Abstract: Techniques are disclosed for generating statistical views in a database system. In one embodiment, a request is received to execute a database workload. One or more constraints pertaining to executing the database workload is retrieved. The database workload is evaluated to generate multiple statistical view candidates. The statistical view candidates are refined based on the one or more constraints. One or more statistical views are then generated based on the refined statistical view candidates.

Abstract: Tuning a production database system through the use of a remote mimic. In response to receipt of a query tuning request against a database system, information about that system is obtained and a mimic of the system is set up in a remote system environment. The mimic aims to imitate the database system in all relevant ways with respect to the tuning request. A tuning analysis is then performed on this mimic system such that there is substantially no impact to operations of the original database system. Tuning results are then applied to the original database system. The entire process takes place with little or no human intervention.

Abstract: Tuning a production database system through the use of a remote mimic. In response to receipt of a query tuning request against a database system, information about that system is obtained and a mimic of the system is set up in a remote system environment. The mimic aims to imitate the database system in all relevant ways with respect to the tuning request. A tuning analysis is then performed on this mimic system such that there is substantially no impact to operations of the original database system. Tuning results are then applied to the original database system. The entire process takes place with little or no human intervention.

Abstract: Techniques are disclosed for generating statistical views in a database system. In one embodiment, a request is received to execute a database workload. One or more constraints pertaining to executing the database workload is retrieved. The database workload is evaluated to generate multiple statistical view candidates. The statistical view candidates are refined based on the one or more constraints. One or more statistical views are then generated based on the refined statistical view candidates.

Abstract: Tuning a production database system through the use of a remote mimic. In response to receipt of a query tuning request against a database system, information about that system is obtained and a mimic of the system is set up in a remote system environment. The mimic aims to imitate the database system in all relevant ways with respect to the tuning request. A tuning analysis is then performed on this mimic system such that there is substantially no impact to operations of the original database system. Tuning results are then applied to the original database system. The entire process takes place with little or no human intervention.

Abstract: Tuning a production database system through the use of a remote mimic. In response to receipt of a query tuning request against a database system, information about that system is obtained and a mimic of the system is set up in a remote system environment. The mimic aims to imitate the database system in all relevant ways with respect to the tuning request. A tuning analysis is then performed on this mimic system such that there is substantially no impact to operations of the original database system. Tuning results are then applied to the original database system. The entire process takes place with little or no human intervention.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: A query processing system has a query processor and a data manager. The query processor calls the data manager to carry out data access for a query including a filtering operation. The data manager accesses the data in a set of data and before returning the data, initiates a callback to the query processor to determine if the located data meets the filtering criteria. Where the data does not satisfy the filtering criteria, the data manager seeks additional data in the set of data, without having to return the first located data to the query processor.

Abstract: A workload specification is obtained for the database. Based on the workload specification, candidate ones of the tables are identified and ranked. Compression impact is evaluated for the candidate ones of the tables. A design for the database is developed, specifying at least one of: (i) which of the tables should be compressed, and (ii) which of the tables should not be compressed.

Abstract: Techniques are disclosed for generating statistical views in a database system. In one embodiment, a request is received to execute a database workload. One or more constraints pertaining to executing the database workload is retrieved. The database workload is evaluated to generate multiple statistical view candidates. The statistical view candidates are refined based on the one or more constraints. One or more statistical views are then generated based on the refined statistical view candidates.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: The retrieval of distinct tuples in a relational database management system. In response to a request from a consumer process for distinct tuples in a relational database table matching a defined criteria, a distinct operator component sequentially requests tuples from a source component. The source component access the database table and returns a tuple in the sequence to the distinct operator component. The distinct operator component passes each tuple in the sequence to an auxiliary logger. The auxiliary component receives a tuples from the distinct component and determines if it is distinct from other previously received tuples in the sequence to verify its uniqueness to the distinct operator. Tuples that are verified as unique by the auxiliary logger are returned to the consumer process by the distinct operator upon verification.

Abstract: A system and method of evaluating queries in distributed databases with MQTs comprises deriving MQTs; replicating the derived MQTs from a local server to at least one remote server; and distributing data and replicated derived MQTs to a plurality of other remote servers, wherein the distributing increases overall query execution efficiency. The databases may comprise heterogeneous databases. The query execution efficiency comprises observed response time at a frontend database and associated costs comprising computational central processing unit costs, input/output costs, and network communication costs. All of the associated costs comprise statistically estimated costs. The method further comprises running a MQT advisor at a frontend database, and considering the costs of at least one MQT placed at the frontend database. The method further comprises running a MQT advisor at a non-frontend database.

Abstract: A workload specification is obtained for the database. Based on the workload specification, candidate ones of the tables are identified and ranked. Compression impact is evaluated for the candidate ones of the tables. A design for the database is developed, specifying at least one of: (i) which of the tables should be compressed, and (ii) which of the tables should not be compressed.

Abstract: A workload specification is obtained for the database. Based on the workload specification, candidate ones of the tables are identified and ranked. Compression impact is evaluated for the candidate ones of the tables. A design for the database is developed, specifying at least one of: (i) which of the tables should be compressed, and (ii) which of the tables should not be compressed.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: The retrieval of distinct tuples in a relational database management system. In response to a request from a consumer process for distinct tuples in a relational database table matching a defined criteria, a distinct operator component sequentially requests tuples from a source component. The source component access the database table and returns a tuple in the sequence to the distinct operator component. The distinct operator component passes each tuple in the sequence to an auxiliary logger. The auxiliary component receives a tuples from the distinct component and determines if it is distinct from other previously received tuples in the sequence to verify its uniqueness to the distinct operator. Tuples that are verified as unique by the auxiliary logger are returned to the consumer process by the distinct operator upon verification.

Abstract: A query processing system has a query processor and a data manager. The query processor calls the data manager to carry out data access for a query including a filtering operation. The data manager accesses the data in a set of data and before returning the data, initiates a callback to the query processor to determine if the located data meets the filtering criteria. Where the data does not satisfy the filtering criteria, the data manager seeks additional data in the set of data, without having to return the first located data to the query processor.

Abstract: The present invention provides a method, system and program for optimizing compression of a workload processed by a database management system. In an embodiment of the present invention a method of optimizing the compression of database workloads is provided. Initially, an estimate of a cost of execution for each query according to a defined metric such as execution time or memory consumption is determined. A sub-set of queries is then selected from the workload in order of the most costly to least costly relative to the defined metric for compression according to either a predetermined compression threshold percentage or a threshold percentage derived from an allotted workload execution time. Compression is then performed on the selected sub-set of queries (i.e. those that will benefit the most from the compression) to achieve a net beneficial trade-off between the cost of workload compression and the cost of workload execution.