Abstract: A database request can be processed at least partly based on one or more differences between multiple database systems and/or environments. The differences can, for example, include differences between one or more database capabilities respectively provided by the multiple database systems, differences between the representation of data in the multiple database systems, and differences in the interfaces for accessing the multiple database systems.

Abstract: Computing capacity of a computing environment can be managed by controlling it associated processing capacity based on a target (or desired) capacity. In addition, fine-grained control over the processing capacity can be exercised. For example, a computing system can change the processing capacity (e.g., processing rate) of at least one processor operating based on a target capacity. The computing system may also be operable to change the processing capacity based on a measured processing capacity (e.g., a measured average of various processing rates of a processor taken over a period of time when a processor may have been operating at different processing rates over that period). By way of example, the processing rate of a processor can be switched between 1/8 and 2/8 of a maximum processing rate to achieve virtually any effective processing rates between them.

Abstract: Excess capacity available to a database system in a capacity controlled environment can be effectively managed. In particular, excess capacity that is not made available for normal operations of a database system can be used to manage errors, especially situations that may hinder expected performance of the database system. In addition, excess capacity can be used to optimize or further optimize database queries, especially those that meet a criterion (e.g., not fully optimize, not optimized as expected).

Abstract: A system includes a multi-system database management system having a plurality of database systems. An index selection subsystem combines sets of query information from respective ones of the plurality of database systems into a workload. The index selection subsystem then generates candidate indexes from the workload, and selects recommended indexes from the candidate indexes based on one or more criteria.

Abstract: A method, system, and computer program are disclosed. Statistics are read from a data dictionary on a target system. The statistics include statistics for a table in a database in the target system. The statistics are exported to a test system separate from the target system. A command is received to use the statistics in emulation. In response the statistics are copied to a cache in the test system and the target system is emulated on the test system using the statistics in the test system's cache.

Abstract: A computer-implemented method, apparatus and article of manufacture for optimizing a database query. Resource usage of one or more resources of the computer system are monitored. A condition code representative of the monitored resource usage is stored. A cost model is modified using the stored condition code. A query execution plan is generated for the database query using the modified cost model. The query execution plan is then executed in order to retrieve data from a database stored on the computer system, wherein the retrieved data is presented to a user for subsequent use and analysis.

Abstract: A query is executed on a multi-database system. The multi-database system includes a first system database and a second system database. The query is partially executed on a first system database by generating a spool. It is determined that it is more efficient to store the spool on the second system database than to store the spool on the first system database, and in response the spool is stored on the second system database. The query execution is continued by accessing the spool on the second system database, completing execution of the query to produce a result, and storing the result.

Abstract: A system and method for managing one or more database systems, wherein the database systems perform database queries to retrieve data stored by the database systems. One or more regulators are used for managing the database systems, wherein the regulators monitor workload priority influenced data temperature in order to allocate resources for the systems. The data temperature is a measure of physical accesses to logical data, and the workload priority is used to further define data temperature, in order to optimize data storage placement and data access decisions.

Abstract: An optimization technique is provided that optimizes data access by mapping each table, or row and/or column in a table, to a particular query, depending on whether the data in said table, row or column is ‘hot’ or ‘cold’ data. In one aspect, the invention features a method for optimizing the access time of an SQL query to a database including data. The method includes receiving, for each query type, a data frequency access measure and associating each query type with a processing rule set, according to the received data frequency access measure.

Abstract: A database system receives information relating to a job requested by a requestor, where the job includes a plurality of requests. Execution of the requests of the job is managed using the received information, where managing the requests includes adjusting one or more of priority settings and resource estimates for the requests.

Abstract: A computer-implemented method, apparatus and article of manufacture for performing an automatic error recovery in a database system. Automatic error recovery is performed for a query execution plan, following errors, problems or failures that occur during execution, by automatically or manually deactivating and/or activating components, features or code paths, and then re-submitting the query execution plan for execution in the computer system.

Abstract: Requests to be executed in the database system are received, where a plurality of the requests are provided in a queue for later execution. Priority indicators are calculated for assignment to corresponding ones of the plurality of requests in the queue, where the priority indicators are calculated based on delay times and predefined priority levels of the requests. The requests in the queue are executed in order according to the calculated priority indicators.

Abstract: A database request can be processed at least partly based on one or more differences between multiple database systems and/or environments. The differences can, for example, include differences between one or more database capabilities respectively provided by the multiple database systems, differences between the representation of data in the multiple database systems, and differences in the interfaces for accessing the multiple database systems.

Abstract: A database system includes an optimizer to generate resource estimates regarding execution of a request in the database system, and a regulator to monitor execution of a request and to adjust a priority level of the request based on the monitored execution and based on the resource estimates provided by the optimizer. The regulator is executable to further feed back statistics regarding execution of the request to the optimizer to improve accuracy of resource estimates provided by the optimizer.

Abstract: A computer-implemented method, apparatus and article of manufacture for optimizing a database query. A query execution plan is generated for the database query, which may be stored in an in-line query capture database. Execution of the query execution plan may be monitored in order to generate performance information, which also may be stored in the in-line query capture database. The data stored in in-line query capture database may be used during the initial generation of query execution plans, as well as for the re-optimization of a query execution plan, during the execution of the query execution plan.

Abstract: Data or one or more operations can be provided, based on one or more characteristics associated with the data and/or operations, to a designated computing group or pool of computing resources designated for handling the data and/or operations with the particular data characteristic(s). The designated computing group can, for example, be one of multiple computing groups in the same system or device. As such, all of the computing groups can still function together in the same system or device, for example, in parallel. However, each one of the multiple computing groups can, for example, be defined or predefined to include one or more computing resources that are more suitable for storing and/or processing data with one or more data characteristics or handle operations with one or more determined characteristics.

Abstract: A filter receives a request to perform an operation in a database system, and the filter receives a resource estimate relating to the request from an optimizer. The filter determines whether the resource estimate exceeds an available resource of the database system, and if so, the filter rejects the request prior to execution of the request.

Abstract: A test system receives environment information of a target database system, where the environment information includes information relating to hardware and software components of the target database system, and one or more of: definitions of workloads in the target database system, and settings of a scheduler in the target database system. The test system emulates an environment of the target database system using the received environment information, and database software is executed in the emulated environment in the test system.

Abstract: Excess capacity available to a database system in a capacity controlled environment can be effectively managed for maintenance and/or tuning activities. In this context, excess capacity can be used as needed and/or on a temporary basis. Furthermore, maintenance and/or tuning activities can be performed without requiring the use of the configured or allotted capacity. As a result, these operations can be performed without adversely affecting other operations which may be deemed more critical by the users of databases. System maintenance and tuning (or fine tuning) of a database environment can, for example, include operations associated with “Physical Tuning,” and “Index Tuning”. Some exemplary operations include collecting Statistics, analyzing a database workload, sampling, analyzing an execution plan, creating indexes.

Abstract: A method, computer program and database system are disclosed for guiding the development of workload group definition (WD) classifications for a database system having resources. WD classification information is provided where a workload group is a set of system requests having characteristics defined by a WD and a WD classification identifies one or more WDs with similar performance requirements. If WD classification is not acceptable, one or more of the following functions is performed until WD classification is acceptable: (a) splitting one or more WDs; and (b) merging two or more WDs.