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

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CHAPTER 1 ■ DEVELOPING SUCCESSFUL ORACLE APPLICATIONS 37 They needed to be able to report on the parent record with aggregates from each of the child tables. The databases they worked with in the past did not support subquery factoring (WITH clause), nor did they support inline views, the ability to “query a query” instead of query a table. Not knowing these features existed, the developers wrote their own database of sorts in the middle tier. They would query the parent table and for each row returned run an aggregate query against each of the child tables. This resulted in their running thousands of queries for each single query the end user wanted to run. Or, they would fetch the entire aggregated child tables into their middle tier into hash tables in memory—and do a hash join. In short, they were reinventing the database, performing the functional equivalent of a nested loops join or a hash join, without the benefit of temporary tablespaces, sophisticated query optimizers, and the like. They were spending their time developing, designing, finetuning, and enhancing software that was trying to do the same thing the database they already bought did! Meanwhile, end users were asking for new features but not getting them, because the bulk of the development time was in this reporting “engine,” which really was a database engine in disguise. I showed them that they could do things such as join two aggregations together, in order to compare data that was stored at different levels of detail in many different ways (see Listings 1-1 through 1-3). Listing 1-1. Inline Views: Query from a “Query” select p.id, c1_sum1, c2_sum2 from p, (select id, sum(q1) c1_sum1 from c1 group by id) c1, (select id, sum(q2) c2_sum2 from c2 group by id) c2 where p.id = c1.id and p.id = c2.id / Listing 1-2. Scalar Subqueries: Run Another Query per Row select p.id, (select sum(q1) from c1 where c1.id = p.id) c1_sum1, (select sum(q2) from c2 where c2.id = p.id) c2_sum2 from p where p.name = '1234' / Listing 1-3. WITH Subquery Factoring with c1_vw as (select id, sum(q1) c1_sum1 from c1
38 CHAPTER 1 ■ DEVELOPING SUCCESSFUL ORACLE APPLICATIONS group by id), c2_vw as (select id, sum(q2) c2_sum2 from c2 group by id), c1_c2 as (select c1.id, c1.c1_sum1, c2.c2_sum2 from c1_vw c1, c2_vw c2 where c1.id = c2.id ) select p.id, c1_sum1, c2_sum2 from p, c1_c2 where p.id = c1_c2.id / Not to mention what they can do with analytic functions like LAG, LEAD, ROW_NUMBER; the ranking functions; and so much more. Well, rather than spending the rest of the day trying to figure out how to tune their middle-tier database engine, we spent the day with the SQL Reference Guide projected on the screen (coupled with SQL*Plus to create ad hoc demonstrations of how things worked). The end goal was no longer tuning the middle tier; now it was turning off the middle tier as quickly as possible. I have seen people set up daemon processes in an Oracle database that read messages off of pipes (a database IPC mechanism). These daemon processes execute the SQL contained within the pipe message and commit the work. They did this so that they could execute auditing in a transaction that would not get rolled back if the bigger transaction did. Usually, if a trigger or something were used to audit an access to some data, but a statement failed later on, all of the work would be rolled back. So, by sending a message to another process, they could have a separate transaction do the work and commit it. The audit record would stay around, even if the parent transaction rolled back. In versions of Oracle before Oracle8i, this was an appropriate (and pretty much the only) way to implement this functionality. When I told them of the database feature called autonomous transactions, they were quite upset with themselves. Autonomous transactions, implemented with a single line of code, do exactly what they were doing. On the bright side, this meant they could discard a lot of code and not have to maintain it. In addition, the system ran faster overall and was easier to understand. Still, they were upset at the amount of time they had wasted reinventing the wheel. In particular, the developer who wrote the daemon processes was quite upset at having just written a bunch of shelfware. This is something I see repeated time and time again—large, complex solutions to problems that are already solved by the database itself. I’ve been guilty of this myself. I still remember the day when my Oracle sales consultant (I was the customer at the time) walked in and saw me surrounded by a ton of Oracle documentation. I looked up at him and just asked “Is this all true?” I spent the next couple of days just digging and reading. I had fallen into the trap of thinking “I know all about databases,” because I had worked with SQL/DS, DB2, Ingress, Sybase, Informix, SQLBase, Oracle, and others. Rather than take the time to see what each had to offer, I would just apply what I knew from the others to whatever I was working on. (Moving to Sybase/SQL Server was the biggest shock to me—it worked nothing like the others at all.) Upon actually discovering what Oracle could do (and the others, to be fair), I started taking advantage of it and was able to move faster, with less code. This was in 1993. Imagine what you can do with the software today, over a decade later.
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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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■CONTENTS vii ■CHAPTER 9 Redo a
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■CONTENTS ix ■CHAPTER 12 Dataty
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Foreword “THINK.” In 1914, Thom
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■FOREWORD xiii Tom is an aficiona
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About the Technical Reviewers ■JO
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Introduction The inspiration for th
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■INTRODUCTION xix • Exposure to
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■INTRODUCTION xxi Chapter 3: File
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■INTRODUCTION xxiii Next up are t
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Setting Up Your Environment In this
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■SETTING UP YOUR ENVIRONMENT xxvi
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CHAPTER 3 ■ FILES 89 A Brief Revi
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CHAPTER 3 ■ FILES 95 dictionary t
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CHAPTER 4 ■ MEMORY STRUCTURES 117
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CHAPTER 5 ■ ORACLE PROCESSES 157
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CHAPTER 6 ■ LOCKING AND LATCHING
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CHAPTER 8 ■ ■ ■ Transactions
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284 CHAPTER 9 ■ REDO AND UNDO cri
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286 CHAPTER 9 ■ REDO AND UNDO Fir
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288 CHAPTER 9 ■ REDO AND UNDO The
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290 CHAPTER 9 ■ REDO AND UNDO We
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292 CHAPTER 9 ■ REDO AND UNDO Wha
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294 CHAPTER 9 ■ REDO AND UNDO row
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296 CHAPTER 9 ■ REDO AND UNDO If
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298 CHAPTER 9 ■ REDO AND UNDO ops
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300 CHAPTER 9 ■ REDO AND UNDO Inv
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314 CHAPTER 9 ■ REDO AND UNDO •
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316 CHAPTER 9 ■ REDO AND UNDO ...
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318 CHAPTER 9 ■ REDO AND UNDO •
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328 CHAPTER 9 ■ REDO AND UNDO Thi
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332 CHAPTER 9 ■ REDO AND UNDO Whe
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334 CHAPTER 9 ■ REDO AND UNDO Tha
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336 CHAPTER 9 ■ REDO AND UNDO tou
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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 427 We then
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CHAPTER 11 ■ INDEXES 429 we ended
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CHAPTER 11 ■ INDEXES 431 The data
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CHAPTER 11 ■ INDEXES 435 Table 11
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CHAPTER 11 ■ INDEXES 439 an 8KB b
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CHAPTER 11 ■ INDEXES 441 select *
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CHAPTER 11 ■ INDEXES 445 Indicate
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CHAPTER 11 ■ INDEXES 447 an index
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CHAPTER 11 ■ INDEXES 449 Table 11
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CHAPTER 11 ■ INDEXES 453 column w
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CHAPTER 13 ■ ■ ■ Partitioning
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CHAPTER 13 ■ PARTITIONING 565 Enh
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Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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