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

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Foreword “THINK.” In 1914, Thomas J. Watson, Sr. joined the company that was to become IBM, and he brought with him this simple one-word motto. It was an exhortation to all IBM employees, no matter their role, to take care in decision-making and do their jobs with intelligence. “THINK” soon became an icon, appearing on publications, calendars, and plaques in the offices of many IT and business managers within and outside IBM, and even in The New Yorker magazine cartoons. “THINK” was a good idea in 1914, and it is a good idea now. “Think different.” More recently, Apple Computer used this slogan in a long-running advertising campaign to revitalize the company’s brand, and even more important, to revolutionize how people think of technology in their daily lives. Instead of saying “think differently,” suggesting how to think, Apple’s slogan used the word “different” as the object of the verb “think,” suggesting what to think (as in, “think big”). The advertising campaign emphasized creativity and creative people, with the implication that Apple’s computers uniquely enable innovative solutions and artistic achievements. When I joined Oracle Corporation (then Relational Software Incorporated) back in 1981, database systems incorporating the relational model were a new, emerging technology. Developers, programmers, and a growing group of database administrators were learning the discipline of database design using the methodology of normalization. The then unfamiliar, nonprocedural SQL language impressed people with its power to manipulate data in ways that previously took painstaking procedural programming. There was a lot to think about then—and there still is. These new technologies challenged people not only to learn new ideas and approaches, but also to think in new ways. Those who did, and those who do, were and are the most successful in creating innovative, effective solutions to business problems using database technology to its best advantage. Consider the SQL database language that was first introduced commercially by Oracle. SQL permits application designers to manipulate sets of rows with a nonprocedural (or “declarative”) language, rather than writing iterative loops in conventional languages that process records one at a time. When I was first introduced to SQL, I found it required me to “think at 45 degrees” to figure out how to use set processing operations like joins and subqueries to achieve the result I wanted. Not only was the idea of set processing new to most people, but so also was the idea of a nonprocedural language, where you specified the result you wanted, not how to derive it. This new technology really did require me to “think differently” and also gave me an opportunity to “think different.” Set processing is far more efficient than one-at-a-time processing, so applications that fully exploit SQL in this way perform much better than those that do not. Yet, it is surprising how often applications deliver suboptimal performance. In fact, in most cases, it is application design, rather than Oracle parameter settings or other configuration choices, that most directly determines overall performance. Thus, application developers must learn not only details about database features and programming interfaces, but also new ways to think about and use these features and interfaces in their applications. xi
xii ■FOREWORD Much “conventional wisdom” exists in the Oracle community about how to tune the system for best performance or the best way to use various Oracle features. Such “wisdom” sometimes becomes “folklore” or even “mythology,” with developers and database administrators adopting these ideas uncritically or extending these ideas without reasoning about them. One example is the idea that “if one is good, more—lots more—is better.” This idea is popular, but only rarely true. Take Oracle’s array interface, for example, which allows the developer to insert or retrieve multiple rows in a single system call. Clearly, reducing the number of network messages between the application and the database is a good thing. But, if you think about it, there is a point of diminishing returns. While fetching 100 rows at once is far better than one at a time, fetching 1,000 rows at once instead of 100 is generally not really any more efficient overall, especially when you consider memory requirements. Another example of uncritical thinking is to focus on the wrong aspects of system design or configuration, rather than those most likely to improve performance (or, for that matter, reliability, availability, or security). Consider the “conventional wisdom” of tuning the system to maximize the buffer hit ratio. For some applications, it’s true that maximizing the chance that required data is in memory will maximize performance. However, for most applications it’s better to focus attention on performance bottlenecks (what we call “wait states”) than it is to focus on specific system-level metrics. Eliminate those aspects of the application design that are causing delays, and you’ll get the best performance. I’ve found that breaking down a problem into smaller parts and solving each part separately is a great way to think about application design. In this way, you can often find elegant and creative uses of SQL to address application requirements. Often, it is possible to do things in a single SQL statement that at first seem to require complex procedural programming. When you can leverage the power of SQL to process sets of rows at a time, perhaps in parallel, not only are you more productive as an application developer, but the application runs faster as well! Sometimes, best practices that were based, even in part, on some degree of truth become no longer applicable as the facts change. Consider the old adage, “Put indexes and data in separate tablespaces for best performance.” I’ve often seen database administrators express strong opinions over the merits of this idea, without taking into account changes in disk speeds and capacities over time, or the specifics of given workloads. In evaluating this particular “rule,” you should think about the fact that the Oracle database caches frequently and recently used database blocks (often blocks belonging to an index) in memory, and the fact that it uses index and data blocks sequentially, not simultaneously, for any given request. The implication is that I/O operations for both index and data really should be spread across all simultaneous users, and across as many disk drives as you have. You might choose to separate index and data blocks for administrative reasons or for personal preference, but not for performance. (Tom Kyte provides valuable insights on this topic on the Ask Tom web site, http:// asktom.oracle.com, where you can search for articles on “index data tablespace”.) The lesson here is to base your decisions on facts, and a complete set of current facts at that. No matter how fast our computers or how sophisticated the database becomes, and regardless of the power of our programming tools, there simply is no substitute for human intelligence coupled with a “thinking discipline.” So, while it’s important to learn the intricacies of the technologies we use in our applications, it’s even more important to know how to think about using them appropriately. Tom Kyte is one of the most intelligent people I know, and one of the most knowledgeable about the Oracle database, SQL, performance tuning, and application design. I’m pretty sure
Page 2 and 3: Expert Oracle Database Architecture
Page 4 and 5: Contents Foreword . . . . . . . . .
Page 6 and 7: ■CONTENTS v Block Buffer Cache .
Page 8 and 9: ■CONTENTS vii ■CHAPTER 9 Redo a
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Page 14 and 15: ■FOREWORD xiii Tom is an aficiona
Page 16 and 17: About the Technical Reviewers ■JO
Page 18 and 19: Introduction The inspiration for th
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Page 26 and 27: Setting Up Your Environment In this
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338 CHAPTER 10 ■ DATABASE TABLES
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CHAPTER 11 ■ ■ ■ Indexes Inde
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CHAPTER 11 ■ INDEXES 423 value of
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CHAPTER 11 ■ INDEXES 425 One of t
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CHAPTER 11 ■ INDEXES 431 The data
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CHAPTER 11 ■ INDEXES 445 Indicate
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CHAPTER 13 ■ ■ ■ Partitioning
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Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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