Title :
Automating statistics management for query optimizers
Author :
Chaudhuri, Surajit ; Narasayya, Vivek
Author_Institution :
Data Manage., Exploration & Min. Group, Microsoft Corp., Redmond, WA, USA
Abstract :
Statistics play a key role in influencing the quality of plans chosen by a database query optimizer. In this paper, we identify the statistics that are essential for an optimizer. We introduce novel techniques that help significantly reduce the set of statistics that need to be created without sacrificing the quality of query plans generated. We discuss how these techniques can be leveraged to automate statistics management in databases. We have implemented and experimentally evaluated our approach on Microsoft SQL Server 7.0
Keywords :
query processing; relational databases; statistics; Microsoft SQL Server 7.0; database query optimizer; plan quality; statistics management automation; Computer Society; Costs; Database systems; Helium; Indexes; Quality management; Sensitivity analysis; Statistical analysis; Statistical distributions; Statistics;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
