Abstract: A common interface to manage heterogeneous databases and develop enterprise class applications is provided. In particular, it is shown that a client-based system and method can: (a) provide a uniform interface for the DBA or the application developer to use across all the database deployments, (b) provide flexibility in the number and kinds of scenarios it can be used, and finally (c) reduce the total cost of ownership for the enterprise.

Abstract: A system for automating data partitioning in a parallel database includes plural nodes connected in parallel. Each node includes a database server and two databases connected thereto. Each database server includes a query optimizer. Moreover, a partitioning advisor communicates with the database server and the query optimizer. The query optimizer and the partitioning advisor include a program for recommending and evaluating data table partitions that are useful for processing a workload of query statements. The data table partitions are recommended and evaluated without requiring the data tables to be physically repartitioned.

Abstract: A method and system for automatically and adaptively determining query execution plans for parametric queries. A first classifier trained by an initial set of training points is generated. A query workload and/or database statistics are dynamically updated. A new set of training points is collected off-line. Using the new set of training points, the first classifier is modified into a second classifier. A database query is received at a runtime subsequent to the off-line phase. The query includes predicates having parameter markers bound to actual values. The predicates are associated with selectivities. A mapping of the selectivities into a plan determines the query execution plan. The determined query execution plan is included in an augmented set of training points, where the augmented set includes the initial set and the new set.

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.

Abstract: The invention finds matches in ordered sequences, e.g. program function call stacks from anomalous software program executions for discovering related or identical software flaws and possible known solutions. Call stacks are matched after removing recursive and uninformative subpatterns, e.g. names of common error handling routines, to see if they were generated due to the same possibly known problem. Sequences statistically unlikely to be matches are pruned from the search. Matches found earlier in the sequences may be weighted differently, e.g. to be more important in call stacks, than other matches. Sequences are indexed so that those relevant to a query are identified automatically without detailed exhaustive search. Maximum matches are found by optimizing a cost function based on weighted sequence similarity.

Abstract: A common interface to manage heterogeneous databases and develop enterprise class applications is provided. In particular, it is shown that a client-based system and method can: (a) provide a uniform interface for the DBA or the application developer to use across all the database deployments, (b) provide flexibility in the number and kinds of scenarios it can be used, and finally (c) reduce the total cost of ownership for the enterprise.

Abstract: A method is disclosed for executing a predetermined query plan, the method comprising: executing a portion of the query plan; providing a reordered query plan; comparing ranking metrics for the query plans; and executing the query plan having the lower ranking metric.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: Provided is a method for modeling the cost of XML as well as relational operators. As with traditional relational cost estimation, a set of system catalog statistics that summarizes the XML data is exploited; however, the novel use of a set of simple path statistics is also proposed. A new statistical learning technique called transform regression is utilized instead of detailed analytical models to predict the overall cost of an operator. Additionally, a query optimizer in a database is enabled to be self-tuning, automatically adapting to changes over time in the query workload and in the system environment.

Abstract: A system for automating data partitioning in a parallel database includes plural nodes connected in parallel. Each node includes a database server and two databases connected thereto. Each database server includes a query optimizer. Moreover, a partitioning advisor communicates with the database server and the query optimizer. The query optimizer and the partitioning advisor include a program for recommending and evaluating data table partitions that are useful for processing a workload of query statements. The data table partitions are recommended and evaluated without requiring the data tables to be physically repartitioned.

Abstract: A method is disclosed for executing a predetermined query plan, the method comprising: executing a portion of the query plan; providing a reordered query plan; comparing ranking metrics for the query plans; and executing the query plan having the lower ranking metric.

Abstract: A method for predictable query execution through early materialization is provided. The method deals with the problem of cardinality misestimation in query execution plans, by pre-executing sub-plans on a query execution plan that have questionable estimates and collecting statistics on the output of these sub-plans. If needed, the overall query execution plan is changed in light of these statistics, before optimizing and executing the remainder of the query.

Abstract: Disclosed is a method for directing a data processing system, the data processing system and an article of manufacture. The data processing system has memory for storing a database. The method directs the data processing system to configuring the database based on a database workload having a performance metric. The method includes selecting a plurality of database characteristics based upon the database workload, each of the database characteristics having an associated estimated performance metric for the database workload, selecting a set of database characteristics from the plurality of database characteristics for which the associated estimated performance metric is lower than the database workload performance metric, and configuring the database using the selected set of database characteristics.

Abstract: A system for automating data partitioning in a parallel database includes plural nodes connected in parallel. Each node includes a database server and two databases connected thereto. Each database server includes a query optimizer. Moreover, a partitioning advisor communicates with the database server and the query optimizer. The query optimizer and the partitioning advisor include a program for recommending and evaluating data table partitions that are useful for processing a workload of query statements. The data table partitions are recommended and evaluated without requiring the data tables to be physically repartitioned.

Abstract: A method and system for automatically and adaptively determining query execution plans for parametric queries. A first classifier trained by an initial set of training points is generated. A query workload and/or database statistics are dynamically updated. A new set of training points is collected off-line. Using the new set of training points, the first classifier is modified into a second classifier. A database query is received at a runtime subsequent to the off-line phase. The query includes predicates having parameter markers bound to actual values. The predicates are associated with selectivities. A mapping of the selectivities into a plan determines the query execution plan. The determined query execution plan is included in an augmented set of training points, where the augmented set includes the initial set and the new set.

Abstract: A method for automatically and adaptively determining query execution plans for parametric queries. A first classifier trained by an initial set of training points is generated using a set of random decision trees (RDTs). A query workload and/or database statistics are dynamically updated. A new set of training points collected off-line is used to modify the first classifier into a second classifier. A database query is received at a runtime subsequent to the off line phase. The query includes predicates having parameter markers bound to actual values. The predicates are associated with selectivities. The query execution plan is determined by identifying an optimal average of posterior probabilities obtained across a set of RDTs and mapping the selectivities to a plan. The determined query execution plan is included in an augmented set of training points that includes the initial set and the new set.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.