The effect of join selectives on optimal nesting order

Authors:
Akhil Kumar;Michael Stonebraker
Affiliations:
EECS Department, University of California, Berkeley, Ca.;EECS Department, University of California, Berkeley, Ca.
Venue:
ACM SIGMOD Record
Year:
1987

Citing 4
Cited 5

Access path selection in a relational database management system

SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Estimating block transfers and join sizes

SIGMOD '83 Proceedings of the 1983 ACM SIGMOD international conference on Management of data
Top-down statistical estimation on a database

SIGMOD '83 Proceedings of the 1983 ACM SIGMOD international conference on Management of data
Accurate estimation of the number of tuples satisfying a condition

SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data

Statistical profile estimation in database systems

ACM Computing Surveys (CSUR)
Join processing in relational databases

ACM Computing Surveys (CSUR)
Correcting execution of distributed queries

DPDS '90 Proceedings of the second international symposium on Databases in parallel and distributed systems
Deciding to Correct Distributed Query Processing

IEEE Transactions on Knowledge and Data Engineering
Domains and Active Domains: What This Distinction Implies for the Estimation of Projection Sizes in Relational Databases

IEEE Transactions on Knowledge and Data Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

A heuristic query optimizer must choose the best way to process an incoming query. This choice is based on comparing the expected cost of many (or all) of the ways that a command might be processed. This expected cost calculation is determined by statistics on the sizes of the relations involved and the selectivities of the operations being performed. Of course, such estimates are subject to error, and in this paper we investigate the sensitivity of the best query plan to errors in the selectivity estimates. We treat the common case of join queries and show that the optimal plan for most queries is very insensitive to selectivity inaccuracies. Hence, there is little reason for a data manager to spend a lot of effort making accurate estimates of join selectivities.