DATA AGGREGATION MODULE SUPPORTING DYNAMIC QUERY RESPONSIVE AGGREGATION DURING THE SERVICING OF DATABASE QUERY REQUESTS PROVIDED BY ONE OR MORE CLIENT MACHINES
First Claim
1. A system comprising:
- a parallel computing platform comprising one or more processors and one or more storage volumes, wherein each processor is associated with space within said storage volumes for physically storing data elements thereof and wherein the location of each data element in a multidimensional database (MDB) is specified in MDB space by business dimensions associated with said data element;
a data loading mechanism, associated with said parallel computing platform, for loading in the business dimensions and associated data elements from a data warehouse;
an address data mapping mechanism, associated with said data loading mechanism, for mapping the business dimensions associated with each said data element to a processor identifier, and for mapping the business dimensions associated with each said data element into a data storage address within space associated with a specific processor, identified by the processor identifier corresponding to said business dimensions; and
a data accessing mechanism in cooperation with said address data mapping mechanism, for accessing each said data element in said one or more storage volumes using said data storage address mapped thereto.
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Abstract
Improved method of and apparatus for aggregating data elements in multidimensional databases (MDDB). In the preferred embodiment, the apparatus is realized in the form of a high-performance stand-alone (i.e. external) aggregation server which can be plugged-into conventional MOLAP systems to achieve significant improvements in system performance. In accordance with the principles of the present invention, the stand-alone aggregation server contains a scalable MDDB and a high-performance aggregation engine that are integrated into the modular architecture of the aggregation server. The stand-alone aggregation server of the present invention can uniformly distribute data elements among a plurality of processors, for balanced loading and processing, and therefore is highly scalable.
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Citations
49 Claims
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1. A system comprising:
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a parallel computing platform comprising one or more processors and one or more storage volumes, wherein each processor is associated with space within said storage volumes for physically storing data elements thereof and wherein the location of each data element in a multidimensional database (MDB) is specified in MDB space by business dimensions associated with said data element; a data loading mechanism, associated with said parallel computing platform, for loading in the business dimensions and associated data elements from a data warehouse; an address data mapping mechanism, associated with said data loading mechanism, for mapping the business dimensions associated with each said data element to a processor identifier, and for mapping the business dimensions associated with each said data element into a data storage address within space associated with a specific processor, identified by the processor identifier corresponding to said business dimensions; and a data accessing mechanism in cooperation with said address data mapping mechanism, for accessing each said data element in said one or more storage volumes using said data storage address mapped thereto. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 22)
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16. A method comprising:
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(a) providing a parallel computing platform comprising one or more processors and one or more storage volumes, wherein each processor is associated with space within said storage volumes for physically storing data elements therein, and wherein the location of each data element in a multidimensional database MDB) is specified in MDB space by business dimensions associated with said data element; (b) loading in the business dimensions and associated data elements from a data warehouse; (c) mapping the business dimensions associated with each said data element to a processor identifier, and mapping the business dimensions associated with each said data element into a data storage address within space associated with a specific processor identified by the processor identifier corresponding to said business dimensions; and (d) using said data storage addresses to access said data elements from said one or more storage volumes. - View Dependent Claims (17, 18, 19, 20, 21, 23, 24, 25, 26, 27, 28, 29, 30)
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31. A stand-alone data aggregation server comprising:
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an aggregation engine that is integrated with a multidimensional data store and an interface, the aggregation engine performing data aggregation operations on data loaded from a database and storing the resultant aggregated data in a multidimensional datastore; and the interface configured to receive requests communicated from any one of a plurality of different nodes, configured to access the aggregation engine to retrieve from the multidimensional datastore aggregated data pertaining to said requests, and configured to communicate the aggregated data corresponding to said requests to said respective node that communicated said requests. - View Dependent Claims (32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49)
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Specification