2. Preface Exponential growth of data volume, steady drop in storage costs, and rapid increase in storage capacity Inadequacy of the sequential processing paradigm Example: Assuming a data rate of 1 terabyte/sec, reading through a petabyte database will take over 10 days Parallel machines in the past, and parallel facilities in today’s commercial DBMS Importance of understanding high-performance and parallel database processing systems Grid as global and distributed data centres New application domains (data-intensive applications): data warehousing and online analytic processing, and data mining

3. Table of Contents 1. Introduction 2. Analytical Models 3. Parallel Search 4. Parallel Sort and Group By 5. Parallel Join 6. Parallel GroupBy-Join 7. Parallel Indexing 8. Parallel Universal Quantification - Collection Join Queries 9. Parallel Query Scheduling and Optimization 10. Transactions in Distributed and Grid Databases 11. Grid Concurrency Control 12. Grid Transaction Atomicity and Durability 13. Replica Management in Grids 14. Grid Atomic Commitment in Replicated Data 15. Parallel Online Analytic Processing (OLAP) and Business Intelligence 16. Parallel Data Mining - Association Rules and Sequential Patterns 17. Parallel Clustering and Classification

4. Table of Contents 1. Introduction 2. Analytical Models 3. Parallel Search 4. Parallel Sort and Group By 5. Parallel Join 6. Parallel GroupBy-Join 7. Parallel Indexing 8. Parallel Universal Quantification - Collection Join Queries 9. Parallel Query Scheduling and Optimization 10. Transactions in Distributed and Grid Databases 11. Grid Concurrency Control 12. Grid Transaction Atomicity and Durability 13. Replica Management in Grids 14. Grid Atomic Commitment in Replicated Data 15. Parallel Online Analytic Processing (OLAP) and Business Intelligence 16. Parallel Data Mining - Association Rules and Sequential Patterns 17. Parallel Clustering and Classification Part I: Introduction

5. Table of Contents 1. Introduction 2. Analytical Models 3. Parallel Search 4. Parallel Sort and Group By 5. Parallel Join 6. Parallel GroupBy-Join 7. Parallel Indexing 8. Parallel Universal Quantification - Collection Join Queries 9. Parallel Query Scheduling and Optimization 10. Transactions in Distributed and Grid Databases 11. Grid Concurrency Control 12. Grid Transaction Atomicity and Durability 13. Replica Management in Grids 14. Grid Atomic Commitment in Replicated Data 15. Parallel Online Analytic Processing (OLAP) and Business Intelligence 16. Parallel Data Mining - Association Rules and Sequential Patterns 17. Parallel Clustering and Classification Part II: Basic Query Parallelism

6. Table of Contents 1. Introduction 2. Analytical Models 3. Parallel Search 4. Parallel Sort and Group By 5. Parallel Join 6. Parallel GroupBy-Join 7. Parallel Indexing 8. Parallel Universal Quantification - Collection Join Queries 9. Parallel Query Scheduling and Optimization 10. Transactions in Distributed and Grid Databases 11. Grid Concurrency Control 12. Grid Transaction Atomicity and Durability 13. Replica Management in Grids 14. Grid Atomic Commitment in Replicated Data 15. Parallel Online Analytic Processing (OLAP) and Business Intelligence 16. Parallel Data Mining - Association Rules and Sequential Patterns 17. Parallel Clustering and Classification Part III: Advanced Parallel Query Processing

7. Table of Contents 1. Introduction 2. Analytical Models 3. Parallel Search 4. Parallel Sort and Group By 5. Parallel Join 6. Parallel GroupBy-Join 7. Parallel Indexing 8. Parallel Universal Quantification - Collection Join Queries 9. Parallel Query Scheduling and Optimization 10. Transactions in Distributed and Grid Databases 11. Grid Concurrency Control 12. Grid Transaction Atomicity and Durability 13. Replica Management in Grids 14. Grid Atomic Commitment in Replicated Data 15. Parallel Online Analytic Processing (OLAP) and Business Intelligence 16. Parallel Data Mining - Association Rules and Sequential Patterns 17. Parallel Clustering and Classification Part IV: Grid Databases

8. Table of Contents 1. Introduction 2. Analytical Models 3. Parallel Search 4. Parallel Sort and Group By 5. Parallel Join 6. Parallel GroupBy-Join 7. Parallel Indexing 8. Parallel Universal Quantification - Collection Join Queries 9. Parallel Query Scheduling and Optimization 10. Transactions in Distributed and Grid Databases 11. Grid Concurrency Control 12. Grid Transaction Atomicity and Durability 13. Replica Management in Grids 14. Grid Atomic Commitment in Replicated Data 15. Parallel Online Analytic Processing (OLAP) and Business Intelligence 16. Parallel Data Mining - Association Rules and Sequential Patterns 17. Parallel Clustering and Classification Part V: Other Data-Intensive Applications

9. Let’s go to Chapter 1…