Query size estimation by adaptive sampling
Selected papers of the 9th annual ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Random sampling for histogram construction: how much is enough?
SIGMOD '98 Proceedings of the 1998 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
An Evaluation of Sampling-Based Size Estimation Methods for Selections in Database Systems
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Oracle Database 10g New Features: Oracle10g Reference for Advanced Tuning and Administration
Oracle Database 10g New Features: Oracle10g Reference for Advanced Tuning and Administration
Estimating nested selectivity in object-oriented and object-relational databases
Information and Software Technology
| Hi-index | 0.00 |
Sybase ASE (Adaptive Server Enterprise) is a cost based database system. Statistics information plays a key role in the costing model of ASE optimizer. Typically, up-to-date statistics is critical in selecting an optimal query plan with good performance. However, updating statistics is a resource intensive maintenance operation. A common user concern is the lack of input on when statistics needs to be updated and also the time taken to maintain the statistics. In this paper, we introduce a new solution for automating statistics maintenance in Sybase ASE 15.0. Our solution includes a new metric for evaluating data changes due to DMLs (Data Management Language), the use of a scheduler to generate rules to gather statistics based on feedback from the metric and random sampling of data when gathering statistics. This approach will make statistics maintenance more intelligent and efficient, and reduce the TCO (Total Cost of Ownership) significantly.