System and method for automated problem isolation in systems with measurements structured as a multidimensional database

• US 6,330,564 B1
• Filed: 02/10/1999
• Issued: 12/11/2001
• Est. Priority Date: 02/10/1999
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Yue, Po Chang, Hellerstein, Joseph L.
• Primary Examiner(s): Breene, John
• Assistant Examiner(s): BLACK, LINH
• Application Number:
  US09/247,239
• Time in Patent Office: 1,035 Days
• Field of Search: 707/5, 707/100, 707/101, 707/103, 707/104
• US Class Current: 1/1
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

A system and method are described for automating navigations in systems with measurement data that are structured as a multidimensional database (MDDB). The navigation includes an Automated Navigation Engine that uses external representations of a dimension selection function and a cube selection function to guide MDDB navigations. The method consists of the steps: (1) select the MDDB dimension that has the largest dimension selection score; (2) if this score is too small, terminate the method; (3) otherwise, select the cube with the largest cube selection score. These steps are performed repeatedly until (2) applies. Navigations can be performed for data mining, problem isolation, trending analysis, etc.

Claims

1. A system for obtaining information by automatically navigating measurement data that is structured into cubes comprising a plurality of dimensions, the system being associated with a multidimensional database component for specifying said cubes, said system comprising:

(a) a dimension selection component that quantifies information provided by navigating to a dimension;

(b) a cube selection component that quantifies the extent to which a cube provides information; and

(c) an automated navigation engine that uses the multidimensional database component, the dimension selection component and the cube selection component to automate navigations by iteratively selecting the best cube within successively selected cube dimensions to arrive at the cube having the desired information.

2. The system of claim 1 wherein said system is adapted to run at least one problem isolation application and wherein said navigations isolate problems.

3. The system of claim 1 wherein said navigations comprise mining of data stored in said database.

4. The system of claim 1 wherein said navigations comprise trending analysis.

5. A method for a system to automatically navigate measurement data for information gathering, wherein said measurement data is structured into a plurality of cubes comprising a plurality of dimensions, said method comprising the steps of:

(a) characterizing the information potential of said data for each of said plurality of dimensions;

(b) selecting the dimension having the greatest information potential based upon said characterizing;

(c) comparing the dimension information potential of said selected dimension to a preset threshold;

(d) terminating the method if the dimension information potential for said selected dimension is less than said threshold;

(e) determining the cube information potential for at least one of said plurality of cubes within said selected dimension when said dimension information potential is not less than said threshold;

(f) selecting the cube within the selected dimension with the largest cube information potential, and

(g) iteratively selecting the best cube within successively selected cube dimensions by repeating steps (b) through (f) to arrive at the cube having the desired information.

6. The method of claim 5 wherein said characterizing comprises quantifying the information potential.

7. The method of claim 6 wherein said system has at least one associated dimension selection component for operating with a dimension selection function, and wherein said quantifying comprises computing a dimension selection score by said dimension selection function for each of said plurality of dimensions.

8. The method of claim 6 wherein said system has at least one associated cube selection component for operating with a cube selection function, and wherein said selecting said cube comprises computing a cube selection score by said cube selection function.

9. The method of claim 7 wherein said system further comprises at least one associated cube selection component for operating with a cube selection function, and wherein said selecting said cube comprises computing a cube selection score by said cube selection function.

10. The method of claim 9 wherein at least one of said cube selection function and said dimension selection function are externally specified.

11. The method of claim 8 wherein said cube selection function is externally specified.

12. The method of claim 7 wherein said dimension selection function is externally specified.

13. A method for providing automated problem isolation for a computer system adapted for detecting a problem, for gathering relevant problem data, and for providing said data in a cube, comprising the steps of:

(a) obtaining an initial cube of relevant data from said computer system;

(b) selecting a cube dimension that best isolates the problem;

(c) comparing said selected cube dimension to a threshold;

(d) finding the best cube in said selected cube dimension when said selected cube dimension is not less than said threshold;

(e) repeating steps (b) through (d) until said selected cube dimension is less than said threshold.

14. The method of claim 13 further comprising the step of obtaining a dimension score function to control the granularity of said problem isolation.

15. The method of claim 13 wherein said finding the best cube in said selected cube dimension comprises the steps of:

(a) selecting a present dimension score;

(b) identifying a successive dimension in said cube;

(c) computing a successive dimension score for said successive dimension;

(d) comparing said successive dimension score to said present dimension score;

(e) replacing said present dimension score with said successive score when said successive score better isolates the problem;

(f) determining whether all dimensions have been analyzed; and

(g) repeating steps (b) through (f) until all dimensions have been analyzed.

16. The method of claim 15 further comprising applying at least one of a cube score function and a dimension score function for computing scores.

17. The method of claim 16 wherein at least one of said cube score function and said dimension score function is externally specified.

18. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for a system associated with said machine to navigate measurement data for information gathering, wherein said measurement data is structured into a plurality of cubes comprising a plurality of dimensions, said method steps comprising:

(a) characterizing the information potential of said data for each of said plurality of dimensions;

(b) selecting the dimension having the greatest information potential based upon said characterizing;

(c) comparing the dimension information potential of said selected dimension to a preset threshold;

(d) terminating the method if the dimension information potential for said selected dimension is less than said threshold;

(e) determining the cube information potential for at least one of said plurality of cubes within said selected dimension when said dimension information potential is not less than said threshold;

(f) selecting the cube within the selected dimension with the largest cube information potential, and

(g) iteratively selectinq the best cube within successively selected cube dimensions by repeating steps (b) through (f) to arrive at the cube having the desired information.

19. The device of claim 18 wherein said characterizing comprises quantifying the information potential.

20. The device of claim 19 wherein said system has at least one associated dimension selection component for operating with a dimension selection function, and wherein said quantifying comprises computing a dimension selection score by said dimension selection function for each of said plurality of dimensions.

21. The device of claim 19 wherein said system has at least one associated cube selection component for operating with a cube selection function, and wherein said selecting said cube comprises computing a cube selection score by said cube selection function.

22. The device of claim 20 wherein said system further comprises at least one associated cube selection component for operating with a cube selection function, and wherein said selecting said cube comprises computing a cube selection score by said cube selection function.

23. The device of claim 22 wherein at least one of said cube selection function and said dimension selection function are externally specified.

24. The device of claim 21 wherein said cube selection function is externally specified.

25. The device of claim 20 wherein said dimension selection function is externally specified.