Abstract: Embodiments of the present invention provide a hardware accelerator that assists a host database system in processing its queries. The hardware accelerator comprises special purpose processing elements that are capable of receiving database query/operation tasks in the form of machine code database instructions, execute them in hardware without software, and return the query/operation result back to the host system. For example, table and column descriptors are embedded in the machine code database instructions. For ease of installation, the hardware accelerators employ a standard interconnect, such as a PCIe or HT interconnect. The processing elements implement a novel dataflow design and Inter Macro-Op Communication (IMC) data structures to execute the machine code database instructions. The hardware accelerator may also comprise a relatively large memory to enhance the hardware execution of the query/operation tasks requested.

Abstract: Methods, data structures, and systems for generating customer segmentation models are provided. Basket transactions are analyzed and classified into a first segment type, a second segment type, a third segment type, or a fourth segment type. A number of the basket transaction within a number of the segment types are separately analyzed to determine sub classifications or sub segments within a particular segment type. Each basket transaction is augmented with a segment type that identifies the segment type classification, and a number of the basket transactions include a segment identifier that identifies the sub segment within a segment type that a basket transaction is associated with. The augmented basket transactions represent a customer segmentation model. In one embodiment, daily transactions are monitored by a script and used to dynamically adjust the customer segmentation model.

Abstract: A database system includes a plurality of access modules and corresponding persistent storage devices each having a pool of storage elements that can be allocated to store permanent files and temporary files. Each access module is associated with a non-persistent file management context and each storage device contains a persistent file management context. The persistent file management context indicates allocation of permanent files, while the non-persistent file management context indicates the allocation of both permanent and temporary files.

Abstract: Embodiments of the present invention provide for batch and incremental loading of data into a database. In the present invention, the loader infrastructure utilizes machine code database instructions and hardware acceleration to parallelize the load operations with the I/O operations. A large, hardware accelerator memory is used as staging cache for the load process. The load process also comprises an index profiling phase that enables balanced partitioning of the created indexes to allow for pipelined load. The online incremental loading process may also be performed while serving queries.

Abstract: Apparatus, systems, and methods may operate to receive a designation of multiple rows to supply data to a single user defined function, which is made available in a structured query language SELECT statement. Further activities may include retrieving the data from at least one storage medium, packing each of the multiple rows having a common key into a single row, and transforming the data from a first state into a second state by applying the single function to the data using a single access module processor. Other apparatus, systems, and methods are disclosed.

Abstract: Techniques for using metadata as comments to assist with search problem determination and analysis are provided. Before an action is taken on a search, contextual information is gathered as metadata about the action and actor requesting the action. The metadata is embedded in the search as comments and the comments are subsequently logged when the action is performed on the search. The comments combine with other comments previously recorded to permit subsequent analysis on searches.

Abstract: Techniques for discovering database connectivity leaks are presented. Each connection made by an application to a database is monitored. When the application is shut down, if information regarding a particular connection remains in memory, then that connection is reported as a potential database connectivity leak.

Abstract: A data-warehousing system allows various areas of an enterprise to view data at varying levels of data freshness. The system acquires data that represents an event in the life of a business enterprise, such as a transaction between the enterprise and one of its customers, and loads this data into a database table. The system then makes the data available for retrieval from the table and stores information indicating when the data was made available for retrieval. In some embodiments, the system also acquires data that is related to and more current than the data representing the event and stores the more current data in the database. The system then stores information indicating when the more current data was stored in the database. Such a data warehouse allows decision-makers in the business to see some information (e.g., customer transaction or account data) up-to-the-moment and other information as it stood at some specific point-in-time, such as at the end of the previous month.

Abstract: A SQL query that includes an IN-List is optimized by (1) performing an evaluation to determine whether access to a table can be performed as a join operation, (2) converting the IN-List to an IN-LIST relation, and (3) joining the IN-List relation with the table to access the data in the table.

Abstract: A method, computer program, and database system are disclosed for querying tables stored on multiple processing modules. The method includes specifying module group characteristics. A plurality of modules corresponding to the module group characteristics are then identified. The identified modules are sampled for statistics concerning at least one table specified in a query. An execution plan for the query is optimized based at least in part on the sampled statistics.

Abstract: Methods, computer programs, and database systems for performing a database query to join a column A and a column B on an inequality condition are disclosed. A database includes value-count indexes for columns A and B. Minimum and a maximum values for A and B are determined, using the value-count indexes for A and B, respectively. The method includes defining three or more sets of values in A and B, relative to the minimum and maximum values for B and A, respectively. The method includes generating one or more Cartesian products between values in A and B. The database query is performed on a set of values in A and a set of values in B to generate a partial query result. The method includes merging one or more Cartesian products and the partial query result.

Abstract: The invention relates to a method of determining the performance of an optimizer program arranged to generate a plan. The method generally comprises the steps of executing the optimizer utilising at least one test case to derive a pre-variation plan; executing the pre-variation plan to generate a first output; varying a strategy of the optimizer program; executing the varied optimizer program utilising the at least one test case to derive a post-variation plan; and executing the post-variation plan to generate a second output. The outputs are then grouped according to at least one element of the plans to assess the performance of the optimizer.

Abstract: Statistics for temporary tables are used in optimizing the execution of a database request. A first temporary table is created using data from a data source as the result of performing an operation while executing the request. A subset of the demographics of the data source is saved in a session level memory as the demographics of the first temporary table. The saved demographics are used in optimizing the execution of the portion of the request involving the first temporary table.

Abstract: Techniques are presented for generic data extraction. Metadata defines a data extraction element with reference to an identifier, a data source, and one or more rules. The metadata may be processed to populate the data extraction element when a reference is made within a data template to the identifier. The identifier may be used to import data to a template or to export data to a different template or service.

Abstract: Processing of a request is optimized. The request has one or more predicates. A list of the one or more predicates in the request is created and predicates for which an actual cost has not been stored or for which a cost cannot be estimated are pruned from the list. An access path for the each of the predicates is selected. The request is processed using the selected access paths producing one or more actual predicate costs. The one or more actual predicate costs are stored.

Abstract: An aggregate User Defined Function (UDF) processing used for multi-regression is provided. The aggregate UDF initializes storage space for multiple nodes of a database environment. Data is then extracted from a relational database and populated according to groupings on each of the nodes. Multiple rows or records are then processed to create a merge and multi-regression processed.

Abstract: Techniques are presented for managing fraud information. Metadata defines user profiles, security levels, fraud cases, and presentation information. One or more queries or reports are processed against disparate data store tables and the results are aggregated into a repository. The repository is also defined by the metadata. Furthermore, operations associated with sharing, viewing, and accessing the results from the repository is defined and controlled by the metadata. In an embodiment, portions of the metadata may be viewed and navigated in a hierarchical and graphical formatted presentation.

Abstract: A computer network is used to improve the profitability of one or more business entities. The network receives business-related data from at least two business entities and stores at least some of the data from each of the business entities in a common database. Then, in accordance with the terms of an agreement among the business entities, the network allows at least one of the business entities to receive information gathered from the common database.

Abstract: Various embodiments may include taking an initial dump of a database table and tracking changes to the database table, with regard to but outside of transactions, since a most recent full or partial dump has been taken. A partial dump, in such embodiments, may be taken since the most recent full or partial dump and used to create a data structure which may be used to update only those database table rows modified since a last full or partial dump. As a result, the dumps of a database table will include a single full dump and may include one or more partial dumps. These full and partial dumps may then be instantiated to create or update an instance of the database table. In some embodiments, dumps may be taken directly to a mirrored instance of a database table.

Abstract: A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.