Lecture Notes in Computer Science : Lecture Notes in Computer Science - Michael Jaedicke

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Lecture Notes in Computer Science

By: Michael Jaedicke

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Paperback | 17 October 2001

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172 Pages

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22.86 x 15.88 x 1.27

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During the last few years, parallel object-relational database management systems have emerged as the leading data management technology on the market. These systems are extensible by user-defined data types and user-defined functionality for the data.
This work focuses on the efficient parallel execution of user-defined functionality. The main contributions describe techniques to support data parallelism for user-defined scalar and aggregate functions and intra-function parallelism for the execution of a scalar function on a large object, and a new technology to provide extensibility with regard to new set-oriented database operations that can efficiently implement user-defined functionality in parallel object-relational database management systems.

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Non-Fiction Computing & I.T.Databases Computer Science Computer Architecture & Logic Design Parallel Processing Artificial Intelligence Expert Systems & Knowledge-Based Systems Medicine Medicine in General Business & Management Management & Management Techniques

Computer Programming & Software Development Object-Oriented Programming or OOP

Introduction
ORDBMS: The Next Great Wave	p. 1
Extensible DBMS	p. 2
Overview	p. 3
Background on User-Defined Routines
User-Defined Routines	p. 5
Definition, Implementation, and Execution of New UDR	p. 6
User-Defined Scalar Functions	p. 7
User-Defined Aggregate Functions	p. 9
User-Defined Table Functions	p. 10
User-Defined Functions and Large Objects	p. 11
Comparison with Stored Procedures	p. 12
Optimization of Queries with UDF	p. 12
Parallel Processing of User-Defined Functions
Introduction	p. 14
Limits of Current ORDBMS	p. 15
Parallel Processing of UDF	p. 17
Two Step Parallel Aggregation of UDAF	p. 17
Partitioning Classes and Partitionable Functions	p. 18
Parallel Sorting as a Preprocessing Step for UDAF	p. 21
Extended Syntax for Function Registration	p. 22
Example Applications	p. 24
The UDAF Most_Frequent	p. 24
The UDSF Running_Average	p. 25
The UDAF Median	p. 25
Further Applications	p. 26
Plausibility Considerations Regarding Performance	p. 28
Related Work	p. 30
Summary	p. 31
Intra-function Parallelism
Introduction	p. 33
Compose/Decompose Operators for Intra-function Parallelism	p. 34
Compose/Decompose Operators	p. 34
Extensibility of Compose Operators by Combine Functions	p. 36
Application of Intra-function Parallelism	p. 37
Intra-function Parallelism for Function Pipelines	p. 38
Experimental Performance Study	p. 39
Experimental Scenario and Implementation	p. 39
Performance Results	p. 41
Related Work	p. 43
Summary	p. 44
The Multi-operator Method
Introduction	p. 45
Performance Problems with Complex UDF in Current ORDBMS	p. 46
The PBSM Algorithm as a Sophisticated UDP Implementation	p. 47
The Multi-operator Method as a New Technique to Implement Complex UDF	p. 49
The Multi-operator Method and Its Benefits	p. 49
A Multi-operator Implementation of the PBSM Algorithm	p. 51
Supporting the Multi-operator Method	p. 53
Executing Query Execution Plans	p. 53
Example for a Textual Specification of Query Execution Plans	p. 55
Parallel Evaluation	p. 55
Performance Evaluation	p. 56
Experimental Scenario	p. 56
Performance Results	p. 62
Related Work	p. 64
Summary	p. 65
User-Defined Table Operators
Introduction	p. 67
User-Defined Table Operators	p. 68
A Generalization Relationship for Row Types	p. 68
Defining and Implementing UDTO	p. 69
The Different Usages of the UDTO Concept	p. 74
Parallel Processing of Procedural UDTO	p. 77
Extension to Multiple Output Tables	p. 80
Example Applications for UDTO	p. 81
Computing a Spatial Join	p. 81
Different UDTO for the Same Predicate	p. 85
Computing the Median: An Aggregation Operator	p. 89
A UDTO for a Complex Aggregation	p. 90
Association Rule Mining	p. 94
Related Work	p. 101
Summary and Conclusions	p. 102
Implementation of UDTO
Introduction	p. 106
The MIDAS Prototype	p. 106
Architectural Overview	p. 107
Query Compilation and Execution	p. 108
The MIDAS System Tables	p. 111
UDSF in MIDAS	p. 112
Implementation of SQL Macros	p. 113
DDL Statements	p. 113
SQL Macro Expansion in DML Statements	p. 115
Expanding SQL Macros in Preprocessors and Middleware	p. 116
Implementation of Procedural UDTO	p. 123
Extensions to the SQL Compiler	p. 123
Extensions to the Optimizer and the Parallelizer	p. 125
Extensions to the Scheduler	p. 126
Extensions to the Execution Engine	p. 126
Extensions to Transaction Management	p. 128
Implementation of Input and Output Tables	p. 131
Optimization Issues for UDTO	p. 134
UDTO and Implied Predicates	p. 134
Estimating Costs and Selectivity of UDTO	p. 135
Application of Traditional Optimization Rules	p. 137
Using UDTO to Generate Alternative Execution Plans for UDF	p. 138
Evaluation of the Implementation	p. 139
Evaluation of SQL Macros	p. 140
Evaluation of Procedural UDTO	p. 142
Summary	p. 144
Summary, Conclusions, and Future Work
Summary	p. 145
Conclusions	p. 146
Future Work	p. 149
References
References	p. 151
Appendix A
The Program sequential_invert	p. 157
The Program parallel_invert	p. 158
The Query Execution Plan for the Spatial Join with SQL Macro	p. 159
Table of Contents provided by Publisher. All Rights Reserved.

Lecture Notes in Computer Science

At a Glance

Paperback

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