International Business Machines Corporation

Haider Abbas Rizvi

Sam Sampson Lightstone

Matthew Albert Huras

Calisto Paul Zuzarte

Qi Cheng

Theodore Jeremy Wasserman

David Benson Skillicorn

Thomas Patrick Martin

According to one embodiment of the present invention, a system partitions data for parallel processing and comprises one or more computer systems with at least one processor. The system partitions data of a data object into a plurality of data partitions within a data structure based on a plurality of keys. The data structure includes a plurality of dimensions and each key is associated with a corresponding different dimension of the data structure. Portions of the data structure representing different data partitions are assigned to the computer systems for parallel processing, and the assigned data structure portions are processed in parallel to perform an operation. Embodiments of the present invention further include a method and computer program product for partitioning data for parallel processing in substantially the same manner described above.

Partitioning data for parallel processing

Methods for reducing the overhead of validating constraints in a database are provided. The method includes providing a target table, and providing a source table. The source table includes data to be loaded into the target table. The method further includes loading data into the target table from the source table including eliminating any logic to validate a constraint defined on the target table based on one or more pre-determined conditions.

Method for reducing overhead of validating constraints in a database

A workload characterization system characterizes an exemplary business intelligence workload for use in sizing a hardware configuration required by a new database system running a similar business intelligence workload. The workload characterization system uses performance-oriented measurements to characterize an exemplary workload in terms of resource usage and performance metrics. The workload characterization system applies unsupervised data mining techniques to group individual business intelligence queries into general classes of queries based on system resource usage, providing insight into the resource demands of queries typical of a business intelligence workload. The general classes of queries are used to define an anticipated workload for a planned database system and to help identify the hardware required for the planned database system.

System, service, and method for characterizing a business intelligence workload for sizing a new database system hardware configuration

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Richmond Hill, Canada

Haider Abbas Rizvi