AGGREGATING DIMENSIONAL DATA USING DENSE CONTAINERS

• US 20150088885A1
• Filed: 09/20/2013
• Published: 03/26/2015
• Est. Priority Date: 09/20/2013
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: ROTH, MARTIN, SOYLEMEZ, EKREM S.C., HOPEMAN, ALBERT A. IV
• Granted Patent: US 9,740,718 B2
• Time in Patent Office: Days
• US Class Current: 707/737
• CPC Class Codes: G06F 16/221 Column-oriented storage; Management thereof

Abstract

Methods, computer systems, and stored instructions are described herein for densely grouping dimensional data and/or aggregating data using a data structure, such as one that is constructed based on dimensional data. When smaller tables are joined with a larger table, a server may analyze the smaller tables first to determine actual value combinations that occur in the smaller tables, and these actual value combinations are used to more efficiently process the larger table. A dense data structure may be generated by processing dimensional data before processing data from fact table. The dense data structure may be generated by compressing ranges of values that are possible in dimensions into a range of values that actually occurs in the dimensions. The compressed range of values may be represented by dense set identifiers rather than the actual compressed range of values.

Claims

1. A method comprising:

storing a query that aggregates data from at least one database object;

for a set of one or more columns on which the aggregated data is grouped, before evaluating the query to aggregate the data, creating;

different storage containers for each different set of one or more values that occurs in the set of one or more columns without creating storage containers for one or more sets of one or more values that do not occur in the set of one or more columns;

evaluating the query to aggregate the data from the at least one database object at least in part by using keys from the at least one database object to locate corresponding storage containers of the different storage containers;

wherein the method is performed by one or more computing devices.

2. The method of claim 1, wherein the query, when evaluated, aggregates the data by computing a sum for the at least one database object, and wherein evaluating the query comprises storing rolling sums in the different storage containers.

3. The method of claim 1, wherein the query, when evaluated, aggregates the data by computing a maximum for the at least one database object, and wherein evaluating the query comprises storing rolling maximums in the different storage containers.

4. The method of claim 1, wherein the query, when evaluated, aggregates the data by computing a minimum for the at least one database object, and wherein evaluating the query comprises storing rolling minimums in the different storage containers.

5. The method of claim 1, wherein evaluating the query comprises aggregating the data in the different storage containers after storing different sequences of corresponding values from the at least one database object in the different storage containers.

6. The method of claim 1, wherein the query is a first query;

the method further comprising;

retaining aggregated data in the different storage containers after evaluation of the first query;

determining that a second query, if executed, could use at least part of the aggregated data in the different storage containers; and

using at least part of the aggregated data in the different storage containers to evaluate the second query.

7. The method of claim 1, wherein the keys from the at least one database object directly identify entries in the data structure, wherein the different storage containers are the different entries in the data structure.

8. The method of claim 1, further comprising using a stored mapping to map the keys from the at least one database object to keys of at least one other database object, wherein the different storage containers are located using the keys of the at least one other database object.

9. The method of claim 1, wherein the different storage containers are mapped to a Cartesian product of set identifiers for two or more dimensions that are referenced by the query, and wherein the at least one database object comprises a fact table.

10. The method of claim 1, wherein the data structure is an array of set identifiers, and wherein different entries in the array correspond to different keys of at least one other database object that is referenced by the query.

11. The method of claim 1, further comprising:

creating, for the set of one or more columns on which the aggregated data is grouped, a data structure that maps combinations of column values to rows of the at least one database object;

filtering, from the data structure, particular combinations of column values that cannot satisfy the query; and

analyzing only those rows of the at least one database object that could be associated with the combinations that remain after filtering.

12. One or more non-transitory computer-readable storage media storing instructions which, when executed, cause:

storing a query that aggregates data from at least one database object;

for a set of one or more columns on which the aggregated data is grouped, before evaluating the query to aggregate the data, creating;

different storage containers for each different set of one or more values that occurs in the set of one or more columns without creating storage containers for one or more sets of one or more values that do not occur in the set of one or more columns;

evaluating the query to aggregate the data from the at least one database object at least in part by using keys from the at least one database object to locate corresponding storage containers of the different storage containers.

13. The one or more non-transitory computer-readable storage media of claim 12, wherein the query, when evaluated, aggregates the data by computing a sum for the at least one database object, and wherein evaluating the query comprises storing rolling sums in the different storage containers.

14. The one or more non-transitory computer-readable storage media of claim 12, wherein the query, when evaluated, aggregates the data by computing a maximum for the at least one database object, and wherein evaluating the query comprises storing rolling maximums in the different storage containers.

15. The one or more non-transitory computer-readable storage media of claim 12, wherein the query, when evaluated, aggregates the data by computing a minimum for the at least one database object, and wherein evaluating the query comprises storing rolling minimums in the different storage containers.

16. The one or more non-transitory computer-readable storage media of claim 12, wherein the instructions, when executed, cause evaluating the query at least in part by causing aggregating the data in the different storage containers after storing different sequences of corresponding values from the at least one database object in the different storage containers.

17. The one or more non-transitory computer-readable storage media of claim 12, wherein the query is a first query;

wherein the instructions, when executed, further cause;

retaining aggregated data in the different storage containers after evaluation of the first query;

determining that a second query, if executed, could use at least part of the aggregated data in the different storage containers; and

using at least part of the aggregated data in the different storage containers to evaluate the second query.

18. The one or more non-transitory computer-readable storage media of claim 12, wherein the keys from the at least one database object directly identify entries in the data structure, wherein the different storage containers are the different entries in the data structure.

19. The one or more non-transitory computer-readable storage media of claim 12, wherein the instructions, when executed, further cause using a stored mapping to map the keys from the at least one database object to keys of at least one other database object, wherein the different storage containers are located using the keys of the at least one other database object.

20. The one or more non-transitory computer-readable storage media of claim 12, wherein the different storage containers are mapped to a Cartesian product of set identifiers for two or more dimensions that are referenced by the query, and wherein the at least one database object comprises a fact table.

21. The one or more non-transitory computer-readable storage media of claim 12, wherein the data structure is an array of set identifiers, and wherein different entries in the array correspond to different keys of at least one other database object that is referenced by the query.

22. The one or more non-transitory computer-readable storage media of claim 12, wherein the instructions, when executed, further cause:

creating, for the set of one or more columns on which the aggregated data is grouped, a data structure that maps combinations of column values to rows of the at least one database object;

filtering, from the data structure, particular combinations of column values that cannot satisfy the query; and

analyzing only those rows of the at least one database object that could be associated with the combinations that remain after filtering.