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Parallel processing is becoming increasingly important to database computing. Databases often grow to enormous sizes and are accessed by huge numbers of users. This growth strains the ability of single-processor and single-computer systems to handle the load. More and more, organizations are turning to parallel processing technologies to give them the performance, scalability, and reliability they need. Anyone managing a large database, a database with a large number of concurrent users, or a database with high availability requirements—such as a heavily trafficked e-commerce site—needs to know how to get the most out of Oracle's parallel processing technologies.Oracle Parallel Processing is the first book to describe the full range of parallel processing capabilities in the Oracle environment, including those new to Oracle8i. It covers:
Dedication;
Preface;
Why We Wrote This Book;
Audience for This Book;
Which Platform and Version?;
Structure of This Book;
Conventions Used in This Book;
Comments and Questions;
Acknowledgments;
Overview;
Chapter 1: Introduction;
1.1 About Parallel Processing;
1.2 Parallel Processing for Databases;
1.3 Parallel Processing in Oracle;
1.4 Overhead for Oracle Parallel Processing;
1.5 Requirements for Oracle’s Parallel Features;
Chapter 2: Architectures for Parallel Processing;
2.1 Hardware Architectures;
2.2 High-Speed Interconnect;
2.3 Software Architectures of Parallel Database Systems;
2.4 Oracle’s Parallel Processing Architecture;
Oracle Parallel Execution;
Chapter 3: Parallel Execution Concepts;
3.1 What Is Parallel SQL?;
3.2 How Parallel Execution Works;
Chapter 4: Using Parallel Execution;
4.1 Parallel Query;
4.2 Parallel DML;
4.3 Parallel DDL;
4.4 Parallel Data Loading;
4.5 Parallel Recovery;
4.6 Parallel Replication Propagation;
Chapter 5: Monitoring and Tuning Parallel Execution;
5.1 Tuning Overview;
5.2 Dynamic Performance Views;
5.3 Using EXPLAIN PLAN to View Parallel Execution;
5.4 Tuning Tips for Parallel Execution;
5.5 Automatic Tuning of Parallel Execution in Oracle8i;
Oracle Parallel Server;
Chapter 6: Oracle Parallel Server Architecture;
6.1 OPS and Oracle Instances;
6.2 Synchronization Between Instances;
6.3 OPS Impact on Database Files;
6.4 Integrated Distributed Lock Manager;
6.5 Group Membership Service;
6.6 Rollback Segments in OPS;
Chapter 7: Administering an OPS Database;
7.1 Creating an OPS Database;
7.2 Starting and Stopping an OPS Database;
7.3 Managing Instance Groups;
7.4 Backing Up an OPS Database;
7.5 Recovering an OPS Database;
Chapter 8: Locking Mechanisms in OPS;
8.1 Cache Coherency;
8.2 Lock Types in OPS;
8.3 Lock Modes;
8.4 Parallel Cache Management;
8.5 PCM Lock Types;
8.6 PCM Lock Allocation Parameters and Verification;
8.7 PCM Lock Allocation Guidelines;
8.8 Non-PCM Locks;
Chapter 9: Storage Management in OPS;
9.1 Using Free Lists and Free List Groups;
9.2 The PCTFREE Parameter: Reserving Free Space;
9.3 Using Reverse Key Indexes;
Chapter 10: Monitoring and Tuning OPS;
10.1 OPS Performance Views;
10.2 Dynamic Performance Views;
10.3 Monitoring PCM Locking;
10.4 Monitoring Overall Statistics;
10.5 Monitoring and Tuning IDLM;
10.6 Oracle Performance Manager;
Chapter 11: Partitioning for OPS;
11.1 When Is Partitioning Needed?;
11.2 Partitioning Techniques;
11.3 Changing Your Partitioning Scheme;
Chapter 12: Application Failover;
12.1 Maintaining a Failover Database;
12.2 Planning for Failover with OPS;
12.3 Failover Complexity;
12.4 Failover Methods;
Chapter 13: Parallel Execution in OPS;
13.1 How Parallel Execution Works with OPS;
13.2 Disk Affinity;
13.3 Instance Groups for Parallel Execution;
Appendix: Case Studies;
Application Suitability;
Case Study 1: An OLTP Application on an SMP Platform;
Case Study 2: An OLTP Application on a Cluster;
Case Study 3: A DSS Application on an MPP Platform;
Colophon;
Overview
Parallel processing is becoming increasingly important to database computing. Databases often grow to enormous sizes and are accessed by huge numbers of users. This growth strains the ability of single-processor and single-computer systems to handle the load. More and more, organizations are turning to parallel processing technologies to give them the performance, scalability, and reliability they need. Anyone managing a large database, a database with a large number of concurrent users, or a database with high ...