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New Concepts for Parallel Object-Relational Query Processing

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ISBN-10: 3540427813

ISBN-13: 9783540427810

Edition: 2001

Authors: Michael Jaedicke

List price: $54.99
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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…    
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Book details

List price: $54.99
Copyright year: 2001
Publisher: Springer Berlin / Heidelberg
Publication date: 10/17/2001
Binding: Paperback
Pages: 163
Size: 6.10" wide x 9.25" long x 0.50" tall
Weight: 1.210
Language: English

ORDBMS: The Next Great Wave
Extensible DBMS
Background on User-Defined Routines
User-Defined Routines
Definition, Implementation, and Execution of New UDR
User-Defined Scalar Functions
User-Defined Aggregate Functions
User-Defined Table Functions
User-Defined Functions and Large Objects
Comparison with Stored Procedures
Optimization of Queries with UDF
Parallel Processing of User-Defined Functions
Limits of Current ORDBMS
Parallel Processing of UDF
Two Step Parallel Aggregation of UDAF
Partitioning Classes and Partitionable Functions
Parallel Sorting as a Preprocessing Step for UDAF
Extended Syntax for Function Registration
Example Applications
The UDAF Most_Frequent
The UDSF Running_Average
The UDAF Median
Further Applications
Plausibility Considerations Regarding Performance
Related Work
Intra-function Parallelism
Compose/Decompose Operators for Intra-function Parallelism
Compose/Decompose Operators
Extensibility of Compose Operators by Combine Functions
Application of Intra-function Parallelism
Intra-function Parallelism for Function Pipelines
Experimental Performance Study
Experimental Scenario and Implementation
Performance Results
Related Work
The Multi-operator Method
Performance Problems with Complex UDF in Current ORDBMS
The PBSM Algorithm as a Sophisticated UDP Implementation
The Multi-operator Method as a New Technique to Implement Complex UDF
The Multi-operator Method and Its Benefits
A Multi-operator Implementation of the PBSM Algorithm
Supporting the Multi-operator Method
Executing Query Execution Plans
Example for a Textual Specification of Query Execution Plans
Parallel Evaluation
Performance Evaluation
Experimental Scenario
Performance Results
Related Work
User-Defined Table Operators
User-Defined Table Operators
A Generalization Relationship for Row Types
Defining and Implementing UDTO
The Different Usages of the UDTO Concept
Parallel Processing of Procedural UDTO
Extension to Multiple Output Tables
Example Applications for UDTO
Computing a Spatial Join
Different UDTO for the Same Predicate
Computing the Median: An Aggregation Operator
A UDTO for a Complex Aggregation
Association Rule Mining
Related Work
Summary and Conclusions
Implementation of UDTO
The MIDAS Prototype
Architectural Overview
Query Compilation and Execution
The MIDAS System Tables
Implementation of SQL Macros
DDL Statements
SQL Macro Expansion in DML Statements
Expanding SQL Macros in Preprocessors and Middleware
Implementation of Procedural UDTO
Extensions to the SQL Compiler
Extensions to the Optimizer and the Parallelizer
Extensions to the Scheduler
Extensions to the Execution Engine
Extensions to Transaction Management
Implementation of Input and Output Tables
Optimization Issues for UDTO
UDTO and Implied Predicates
Estimating Costs and Selectivity of UDTO
Application of Traditional Optimization Rules
Using UDTO to Generate Alternative Execution Plans for UDF
Evaluation of the Implementation
Evaluation of SQL Macros
Evaluation of Procedural UDTO
Summary, Conclusions, and Future Work
Future Work
Appendix A
The Program sequential_invert
The Program parallel_invert
The Query Execution Plan for the Spatial Join with SQL Macro