Adaptive access path selection for relational database systems

Yann-Hang Lee, Philip S. Yu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Query optimization is crucial to relational database performance. Traditional approaches select the access plan with the minimum projected cost based on estimated selectivity. Since estimates can deviate substantial from true values, the access plan chosen can be far from optimal. We propose an adaptive approach which utilizes the information embedded in indexes to identify the tuples satisfying a select predicate or having a match in a join operation. Then, access path (index or table scan) and join method (index join, nested loop, sort-merge) are chosen to construct the results progressively. This leads to the optimal evaluation of queries and substantial performance improvement. With an efficient implementation, the decision process becomes a part of query evaluation procedure and imposes a minimal overhead.

Original languageEnglish (US)
Pages (from-to)52-61
Number of pages10
JournalComputer Systems Science and Engineering
Volume7
Issue number1
StatePublished - Jan 1992
Externally publishedYes

Fingerprint

Relational database systems
Database Systems
Relational Database
Join
Path
Costs
Query Evaluation
Query Optimization
Selectivity
Efficient Implementation
Predicate
Sort
Table
Query
Evaluation
Estimate

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Hardware and Architecture
  • Theoretical Computer Science

Cite this

Adaptive access path selection for relational database systems. / Lee, Yann-Hang; Yu, Philip S.

In: Computer Systems Science and Engineering, Vol. 7, No. 1, 01.1992, p. 52-61.

Research output: Contribution to journalArticle

@article{d67bd1d81baa46efa6880e5d091d5b9b,
title = "Adaptive access path selection for relational database systems",
abstract = "Query optimization is crucial to relational database performance. Traditional approaches select the access plan with the minimum projected cost based on estimated selectivity. Since estimates can deviate substantial from true values, the access plan chosen can be far from optimal. We propose an adaptive approach which utilizes the information embedded in indexes to identify the tuples satisfying a select predicate or having a match in a join operation. Then, access path (index or table scan) and join method (index join, nested loop, sort-merge) are chosen to construct the results progressively. This leads to the optimal evaluation of queries and substantial performance improvement. With an efficient implementation, the decision process becomes a part of query evaluation procedure and imposes a minimal overhead.",
author = "Yann-Hang Lee and Yu, {Philip S.}",
year = "1992",
month = "1",
language = "English (US)",
volume = "7",
pages = "52--61",
journal = "Computer Systems Science and Engineering",
issn = "0267-6192",
publisher = "CRL Publishing",
number = "1",

}

TY - JOUR

T1 - Adaptive access path selection for relational database systems

AU - Lee, Yann-Hang

AU - Yu, Philip S.

PY - 1992/1

Y1 - 1992/1

N2 - Query optimization is crucial to relational database performance. Traditional approaches select the access plan with the minimum projected cost based on estimated selectivity. Since estimates can deviate substantial from true values, the access plan chosen can be far from optimal. We propose an adaptive approach which utilizes the information embedded in indexes to identify the tuples satisfying a select predicate or having a match in a join operation. Then, access path (index or table scan) and join method (index join, nested loop, sort-merge) are chosen to construct the results progressively. This leads to the optimal evaluation of queries and substantial performance improvement. With an efficient implementation, the decision process becomes a part of query evaluation procedure and imposes a minimal overhead.

AB - Query optimization is crucial to relational database performance. Traditional approaches select the access plan with the minimum projected cost based on estimated selectivity. Since estimates can deviate substantial from true values, the access plan chosen can be far from optimal. We propose an adaptive approach which utilizes the information embedded in indexes to identify the tuples satisfying a select predicate or having a match in a join operation. Then, access path (index or table scan) and join method (index join, nested loop, sort-merge) are chosen to construct the results progressively. This leads to the optimal evaluation of queries and substantial performance improvement. With an efficient implementation, the decision process becomes a part of query evaluation procedure and imposes a minimal overhead.

UR - http://www.scopus.com/inward/record.url?scp=0026623830&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026623830&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0026623830

VL - 7

SP - 52

EP - 61

JO - Computer Systems Science and Engineering

JF - Computer Systems Science and Engineering

SN - 0267-6192

IS - 1

ER -