# US 8,788,453 B2 · Data aggregation module supporting dynamic query responsive aggregation during the servicing of database query requests provided by one or more client machines > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,788,453 B2 - Document ID: US8788453B2 - Status: Granted - Kind: B2 - Application number: 13/275,242 - Filed: 2011-10-17 - Published: 2012-04-12 - Granted: 2014-07-22 - Earliest claimed: 1999-08-04 - Assignees: Yanicklo Technology Limited Liability Company - Applicants: Reuven Bakalash; Guy Shaked; Joseph Caspi - Inventors: Reuven Bakalash; Guy Shaked; Joseph Caspi - Web page: https://patentgrep.com/patent/US8788453B2 ## CPC - G06F 16/24556: {Aggregation; Duplicate elimination} - G06F 16/283: {Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP} - Y10S 707/99932: Access augmentation or optimizing - Y10S 707/99933: Query processing, i.e. searching - Y10S 707/99943: Generating database or data structure, e.g. via user interface - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - Y10S: TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS ## 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. ## Claims ### Claim 1 A method comprising: by a computer system comprising computer hardware: receiving a first multidimensional cube of data, wherein the first multidimensional cube of data is sparse; initiating a first aggregation process; conducting the first aggregation process: receiving a query after the first aggregation process has been initiated and while the first aggregation process is being conducted; determining a sequence for storing the first multidimensional cube of data in a multidimensional database; and at least partly in response to the query, performing a query directed, on-the-fly roll-up process while the first aggregation process is still being conducted, extracting, based at least in part on the determined sequence, a first slice of data for storage in the multidimensional database from the first multidimensional cube of data, wherein the first slice of data is a second multidimensional cube of data that is a subset of the first multidimensional cube of data. ### Claim 2 (depends on 1) The method of claim 1, wherein a plurality of non-null data points are stored in a first record in the multidimensional database indexed in an ascending order along an aggregation direction. ### Claim 3 (depends on 2) The method of claim 2, further comprising extracting, based at least in part on the determined sequence, a second slice of data for storage from the first multidimensional cube of data. ### Claim 4 (depends on 3) The method of claim 3, wherein non-null data points within the second slice are stored in a second record in the multidimensional database. ### Claim 5 (depends on 4) The method of claim 4, wherein a length of the first record and second record are different and based at least in part on the number of non-null data points that were stored. ### Claim 6 A computing system comprising: a processor comprising hardware; and a computer readable medium storing machine-executable instructions including one or more modules configured for execution by the processor in order to cause the computing system to: receive a first multidimensional cube of data, wherein the first multidimensional cube of data is sparse; initiate a first on-the-fly aggregation process; conduct the first on-the-fly aggregation process: determine a sequence for storing the first multidimensional cube of data in a multidimensional database; receive a query after the first on-the-fly aggregation process has been initiated and while the first a on-the-fly aggregation process is being conducted; determine a sequence for storing the first multidimensional cube of data in a multidimensional database; at least partly in response to the received query, perform a query directed roll-up process while the first on-the-fly aggregation process is still being conducted; and extract, based at least in part on the determined sequence, a first slice of data from the first multidimensional cube of data, wherein the first slice of data is a second multidimensional cube of data that is a subset of the first multidimensional cube of data; and store the extracted first slice of data in the multidimensional database. ### Claim 7 (depends on 6) The system of claim 6, wherein a plurality of non-null data points are stored in a first record in the multidimensional database indexed in an ascending order along an aggregation direction. ### Claim 8 (depends on 7) The system of claim 7, wherein the instructions are further configured to cause the computing system to extract, based at least in part on the determined sequence, a second slice of data for storage from the first multidimensional cube of data. ### Claim 9 (depends on 8) The system of claim 8, wherein non-null data points within the second slice are stored in a second record in the multidimensional database. ### Claim 10 (depends on 9) The system of claim 9, wherein a length of the first record and second record are different and based at least in part on the number of non-null data points that were stored. ### Claim 11 A non-transitory computer-readable medium encoded with instructions thereon, wherein the instructions are readable by a computing system in order to cause the computing system to perform operations comprising: receiving a first multidimensional cube of data, wherein the first multidimensional cube of data is sparse; initiating a first aggregation process; conducting the first on-the-fly aggregation process: determining a sequence for storing the first multidimensional cube of data in a multidimensional database; receiving a query after the first on-the-fly aggregation process has been initiated and while the first aggregation process is being conducted; at least partly in response to the received query, performing a query directed roll-up process while the first on-the-fly aggregation process is still being conducted; extracting, based at least in part on the determined sequence, a first slice of data from the first multidimensional cube of data, wherein the first slice of data is a second multidimensional cube of data that is a subset of the first multidimensional cube of data; and storing the extracted first slice of data in the multidimensional database. ### Claim 12 (depends on 11) The non-transitory computer-readable medium of claim 11, wherein a plurality of non-null data points are stored in a first record in the multidimensional database indexed in an ascending order along an aggregation direction. ### Claim 13 (depends on 12) The non-transitory computer-readable medium of claim 12, wherein the instructions are further encoded to cause the computing system to perform operations comprising extracting, based at least in part on the determined sequence, a second slice of data for storage from the first multidimensional cube of data. ### Claim 14 (depends on 13) The non-transitory computer-readable medium of claim 13, wherein non-null data points within the second slice are stored in a second record in the multidimensional database. ### Claim 15 (depends on 14) The non-transitory computer-readable medium of claim 14, wherein a length of the first record and second record are different and based at least in part on the number of non-null data points that were stored.