High-Performance Parallel Database Processing

The growth in grid databases, coupled with the utility of parallel query processing, presents an important opportunity to understand and utilize high-performance parallel database processing within a major database management system (DBMS). This important new book provides readers with a fundamental understanding of parallelism in data-intensive applications, and demonstrates how to develop faster capabilities to support them. It presents a balanced treatment of the theoretical and practical aspects of high-performance databases to demonstrate how parallel query is executed in a DBMS, including concepts, algorithms, analytical models, and grid transactions.

David Taniar, PhD, lectures in information technology at Monash University, Australia. Dr. Taniar has published extensively in the field of high- performance parallel databases and is the Editor in Chief of the International Journal of Data Warehousing and Mining.

Clement H. C. Leung, PhD, is Foundation Chair in Computer Science at Victoria University, Australia. Dr. Leung previously held the Established Chair in Computer Science at the University of London.

Wenny Rahayu, PhD, is Associate Professor at La Trobe University, Australia, and actively works in the areas of database design and implementation, covering object-relational databases and Web databases.

Sushant Goel, PhD, is a software consultant and holds a PhD in computer systems engineering from RMIT University, Australia. His research interests are in grid transaction management and software development processes, such as agile computing.

Introduction
Introduction
A Brief Overview: Parallel Databases and Grid Databases
Parallel Query Processing: Motivations
Parallel Query Processing: Objectives
Forms of Parallelism
Parallel Database Architectures
Grid Database Architecture
Structure of this Book
Summary
Bibliographical Notes
Exercises
Analytical Models
Cost Models
Cost Notations
Skew Model
Basic Operations in Parallel Databases
Summary
Bibliographical Notes
Exercises
Basic Query Parallelism
Parallel Search
Search Queries
Data Partitioning
Search Algorithms
Summary
Bibliographical Notes
Exercises
Parallel Sort and Group-By
Sorting, Duplicate Removal, and Aggregate Queries
Serial External Sorting Method
Algorithms for Parallel External Sort
Parallel Algorithms for GroupBy Queries
Cost Models for Parallel Sort
Cost Models for Parallel GroupBy
Summary
Bibliographical Notes
Exercises iii
Parallel Join
Join Operations
Serial Join Algorithms
Parallel Join Algorithms
Cost Models
Parallel Join Optimization
Summary
Bibliographical Notes
Exercises
Advanced Parallel Query Processing
Parallel GroupBy-Join
GroupBy-Join Queries
Parallel Algorithms for GroupBy-Before-Join Query Processing
Parallel Algorithms for ?GroupBy-After-Join? Query Processing
Cost Model Notations
Cost Model for "GroupBy-Before-Join" Query Processing
Cost Model for "GroupBy-After-Join" Query Processing
Summary
Bibliographical Notes
Exercises
Parallel Indexing
Parallel Indexing - An Internal Sight of Parallel Indexing Structures
Parallel Indexing Structures
Index Maintenance
Index Storage Analysis
Parallel Processing of Search Queries Using Index
Parallel Index-Join Algorithms
Comparative Analysis
Summary
Bibliographical Notes
Exercises
Parallel Universal Quantification ? Collection Join Queries
Universal Quantification and Collection Join
Collection Types and Collection Join Queries
Parallel Algorithms for Collection Join Queries
Parallel Collection-Equi Join Algorithms
Parallel Collection-Intersect Join Algorithms
Parallel Sub-Collection Join Algorithms
Summary
Bibliographical Notes
Exercises
Parallel Query Scheduling and Optimization
Query Execution Plan
Sub-Queries Execution Scheduling Strategies
Serial vs. Parallel Execution Scheduling
Scheduling Rules
Cluster Query Processing Model
Dynamic Cluster Query Optimization
Other Approaches of Dynamic Query Optimization
Summary
Bibliographical Notes
Exercises
Grid Databases
Transactions in Distributed and Grid Databases
Grid Database Challenges
Distributed Database Systems and Multidatabase Systems
Basic Definitions on Transaction Management
ACID Properties of Transactions
Transaction Management in Various Database Systems
Requirements in Grid Database Systems
Concurrency Control Protocols
Atomic Commit Protocols
Replica Synchronization Protocols
Summary
Bibliographical Notes vi
Exercises
Grid Concurrency Control
A Grid Database Environment
An Example
Grid Concurrency Control
Correctness of GCC Protocol
Features of GCC Protocol
Summary
Bibliographical Notes
Exercises
Grid Transaction Atomicity and Durability
Motivation
Grid Atomic Commit Protocol (Grid-ACP
Handling Failure of Sites with Grid-ACP
Summary
Bibliographical Notes
Exercises
Replica Management in Grids
Motivation
Replica Architecture
Grid Replica Access Protocol (GRAP
Handling Multiple Partitioning
Summary
Bibliographical Notes
Exercises
Grid Atomic Commitment in Replicated Data
Motivation
Modified Grid Atomic Commitment Protocol
Transaction Properties in Replicated Environment
Summary
Bibliographical Notes
Exercises
Other Data Intensive Applications
Parallel Online Analytic Processing (OLAP) and Business Intelligence
Parallel Multidimensional Analysis
Parallelization of ROLLUP Queries
Parallelization of CUBE Queries
Parallelization of Top-N and Ranking Queries
Parallelization of CUME_DIST Queries
Parallelization of NTILE and Histogram Queries
Parallelization of Moving Average and Windowing Queries
Summary
Bibliographical Notes
Exercises
Parallel Data Mining - Association Rules and Sequential Patterns
From Databases, Data Warehousing, to Data Mining: A Journey
Data Mining: A Brief Overview
Parallel Association Rules
Parallel Sequential Patterns
Summary
Bibliographical Notes
Exercises
Parallel Clustering and Classification
Clustering and Classification
Parallel Clustering
Parallel Classification
Summary
Bibliographical Notes
Exercises
Table of Contents provided by Publisher. All Rights Reserved.

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High-Performance Parallel Database Processing and Grid Databases

Summary

Author Biography

Table of Contents

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