Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: Techniques for processing queries are provided. In one approach, an execution plan for a query includes multiple sub-plans, one or more of which are selected at runtime while one or more other sub-plans are not executed during execution of the execution plan. In another approach, data about misestimate is generated and stored persistently for subsequent queries. In another approach, statistics for a database object are generated automatically and efficiently while the database object is created or data items are added thereto. In another approach, a hybrid histogram is created that includes a feature of frequency histograms and a feature of height-balanced histograms. In another approach, computer jobs are executed in such a way to avoid deadlock. In another approach, changes to a database object trigger a hard parse of a query even though an execution plan already exists for the query.

Abstract: Techniques for sharing cursors are provided. When a new query is issued, a database server determines whether the new query is semantically equivalent to a previous query. If so, then database server computes statistics associated with the new query. Based on the statistics, the database server determines whether compiling the new query would produce an execution plan that satisfies certain criteria. If so, then the cursor is used to execute the new query. In another approach, one cursor sharing technique (CST) is used to determine which cursor to use to execute a first set of semantically-equivalent queries. Statistics are gathered during execution of the first set of queries. The database server determines, based on the statistics, when to switch from using the first CST to a different CST. The different CST is used to determine which cursor to use to execute a second set of queries that are semantically-equivalent to the first set.

Abstract: Techniques for sharing cursors are provided. When a new query is issued, a database server determines whether the new query is semantically equivalent to a previous query. If so, then database server computes statistics associated with the new query. Based on the statistics, the database server determines whether compiling the new query would produce an execution plan that satisfies certain criteria. If so, then the cursor is used to execute the new query. In another approach, one cursor sharing technique (CST) is used to determine which cursor to use to execute a first set of semantically-equivalent queries. Statistics are gathered during execution of the first set of queries. The database server determines, based on the statistics, when to switch from using the first CST to a different CST. The different CST is used to determine which cursor to use to execute a second set of queries that are semantically-equivalent to the first set.

Abstract: Techniques for sharing cursors are provided. When a new query is issued, a database server determines whether the new query is semantically equivalent to a previous query. If so, then database server computes statistics associated with the new query. Based on the statistics, the database server determines whether compiling the new query would produce an execution plan that satisfies certain criteria. If so, then the cursor is used to execute the new query. In another approach, one cursor sharing technique (CST) is used to determine which cursor to use to execute a first set of semantically-equivalent queries. Statistics are gathered during execution of the first set of queries. The database server determines, based on the statistics, when to switch from using the first CST to a different CST. The different CST is used to determine which cursor to use to execute a second set of queries that are semantically-equivalent to the first set.

Abstract: Techniques for sharing cursors are provided. When a new query is issued, a database server determines whether the new query is semantically equivalent to a previous query. If so, then database server computes statistics associated with the new query. Based on the statistics, the database server determines whether compiling the new query would produce an execution plan that satisfies certain criteria. If so, then the cursor is used to execute the new query. In another approach, one cursor sharing technique (CST) is used to determine which cursor to use to execute a first set of semantically-equivalent queries. Statistics are gathered during execution of the first set of queries. The database server determines, based on the statistics, when to switch from using the first CST to a different CST. The different CST is used to determine which cursor to use to execute a second set of queries that are semantically-equivalent to the first set.