Parallel database techniques

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Parallel database techniques / [edited by] Mahdi Abdelguerfi, Kam-Fai Wong

資料種別:

図書

出版情報:

Los Alamitos, CA : IEEE Computer Society, c1998

形態:

vii, 222 p. ; 26 cm

著者名:

ISBN:

9780818683985 [0818683988]

書誌ID:

BA37582541

子書誌情報

フルテキスト

所蔵情報

他の版・巻

書誌詳細

注記:

Includes bibliographical references

主題:

Database management; Parallel processing (Electronic computers)

言語:

英語

目次情報:

Introduction / 1：

Background / 1.1：

Parallel Database Systems / 1.2：

Computation Model / 1.2.1：

Engineering Model / 1.2.2：

About this Manuscript / 1.3：

Bibliography

Request Manager / I：

Designing an Optimizer for Parallel Relational Systems / 2：

Overall Design Issues / 2.1：

Design a Simple Parallel Execution Model / 2.2.1：

The Two-Phase Approach / 2.2.2：

Parallelizing is Adding Information! / 2.2.3：

Two-Phase versus Parallel Approaches / 2.2.4：

Parallelization / 2.3：

Kinds of Parallelism / 2.3.1：

Specifying Parallel Execution / 2.3.2：

Search Space / 2.4：

Slicing Hash Join Trees / 2.4.1：

Search Space Size / 2.4.2：

Heuristics / 2.4.3：

The Two-Phase Heuristics / 2.4.4：

Cost Model / 2.5：

Exceptions to the Principle of Optimality / 2.5.1：

Resources / 2.5.2：

Skew and Size Model / 2.5.3：

The Cost Function / 2.5.4：

Search Strategies / 2.6：

Deterministic Search Strategies / 2.6.1：

Randomized Strategies / 2.6.2：

Conclusion / 2.7：

New Approaches to Parallel Join Utilizing Page Connectivity Information / 3：

The Environment and a Motivating Example / 3.1：

The Methodology / 3.3：

Definition of Parameters / 3.3.1：

The Balancing Algorithm / 3.3.2：

Schedules for Reading Join Components and Data Pages / 3.3.3：

Performance Analysis / 3.4：

The Evaluation Method / 3.4.1：

Evaluation Results / 3.4.2：

Concluding Remarks and Future Work / 3.5：

A Performance Evaluation Tool for Parallel Database Systems / 4：

Performance Evaluation Methods / 4.1：

Analytical Modeling / 4.2.1：

Benchmarks / 4.2.2：

Observations / 4.2.3：

The Software Testpilot / 4.3：

The Experiment Specification / 4.3.1：

The Performance Assessment Cycle / 4.3.2：

The System Interface / 4.3.3：

The Software Testpilot and Oracle/Ncube / 4.4：

Database System Performance Assessment / 4.4.1：

The Oracle/Ncube Interface / 4.4.2：

Preliminary Results / 4.5：

Load Placement in Distributed High-Performance Database Systems / 4.6：

Investigated System / 5.1：

System Architecture / 5.2.1：

Load Scenarios / 5.2.2：

Trace Analysis / 5.2.3：

Load Setup / 5.2.4：

Load Placement Strategies Investigated / 5.3：

Scheduling Strategies for Transactions / 5.4：

Simulation Results / 5.5：

Influence of Scheduling / 5.5.1：

Evaluation of the Load Placement Strategies / 5.5.2：

Lessons Learned / 5.5.3：

Decision Parameters Used / 5.5.4：

Conclusion and Open Issues / 5.6：

Parallel Machine Architecture / II：

Modeling Recovery in Client-Server Database Systems / 6：

Uniprocessor Recovery and Formal Approach to Modeling Recovery / 6.1：

Basic Formal Concepts / 6.2.1：

Logging Mechanisms / 6.2.2：

Runtime Policies for Ensuring Correctness / 6.2.3：

Data Structures Maintained for Efficient Recovery / 6.2.4：

Restart Recovery--The ARIES Approach / 6.2.5：

LSN Sequencing Techniques for Multinode Systems / 6.3：

Recovery in Client-Server Database Systems / 6.4：

Client-Server EXODUS (ESM-CS) / 6.4.1：

Client-Server ARIES (ARIES/CSA) / 6.4.2：

Shared Nothing Clients with Disks (CD) / 6.4.3：

Summary of Recovery Approaches in Client-Server Architectures / 6.4.4：

Parallel Strategies for a Petabyte Multimedia Database Computer / 6.5：

Multimedia Data Warehouse, Databases, and Applications / 7.1：

Three Waves of Multimedia Database Development / 7.2.1：

National Medical Practice Knowledge Bank Application / 7.2.2：

Massively Parallel Architecture, Infrastructure, and Technology / 7.3：

Parallelism / 7.3.1：

Teradata-MM Architecture, Framework, and New Concepts / 7.4：

Teradata-MM Architecture / 7.4.1：

Key New Concepts / 7.4.2：

SQL3 / 7.4.3：

Federated Coordinator / 7.4.4：

Teradata Multimedia Object Server / 7.4.5：

Parallel UDF Execution Analysis / 7.5：

UDF Optimizations / 7.5.1：

PRAGMA Facility / 7.5.2：

UDF Value Persistence Facility / 7.5.3：

Spatial Indices for Content-Based Querying / 7.5.4：

The MEDUSA Project / 7.6：

Indexing and Data Partitioning / 8.1：

Standard Systems / 8.2.1：

Grid Files / 8.2.2：

Dynamic Load Balancing / 8.3：

Data Access Frequency / 8.3.1：

Data Distribution / 8.3.2：

Query Partitioning / 8.3.3：

The MEDUSA Architecture / 8.4：

Software / 8.4.2：

Grid File Implementation / 8.4.3：

Load Balancing Strategy / 8.4.4：

MEDUSA Performance Results / 8.5：

Test Configuration / 8.5.1：

Transaction Throughput / 8.5.2：

Speedup / 8.5.3：

Load Balancing Test Results / 8.5.4：

Conclusions / 8.6：

Partitioned Data Store / III：

System Software of the Super Database Computer SDC-II / 9：

Architectural Overview of the SDC-II / 9.1：

Design and Organization of the SDC-II System Software / 9.3：

Parallel Execution Model / 9.3.1：

I/O Model and Buffer Management Strategy for Bulk Data Transfer / 9.3.2：

Process Model and Efficient Flow Control Mechanism / 9.3.3：

Structure of the System Software Components / 9.3.4：

Evaluation of the SDC-II System / 9.4：

Details of a Sample Query Processing / 9.4.1：

Comparison with Commercial Systems / 9.4.2：

Data Placement in Parallel Database Systems / 9.5：

Overview of Data Placement Strategies / 10.1：

Declustering and Redistribution / 10.2.1：

Placement / 10.2.2：

Effects of Data Placement / 10.3：

STEADY and TPC-C / 10.3.1：

Dependence on Number of Processing Elements / 10.3.2：

Dependence on Database Size / 10.3.3：

Contributors / 10.4：

Introduction / 1：

Background / 1.1：

Parallel Database Systems / 1.2：

Computation Model / 1.2.1：

Engineering Model / 1.2.2：

About this Manuscript / 1.3：

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