Efficient Bulk-Loading of Gridfiles

Abstract

This paper considers the problem of bulk-loading large data sets for the gridfile multi-attribute indexing technique. We propose a rectilinear partitioning algorithm that heuristically seeks to minimize the size of the gridfile needed to ensure no bucket overflows. Empirical studies on both synthetic data sets and on data sets drawn from computational fluid dynamics applications demonstrate that our algorithm is very efficient, and is able to handle large data sets. In addition, we present an algorithm for bulk-loading data sets too large to fit in main memory. Utilizing a sort of the entire data set it creates a gridfile without incurring any overflows. Gridfile, Bulk- loading, Scientific databases

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1994
Accession Number
ADA286283

Entities

People

  • David M. Nicol
  • Scott T. Leutenegger

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computational Fluid Dynamics
  • Computations
  • Computer Programming
  • Computer Science
  • Data Sets
  • Databases
  • Directories
  • Dynamic Programming
  • Engineering
  • Equations
  • Fluid Dynamics
  • Grids
  • Optimization
  • Parallel Computing
  • Quadrants
  • Relational Databases

Fields of Study

  • Computer science

Readers

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