TEMPORALLY-AWARE EVALUATIVE SCORE

• US 20090083216A1
• Filed: 09/24/2007
• Published: 03/26/2009
• Est. Priority Date: 09/24/2007
• Status: Active Grant

• Current Assignee: NICE Systems Technologies Inc. (Nice Ltd)
• Original Assignee: Merced Systems Incorporated (Nice Ltd)
• Inventors: Dampier, Todd O.
• Granted Patent: US 8,051,075 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/2477 Temporal data queries
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

A method includes processing a performance query to a dimensional data model by processing dimension coordinates that exist within the dimensional data model, wherein the dimension coordinates have a first particular grain (“finer grain”) that is finer than a second particular grain (“coarser grain”), the method to determine an evaluative score for a particular finer grain value based on performance facts for dimension coordinates associated with the particular finer grain value. Performance parameters are determined relative to a particular coarser grain value, against which to measure the performance facts associated with the finer grain value, including processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates. The evaluative score is determined for the particular finer grain value based on performance facts of dimension coordinates having the particular finer grain value, in view of the determined performance parameters.

Claims

1. A method of processing a performance query to a dimensional data model by processing dimension coordinates that exist within the dimensional data model, wherein the dimension coordinates have a first particular grain (“

finer grain”

) that is finer than a second particular grain (“

coarser grain”

), the method to determine an evaluative score for a particular finer grain value based on performance facts for dimension coordinates associated with the particular finer grain value, the method comprising;

determining performance parameters, relative to a particular coarser grain value, against which to measure the performance facts associated with the finer grain value, including processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates;

determining the evaluative score for the particular finer grain value based on performance facts of dimension coordinates having the particular finer grain value, in view of the determined performance parameters.

2. The method of claim 1, wherein:

processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates includes, for the particular coarser grain value,

determining a set of finer grain values for dimension coordinates having the particular coarser grain value;

determining a set of dimension coordinates having finer grain values in the determined set of finer grain values, including dimension coordinates having finer grain values in the determined set of finer grain values but not having the particular coarser grain value.

3. The method of claim 1, wherein:

for the dimension coordinates having the particular finer grain value, on which the determination of evaluative score for the particular finer grain value is based, at least some of those dimension coordinates do not have the particular coarser grain value.

4. The method of claim 3, wherein:

determining a set of dimension coordinates having finer grain values in the determined set of finer grain values, including dimension coordinates having finer grain values in the determined set of finer grain values but not having the particular coarser grain value includes;

processing a query constraint that is expressed in terms of the particular coarser grain value to determine an initial set of dimension coordinates; and

rewriting and reapplying the query constraint in terms of finer grain values of the determined initial set of dimension coordinates, to determine the set of dimension coordinates.

5. The method of claim 2, wherein:

determining the performance parameters for the particular coarser grain value includes processing performance facts for the determined set of dimension coordinates.

6. The method of claim 1, wherein:

the particular finer grain value is a first particular finer grain value of a plurality of particular finer grain values; and

the method further comprises

processing a temporal mode to determine a time extent descriptor; and

determining the plurality of finer grain values based at least in part on processing the determined time extent descriptor.

7. A computer program product for processing a performance query to a dimensional data model by processing dimension coordinates that exist within the dimensional data model, wherein the dimension coordinates have a first particular grain (“

finer grain”

) that is finer than a second particular grain (“

coarser grain”

), the processing to determine an evaluative score for a particular finer grain value based on performance facts for dimension coordinates associated with the particular finer grain value, the computer program product comprising at least one computer-readable medium having computer program instructions stored therein which are operable to cause at least one computing device to;

determine performance parameters, relative to a particular coarser grain value, against which to measure the performance facts associated with the finer grain value, including processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates; and

determine the evaluative score for the particular finer grain value based on performance facts of dimension coordinates having the particular finer grain value, in view of the determined performance parameters.

8. The computer program product of claim 7, wherein:

processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates includes, for the particular coarser grain value, includes

determining a set of finer grain values for dimension coordinates having the particular coarser grain value;

determining a set of dimension coordinates having finer grain values in the determined set of finer grain values, including dimension coordinates having finer grain values in the determined set of finer grain values but not having the particular coarser grain value.

9. The computer program product of claim 7, wherein:

for the dimension coordinates, having the particular finer grain value, on which the determination of performance score for the particular finer grain value is based, at least some of those dimension coordinates do not have the particular coarser grain value.

10. The computer program product of claim 9, wherein:

determining a set of dimension coordinates having finer grain values in the determined set of finer grain values, including dimension coordinates having finer grain values in the determined set of finer grain values but not having the particular coarser grain value includes;

processing a query constraint that is expressed in terms of the particular coarser grain value to determine an initial set of dimension coordinates; and

rewriting and reapplying the query constraint in terms of finer grain values of the determined initial set of dimension coordinates, to determine the set of dimension coordinates.

11. The computer program product of claim 8, wherein:

determining the performance parameters for the particular coarser grain value includes processing performance facts for the determined set of dimension coordinates.

12. The computer program product of claim 7, wherein:

the particular finer grain value is a first particular finer grain value of a plurality of particular finer grain values; and

the computer program instructions are further operable to cause at least one computing device to;

process a temporal mode to determine a time extent descriptor; and

determine the plurality of finer grain values based at least in part on processing the determined time extent descriptor.

13. A computer system configured to process a performance query to a dimensional data model by processing dimension coordinates that exist within the dimensional data model, wherein the dimension coordinates have a first particular grain (“

finer grain”

) that is finer than a second particular grain (“

coarser grain”

), the processing to determine an evaluative score for a particular finer grain value based on performance facts for dimension coordinates associated with the particular finer grain value, the computer system configured to;

determine performance parameters, relative to a particular coarser grain value, against which to measure the performance facts associated with the finer grain value, including processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates; and

determine the evaluative score for the particular finer grain value based on performance facts of dimension coordinates having the particular finer grain value, in view of the determined performance parameters.

14. The computer system of claim 13, wherein:

processing the temporal relationships of finer grain values to coarser grain values for the dimension coordinates includes, for the particular coarser grain value, includes

determining a set of finer grain values for dimension coordinates having the particular coarser grain value;

determining a set of dimension coordinates having finer grain values in the determined set of finer grain values, including dimension coordinates having finer grain values in the determined set of finer grain values but not having the particular coarser grain value.

15. The computer system of claim 13, wherein:

for the dimension coordinates, having the particular finer grain value, on which the determination of performance score for the particular finer grain value is based, at least some of those dimension coordinates do not have the particular coarser grain value.

16. The computer system of claim 13, wherein:

determining a set of dimension coordinates having finer grain values in the determined set of finer grain values, including dimension coordinates having finer grain values in the determined set of finer grain values but not having the particular coarser grain value includes;

processing a query constraint that is expressed in terms of the particular coarser grain value to determine an initial set of dimension coordinates; and

rewriting and reapplying the query constraint in terms of finer grain values of the determined initial set of dimension coordinates, to determine the set of dimension coordinates.

17. The computer program product of claim 14, wherein:

determining the performance parameters for the particular coarser grain value includes processing performance facts for the determined set of dimension coordinates.

18. The computer system of claim 13, wherein:

the particular finer grain value is a first particular finer grain value of a plurality of particular finer grain values; and

the computer system is further configured to;

process a temporal mode to determine a time extent descriptor; and

determine the plurality of finer grain values based at least in part on processing the determined time extent descriptor.