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New Concepts for Parallel Object-Relational Query Processing [electronic resource] / by Michael Jaedicke.

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 2169Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2001Description: XI, 161 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540455073
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 005.74 23
LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Background on User-Defined Routines -- Parallel of User-Defined Functions -- Intra-function Parallelism -- The Multi-operator Method -- User-Defined Table Operators -- Implementation of UDTO -- Summary, Conclusions, and Future Work.
In: Springer eBooksSummary: 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.
Item type: E-BOOKS
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Background on User-Defined Routines -- Parallel of User-Defined Functions -- Intra-function Parallelism -- The Multi-operator Method -- User-Defined Table Operators -- Implementation of UDTO -- Summary, Conclusions, and Future Work.

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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The Institute of Mathematical Sciences, Chennai, India