Abstract: According to an embodiment of the present invention, methods, systems, and computer readable media are provided for collecting statistics for use in optimizing a database query. Collected statistics for the database are compared to corresponding predetermined states of conditions for optimizing the database query. One or more collected statistics in compliance with the corresponding predetermined states of conditions are identified based on the comparison. Collection of the one or more identified statistics for the query optimization is disabled.

Abstract: According to an embodiment of the present invention, methods, systems, and computer readable media are provided for collecting statistics for use in optimizing a database query. Collected statistics for the database are compared to corresponding predetermined states of conditions for optimizing the database query. One or more collected statistics in compliance with the corresponding predetermined states of conditions are identified based on the comparison. Collection of the one or more identified statistics for the query optimization is disabled.

Abstract: A query optimizer receives a relational database management system (RDBMS) query having a join predicate with a join between a first and a second table. The query optimizer determines a high skew value for a first variable joining the first and second tables at columns per the join predicate. A count query on one of the first and second tables is constructed and run only using the high skew value as a substitution for the first variable. A quantity of records for the join of the first and second tables is estimated using results of the count query. Different access paths (e.g., query plans) are used by the query optimizer depending on whether the estimated quantity of records exceeds a previously determined threshold or not.

Abstract: According to an embodiment of the present invention, methods, systems, and computer readable media are provided for collecting statistics for use in optimizing a database query. Collected statistics for the database are compared to corresponding predetermined states of conditions for optimizing the database query. One or more collected statistics in compliance with the corresponding predetermined states of conditions are identified based on the comparison. Collection of the one or more identified statistics for the query optimization is disabled.

Abstract: According to an embodiment of the present invention, methods, systems, and computer readable media are provided for collecting statistics for use in optimizing a database query. Collected statistics for the database are compared to corresponding predetermined states of conditions for optimizing the database query. One or more collected statistics in compliance with the corresponding predetermined states of conditions are identified based on the comparison. Collection of the one or more identified statistics for the query optimization is disabled.

Abstract: A technique for factoring uncertainty into cost-based query optimization includes: determining the degree of uncertainty involved in the cost estimates for the query, determining the degree of sensitivity the query has to that uncertainty, and determining if there is an access path that performs well across the range of possible conditions that could occur at execution time, reducing the risk of performance spikes and performance volatility. If such an access path exists, select that access path; if not, perform parametric query optimization or query re-optimization.

Abstract: A technique for factoring uncertainty into cost-based query optimization includes: determining the degree of uncertainty involved in the cost estimates for the query, determining the degree of sensitivity the query has to that uncertainty, and determining if there is an access path that performs well across the range of possible conditions that could occur at execution time, reducing the risk of performance spikes and performance volatility. If such an access path exists, select that access path; if not, perform parametric query optimization or query re-optimization.

Abstract: A technique for factoring uncertainty into cost-based query optimization includes: determining the degree of uncertainty involved in the cost estimates for the query, determining the degree of sensitivity the query has to that uncertainty, and determining if there is an access path that performs well across the range of possible conditions that could occur at execution time, reducing the risk of performance spikes and performance volatility. If such an access path exists, select that access path; if not, perform parametric query optimization or query re-optimization.

Abstract: A technique for factoring uncertainty into cost-based query optimization includes: determining the degree of uncertainty involved in the cost estimates for the query, determining the degree of sensitivity the query has to that uncertainty, and determining if there is an access path that performs well across the range of possible conditions that could occur at execution time, reducing the risk of performance spikes and performance volatility. If such an access path exists, select that access path; if not, perform parametric query optimization or query re-optimization.