Abstract: A system for dynamically parallelizing the loading operation for loading a data file onto a database. The dynamic parallelization of the loading operation involves scanning the data file in segments, such that scanning of an individual segment terminates when the scanned information is enough to enable loading of the segment across a plurality of exclusive-access memory blocks. Following the scanning of the first data file segment, the parallelized loading of each scanned segment occurs in a lock-step-mode with the scanning operation. As such, the loading of each scanned data segment is performed in parallel across multiple exclusive-access memory location, as determined by the prior scanning results, and furthermore in parallel with the scanning of a subsequent segment of the data file.

Abstract: A system for generating a parallel calculation plan to evaluate a rule-set or a rule-based expression list by spilling the list of rule-based expressions into multiple task units and reconfiguring all independent task units at the same calculation levels into several parallelized task groups such that task units within each task group may be scheduled for parallel execution across a cluster of processing nodes. The parallelization may be dynamically determined based on generated tasks but may further be subject to an additional layer of parallelization based on range-based splitting of each task into multiple parallel executable subtasks. The final parallelized calculation plan may include a set of sequentially ordered task groups based on logical dependencies and problem partitioning with information regarding parallelized execution of each task group.

Abstract: A system for generating a parallel calculation plan to evaluate a rule-set or a rule-based expression list by spilling the list of rule-based expressions into multiple task units and reconfiguring all independent task units at the same calculation levels into several parallelized task groups such that task units within each task group may be scheduled for parallel execution across a cluster of processing nodes. The parallelization may be dynamically determined based on generated tasks but may further be subject to an additional layer of parallelization based on range-based splitting of each task into multiple parallel executable subtasks. The final parallelized calculation plan may include a set of sequentially ordered task groups based on logical dependencies and problem partitioning with information regarding parallelized execution of each task group.

Abstract: A system for dynamically parallelizing the loading operation for loading a data file onto a database. The dynamic parallelization of the loading operation involves scanning the data file in segments, such that scanning of an individual segment terminates when the scanned information is enough to enable loading of the segment across a plurality of exclusive-access memory blocks. Following the scanning of the first data file segment, the parallelized loading of each scanned segment occurs in a lock-step-mode with the scanning operation. As such, the loading of each scanned data segment is performed in parallel across multiple exclusive-access memory location, as determined by the prior scanning results, and furthermore in parallel with the scanning of a subsequent segment of the data file.

Abstract: A system and method for allowing a user to segment and partition a database based upon attributes associated with the data in the database. Also, a system and method for generating a report for a user which allows the user to make decisions, without requiring the user to understand or interpret data itself. A database computer includes a database containing the data. The data includes a collection of information about an enterprise of the user. A server computer is coupled to the database computer and executes a database management program. A client computer is coupled to the server and executes an application program. The application program allows a user to define predetermined data types, to define relationships between the data types, to define parameters for the report, to define a method of analysis for the report, and to create the report. The report summarizes the data in terms of the data types, the data relationships, and the method of analysis.