Title :
Automating statistics management for query optimizers
Author :
Chaudhuri, Surajit ; Narasayya, Vivek
Author_Institution :
Microsoft Corp., Redmond, WA, USA
Abstract :
Statistics play a key role in influencing the quality of plans chosen by a database query optimizer. 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 :
SQL; database theory; optimisation; query processing; relational databases; statistical databases; Microsoft SQL Server; database query optimizer; databases; experiment; query plan quality; statistics management; Costs; Database systems; Indexes; Quality management; Sensitivity analysis; Statistical analysis; Statistical distributions; Statistics;
Conference_Titel :
Data Engineering, 2000. Proceedings. 16th International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7695-0506-6
DOI :
10.1109/ICDE.2000.839433
