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

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CHAPTER 7 ■ CONCURRENCY AND MULTI-VERSIONING 237 commits. This is one reason why many people have a bad habit of committing every statement, instead of processing well-formed transactions consisting of all of the statements needed to take the database from one consistent state to the next. Updates interfere with reads in most other databases. The really bad news in this scenario is that we are making the end user wait for the wrong answer. We still receive an answer that never existed in the database at any point in time, as with the dirty read, but this time we made the user wait for the wrong answer. In the next section, we’ll look at what these other databases need to do to achieve read-consistent, correct results. The important lesson here is that various databases executing in the same, apparently safe isolation level can and will return very different answers under the exact same circumstances. It is important to understand that, in Oracle, non-blocking reads are not had at the expense of correct answers. You can have your cake and eat it too, sometimes. REPEATABLE READ The goal of REPEATABLE READ is to provide an isolation level that gives consistent, correct answers and prevents lost updates. We’ll take a look at examples of both, see what we have to do in Oracle to achieve these goals, and examine what happens in other systems. Getting a Consistent Answer If we have a REPEATABLE READ isolation, the results from a given query must be consistent with respect to some point in time. Most databases (not Oracle) achieve repeatable reads via the use of row-level shared read locks. A shared read lock prevents other sessions from modifying data that we have read. This, of course, decreases concurrency. Oracle opted for the more concurrent, multi-versioning model to provide read-consistent answers. In Oracle, using multi-versioning, we get an answer that is consistent with respect to the point in time the query began execution. In other databases, using shared read locks, we get an answer that is consistent with respect to the point in time the query completes—that is, when we can get the answer at all (more on this in a moment). In a system that employs a shared read lock to provide repeatable reads, we would observe rows in a table getting locked as the query processed them. So, using the earlier example, as our query reads the ACCOUNTS table, it would leave shared read locks on each row, as shown in Table 7-5. Table 7-5. Timeline 1 in Non-Oracle Database Using READ REPEATABLE Isolation Time Query Account Transfer Transaction T1 T2 T3 Reads row 1. Sum = $500.00 so far. Block 1 has a shared read lock on it. Reads row 2. Sum = $740.25 so far. Block 2 has a shared read lock on it. T4 Reads row N. Sum = . . . Attempts to update row 1 but is blocked. Transaction is suspended until it can obtain an exclusive lock. Continued
238 CHAPTER 7 ■ CONCURRENCY AND MULTI-VERSIONING Table 7-5. Continued Time Query Account Transfer Transaction T5 T6 T7 T8 Reads row 342,023, sees $100.00, and presents final answer. Commits transaction. Updates row 1 and puts an exclusive lock on this block. Row 1 now has $100.00. Updates row 342,023 and puts an exclusive lock on this block. Row 342,023 now has $500.00. Commits transaction. Table 7-5 shows that we now get the correct answer, but at the cost of physically blocking one transaction and executing the two transactions sequentially. This is one of the side effects of shared read locks for consistent answers: readers of data will block writers of data. This is in addition to the fact that, in these systems, writers of data will block readers of data. Imagine if automatic teller machines (ATMs) worked this way in real life. So, you can see how shared read locks would inhibit concurrency, but they can also cause spurious errors to occur. In Table 7-6, we start with our original table, but this time with the goal of transferring $50.00 from account 987 to account 123. Table 7-6. Timeline 2 in Non-Oracle Database Using READ REPEATABLE Isolation Time Query Account Transfer Transaction T1 T2 T3 Reads row 1. Sum = $500.00 so far. Block 1 has a shared read lock on it. Reads row 2. Sum = $740.25 so far. Block 2 has a shared read lock on it. T4 Reads row N. Sum = . . . T5 T6 Attempts to read row 342,023 but cannot as an exclusive lock is already in place. Updates row 342,023 and puts an exclusive lock on block 342,023, preventing other updates and shared read locks. This row now has $50.00. Attempts to update row 1 but is blocked. Transaction is suspended until it can obtain an exclusive lock. We have just reached the classic deadlock condition. Our query holds resources the update needs and vice versa. Our query has just deadlocked with our update transaction. One of them will be chosen as the victim and will be killed. We just spent a lot of time and resources only to fail and get rolled back at the end. This is the second side effect of shared read locks: readers and writers of data can and frequently will deadlock each other. As we have seen in Oracle, we have statement-level read consistency without reads blocking writes or deadlocks. Oracle never uses shared read locks—ever. Oracle has chosen the harder-to-implement but infinitely more concurrent multi-versioning scheme.
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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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Foreword “THINK.” In 1914, Thom
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About the Technical Reviewers ■JO
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Introduction The inspiration for th
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