world situations and start to attack a problem. This is followed with two appendices. The first is scripts and samples, the second tools that are available to help in finding issues and resolving them. Some of the authors tools use SQLite, which is discussed briefly in the chapter on creating test data as some of the tools depend upon it.
I think that it has been a while since I’ve read a book that could have such a rapid return on investment. There are many suggestions and insights that should enable anyone to squeeze better performance out of just about any database application. While the focus is on the application side, there is plenty that requires understanding and work on the database side as well. There is discussion of the parameters and hardware I mentioned at the start of this review. But rather than the only options, they are one part in a much larger and systematic approach.
The authors relate that often refactoring for this type of application comes into play when something that used to work does not work any more. This can often lead to an environment of high pressure and emotion. The desire for a rapid resolution can lead to casting about in the dark for a quick fix or a feeling that cost is no longer as significant since a fix must be had now. The authors argue, and I agree, that this is exactly when a rational, disciplined process of tracking down and fixing issues is the most valuable. I agree. The issue is of course that someone in a position to do something must have the ability to take that approach. This book will get one well on the way to being in that place. Of course it can’t take a brand new developer or DBA an expert. Much like a degree it can give them some fundamental tools that will allow them to take full advantage of experience as it comes rather than just crashing and burning.
If I could I’d have any developer on a database centric application read this, and DBAs as well. There is a lot here for both sides to learn about just how much they depend upon and impact one another. This may be an idealistic dream, especially for larger shops where often the relationship between those two groups is adversarial, but I think that such an approach could only make life much better for everyone involved. For anyone looking to enter this world on either side of the DBA or developer equation, this may make a nice addition to their education. For that individual wearing both hats this could be a life saver. In this small book they will learn many things to look out for as well as gain exposure to some of the similarities and differences in what are arguably the top three relational database management systems right now.
Title: Refactoring SQL Applications
Author: Stephane Faroult with Pascal L’Hermite
Publisher: O’Reilly Media, Inc.