Abstract: A system, method, and computer-readable medium for optimizing complex SQL statements using a region divided preferential SQL rewrite operation. The region divided preferential SQL rewrite operation makes it possible for a user to inference a machine SQL statement rewrite operation to optimize the SQL statement with more or less focus on different regions of the SQL. This operation combines the strength of using heuristic knowledge and understanding of data to rewrite the region of the SQL statement where the problem originates with the precision and efficiency of a machine SQL statement rewrite operation.

Abstract: A system, method, and computer-readable medium for optimizing complex SQL statements using a region divided preferential SQL rewrite operation. The region divided preferential SQL rewrite operation makes it possible for a user to inference a machine SQL statement rewrite operation to optimize the SQL statement with more or less focus on different regions of the SQL. This operation combines the strength of using heuristic knowledge and understanding of data to rewrite the region of the SQL statement where the problem originates with the precision and efficiency of a machine SQL statement rewrite operation.

Abstract: A system, method, and computer-readable medium are disclosed for improving the readability and understanding of a SQL query plan by presenting SQL query plan in a join plan representation. In various embodiments, the join plan representation includes one or more of a table join path portion, a statistics portion, an objects axis region and an operator region. The order of the table join path can be easily read in such a representation. Also, statistic figures like cost, IO, CPU and cardinality are all consistently and orderly presented, making it easy for users to understand and compare.

Abstract: A system, method, and computer-readable medium are disclosed for providing usage and symptom oriented SQL statement optimization. More specifically, in certain embodiments, a SQL Optimizer is provided with a SQL Statement Usage and Symptom Oriented Tuning Tool. More specifically, the SQL Statement Usage and Symptom Oriented Tuning Tool assists users in composing a correct test run method and selecting a correct resource saving item. Additionally, in certain embodiments, the SQL Statement Usage and Symptom Oriented Tuning Tool includes a tuning tool user interface which allows users to provide the tool with specific information about the performance symptoms and usage patterns of their SQL statement. By providing such a user interface, users do not need to have knowledge of the actual settings used to tune the SQL statement. The SQL Statement Usage and Symptom Oriented Tuning Tool automatically composes settings to provide a SQL statement test run method on behalf of the user.

Abstract: Aspects of the present invention provide systems and methods that can help generate potential execution plans for a query statement that have one or more bind variable, whether the one or more bind variables were originally in the query statement or replaced one or more literals in the query. Embodiments of the present invention also include systems and methods for testing performance of one or more of the potential execution plans before they emerge in the production environment.

Abstract: Systems and methods are disclosed that utilize a genetic algorithm to search for an index configuration for a collection of data such as, e.g., a database. Genetic algorithms can include stochastic search heuristics that mimic processes of natural evolution including inheritance, mutation, crossover, and selection. A population of chromosomes representing candidate index configurations can evolve to increase or optimize the fitness of the population and to identify the best (e.g., most fit) index configuration. Fitness of a chromosome may be measured based at least in part on the cost of computer resources used for executing Structured Query Language (SQL) statements in the indexed database.

Abstract: Systems and methods are disclosed that utilize a genetic algorithm to search for an index configuration for a collection of data such as, e.g., a database. Genetic algorithms can include stochastic search heuristics that mimic processes of natural evolution including inheritance, mutation, crossover, and selection. A population of chromosomes representing candidate index configurations can evolve to increase or optimize the fitness of the population and to identify the best (e.g., most fit) index configuration. Fitness of a chromosome may be measured based at least in part on the cost of computer resources used for executing Structured Query Language (SQL) statements in the indexed database.

Abstract: Systems and methods for extracting or analyzing time-series behavior are described. Some embodiments of computer-implemented methods include generating fuzzy rules from time series data. Certain embodiments also include resolving conflicts between fuzzy rules according to how the data is clustered. Some embodiments further include extracting a model of the time-series behavior via defuzzification and making that model accessible. Advantageously, to resolve conflicts between fuzzy rules, some embodiments define Gaussian functions for each conflicting data point, sum the Gaussian functions according to how the conflicting data points are clustered, and resolve the conflict based on the results of summing the Gaussian functions. Some embodiments use both crisp and non-trivially fuzzy regions and/or both crisp and non-trivially fuzzy membership functions.

Abstract: Systems and methods for extracting or analyzing time-series behavior are described. Some embodiments of computer-implemented methods include generating fuzzy rules from time series data. Certain embodiments also include resolving conflicts between fuzzy rules according to how the data is clustered. Some embodiments further include extracting a model of the time-series behavior via defuzzification and making that model accessible. Advantageously, to resolve conflicts between fuzzy rules, some embodiments define Gaussian functions for each conflicting data point, sum the Gaussian functions according to how the conflicting data points are clustered, and resolve the conflict based on the results of summing the Gaussian functions. Some embodiments use both crisp and non-trivially fuzzy regions and/or both crisp and non-trivially fuzzy membership functions.

Abstract: Systems and methods for extracting or analyzing time-series behavior are described. Some embodiments of computer-implemented methods include generating fuzzy rules from time series data. Certain embodiments also include resolving conflicts between fuzzy rules according to how the data is clustered. Some embodiments further include extracting a model of the time-series behavior via defuzzification and making that model accessible. Advantageously, to resolve conflicts between fuzzy rules, some embodiments define Gaussian functions for each conflicting data point, sum the Gaussian functions according to how the conflicting data points are clustered, and resolve the conflict based on the results of summing the Gaussian functions. Some embodiments use both crisp and non-trivially fuzzy regions and/or both crisp and non-trivially fuzzy membership functions.