Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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CHAPTER 1 ■ DEVELOPING SUCCESSFUL ORACLE APPLICATIONS 15 Executing SQL statements without bind variables is very much like compiling a subroutine before each and every method call. Imagine shipping Java source code to your customers where, before calling a method in a class, they had to invoke the Java compiler, compile the class, run the method, and then throw away the bytecode. The next time they wanted to execute the exact same method, they would do the same thing: compile it, run it, and throw it away. You would never consider doing this in your application. You should never consider doing this in your database, either. As it was, on this particular project, reworking the existing code to use bind variables was the best course of action. The resulting code ran orders of magnitude faster and increased many times the number of simultaneous users that the system could support. However, it came at a high price in terms of time and effort. It is not that using bind variables is difficult or error-prone, it’s just that the developers did not do it initially and thus were forced to go back and revisit virtually all of the code and change it. They would not have paid this high price if they had understood that it was vital to use bind variables in their application from day one. Understanding Concurrency Control Concurrency control is one area where databases differentiate themselves. It is an area that sets a database apart from a file system and databases apart from each other. It is vital that your database application work correctly under concurrent access conditions, and yet this is something people fail to test time and time again. Techniques that work well if everything happens consecutively do not work so well when everyone does them simultaneously. If you don’t have a good grasp of how your particular database implements concurrency control mechanisms, then you will • Corrupt the integrity of your data. • Have applications run slower than they should with a small number of users. • Decrease your ability to scale to a large number of users. Notice I don’t say, “You might . . .” or “You run the risk of . . .” Rather, you will invariably do these things without proper concurrency control without even realizing it. Without correct concurrency control, you will corrupt the integrity of your database because something that works in isolation will not work as you expect in a multiuser situation. Your application will run slower than it should because it will end up waiting for resources. You’ll lose your ability to scale because of locking and contention issues. As the queues to access a resource get longer, the wait times get longer and longer. An analogy here would be a backup at a tollbooth. If cars arrive in an orderly, predictable fashion, one after the other, there will never be a backup. If many cars arrive simultaneously, lines start to form. Furthermore, the waiting time does not increase in line with the number of cars at the booth. After a certain point, considerable additional time is spent “managing” the people that are waiting in line, as well as servicing them (the parallel in the database is context switching). Concurrency issues are the hardest to track down; the problem is similar to debugging a multithreaded program. The program may work fine in the controlled, artificial environment of the debugger but crashes horribly in the real world. For example, under race conditions, you find that two threads can end up modifying the same data structure simultaneously.
16 CHAPTER 1 ■ DEVELOPING SUCCESSFUL ORACLE APPLICATIONS These kinds of bugs are terribly difficult to track down and fix. If you only test your application in isolation and then deploy it to dozens of concurrent users, you are likely to be (painfully) exposed to an undetected concurrency issue. Over the next two sections, I’ll relate two small examples of how the lack of understanding concurrency control can ruin your data or inhibit performance and scalability. Implementing Locking The database uses locks to ensure that, at most, one transaction is modifying a given piece of data at any given time. Basically, locks are the mechanism that allows for concurrency— without some locking model to prevent concurrent updates to the same row, for example, multiuser access would not be possible in a database. However, if overused or used improperly, locks can actually inhibit concurrency. If you or the database itself locks data unnecessarily, then fewer people will be able to concurrently perform operations. Thus, understanding what locking is and how it works in your database is vital if you are to develop a scalable, correct application. What is also vital is that you understand that each database implements locking differently. Some have page-level locking, others have row-level locking; some implementations escalate locks from row level to page level, whereas others do not; some use read locks, others do not; and some implement serializable transactions via locking and others via read-consistent views of data (no locks). These small differences can balloon into huge performance issues or downright bugs in your application if you do not understand how they work. The following points sum up Oracle’s locking policy: • Oracle locks data at the row level on modification only. There is no lock escalation to a block or table level under normal circumstances (there is a short period of time during a two-phase commit, a not common operation, where this is not true). • Oracle never locks data just to read it. There are no locks placed on rows of data by simple reads. • A writer of data does not block a reader of data. Let me repeat: reads are not blocked by writes. This is fundamentally different from almost every other database, where reads are blocked by writes. While this sounds like an extremely positive attribute (it generally is), if you do not understand this idea thoroughly, and you attempt to enforce integrity constraints in your application via application logic, you are most likely doing it incorrectly. We will explore this topic in Chapter 7 on concurrency control in much more detail. • A writer of data is blocked only when another writer of data has already locked the row it was going after. A reader of data never blocks a writer of data. You must take these facts into consideration when developing your application, and you must also realize that this policy is unique to Oracle—every database has subtle differences in its approach to locking. Even if you go with lowest common denominator SQL in your applications, the locking and concurrency control models employed by each database’s vendor dictates that something about how your application behaves will be different. A developer who does not understand how his or her database handles concurrency will certainly
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Expert Oracle Database Architecture
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Contents Foreword . . . . . . . . .
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■CONTENTS v Block Buffer Cache .
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Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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