Online syntheses programming technique

• US 6,434,557 B1
• Filed: 12/30/1999
• Issued: 08/13/2002
• Est. Priority Date: 12/30/1999
• Status: Expired due to Fees

• Current Assignee: Decode Genetics Ehf.
• Original Assignee: Decode Genetics Ehf.
• Inventors: Egilsson, Agust Sverrir, Gudbjartsson, Hakon
• Primary Examiner(s): Mizrahl, Diane D.
• Assistant Examiner(s): Veillard, Jacques
• Application Number:
  US09/475,436
• Time in Patent Office: 957 Days
• Field of Search: 707/3, 707/5, 707/104, 707/102, 707/103
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2264 Multidimensional index structures
• CPC Class Codes: G06F 2216/03 Data mining
• CPC Class Codes: Y10S 707/956 Hierarchical
• CPC Class Codes: Y10S 707/958 Data cubes
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

The current mechanism discloses methods for transforming a set of heterogeneous relations into multidimensional data cubes. A syntheses process is disclosed that dynamically and with minimal user input eliminates ambiguities in a populated hypercube. Including, ambiguities reflecting dependencies between dimensions in the hypercube as well as reflecting the need for supporting points in the cube with realistic observations. The hypercubes also support complex dimension structures, complex operations and hierarchies that are not necessary regular or of aggregation type. The methods are generic and applicable to any data warehouse design. The methods enable relational OLAP for a wider variety of data and structures than possible using current relational implementation schemas.

Claims

1. A method for synthesizing relations in multidimensional processing, comprising:

(a) determining relations for processing, each relation having a respective domain,

(b) associating the domains of said relations with dimensions in a hypercube representation,

(c) determining join criteria and join operators for said dimensions,

(d) determining calculated relations between at least two of said dimensions in said hypercube, and

(e) using said relations, said join criteria, said join operators and said calculated relations to compose related values from said relations into points in said hypercube.

2. The method of claim 1, comprising generating said relations and said hypercube from an initial set of relations and an initial hypercube by repeatedly applying operators that modify and/or add relations and/or modify the dimension structure in the hypercube.

3. The method of claim 1, comprising following a join/composition path such that said resulting points are determined to be contradiction free.

4. The method of claim 1, wherein said calculated relations are determined from said dimensions in said hypercube.

5. The method of claim 1, comprising associating with said dimensions in said hypercube, hierarchical structures for the grouping of said points.

6. The method of claim 5, comprising translating said hypercube representation, said hierarchical structures and said points into fact and dimension tables.

7. The method of claim 1, wherein said relations contain, inter alia, heterogeneous information including disease/health data about individuals, genotype readings and/or readings about environmental factors.

8. The method of claim 7, comprising, inter alia, relations about a domain with entries about individuals and hierarchical structures about said domain with information about genealogical records.

9. A system for synthesizing relations in multidimensional processing, the system comprising:

(a) means for determining relations for processing,

(b) means for associating the domains of said relations with dimensions in a hypercube representation,

(c) means for determining join criteria and join operators for said dimensions,

(d) means for determining calculated relations between at least two of said dimensions in said hypercube, and

(e) means for using said relations, said join criteria, said join operators and said calculated relations to compose related values from said relations into points in said hypercube.

10. The system of claim 9, further including means for generating said relations and said hypercube from an initial set of relations and an initial hypercube by repeatedly applying operators that modify and/or add relations and/or modify the dimension structure in the hypercube.

11. The system of claim 9, further including means for following a join/composition path such that said resulting points are determined to be contradiction free.

12. The system of claim 9, further including means for determining said calculated relations from said dimensions in said hypercube.

13. The system of claim 9, further including means for associating with said dimensions in said hypercube, hierarchical structures for the grouping of said points.

14. The system of claim 13, further including means for translating said hypercube representation, said hierarchical structures and said points into fact and dimension tables.

15. The system of claim 9, further including means for having said relations contain, inter alia, heterogeneous information including disease/health data about individuals, genotype readings and/or readings about environmental factors.

16. The system of claim 15, further including means for processing, inter alia, relations about a domain with entries about individuals and hierarchical structures about said domain with information about genealogical records.