DATA FILTERING

• US 20160132496A1
• Filed: 11/06/2014
• Published: 05/12/2016
• Est. Priority Date: 11/06/2014
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: Evelyna Holban, Ives Toe, Sebastien Phan, Tim Gast, Unmesh Gandhi
• Inventors: GANDHI, Unmesh, TOE, Ives, PHAN, Sebastien, HOLBAN, Evelyna, GAST, Tim
• Granted Patent: US 10,579,589 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/148 File search processing
• CPC Class Codes: G06F 16/164 File meta data generation
• CPC Class Codes: G06F 16/244 Grouping and aggregation
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/2457 with adaptation to user needs

Abstract

A method for filtering a product transaction data file involves receiving, by a computer, a query including one or more groups of attribute conditions for filtering the product transaction data file. The attribute conditions in the query are applicable to product attribute data records split across a set of vertically split attribute data files. The method further includes determining which of the product attribute data records split across the set of vertically split attribute data files satisfy all of the one or more groups of attribute conditions in the query, identifying product keys associated with the product attribute data records that satisfy all of the one or more groups of attribute conditions in the query, and using the so-identified product keys to filter product data records in the transaction data file.

Claims

1. A method for filtering a product transaction data file, the method comprising:

receiving, by a computer, a query including one or more alternate groups of attribute conditions for filtering the product transaction data file, the attribute conditions being applicable to product attribute data records present across a set of vertically split attribute data files;

determining which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query;

identifying keys associated with the product attribute data records that satisfy at least one group of attribute conditions in the query; and

using the identified keys to filter product data records in the transaction data file.

2. The method of claim 1, wherein determining which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query includes initializing group counts of the attribute conditions in the one or more groups of attribute conditions in the query.

3. The method of claim 1, wherein determining which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query includes processing the set of vertically split attribute data files one file at a time, and when a product attribute data record in a current file satisfies a number of attribute conditions in a group of attribute conditions in the query, increasing an effective group count for the key associated with the product attribute data record in the current file by a count equal to the number of attribute conditions satisfied.

4. The method of claim 3, wherein identifying keys associated with the product attribute data records that satisfy at least one group of attribute conditions in the query includes confirming that effective group count ascribed to an identified key, after processing all of the set of vertically split attribute data files, equals an initial group count of the attribute conditions in at least one group of attribute conditions in the query.

5. The method of claim 3, wherein determining which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query includes filtering the current file using the at least one group of attribute conditions.

6. The method of claim 5, wherein filtering the current file using the at least one group of attribute conditions includes determining attribute criteria form file column data, determining hierarchy criteria from file column data, building a hierarchy query and building a regular expression query to filter the current file.

7. The method of claim 1, further comprising, mapping attribute field names used in the query to equivalent attribute field names used in the set of vertically split attribute data files and/or transaction data file.

8. A system for filtering a product transaction data file, the system comprising a memory and a semiconductor-based processor, the memory and the processor forming one or more logic circuits configured to:

receive a query including one or more alternate groups of attribute conditions for filtering the product transaction data file, the attribute conditions being applicable to product attribute data records present across a set of vertically split attribute data files;

determine which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query;

identify keys associated with the product attribute data records that satisfy at least one group of attribute conditions in the query; and

use the identified keys to filter product data records in the transaction data file.

9. The system of claim 8, wherein one or more logic circuits are configured initialize group counts of the attribute conditions in the one or more groups of attribute conditions in the query.

10. The system of claim 8, wherein the logic circuits are configured to determine which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query by processing the set of vertically split attribute data files one file at a time, and when a product attribute data record in a current file satisfies a number of attribute conditions in a group of attribute conditions in the query, increase an effective group count for the key associated with the product attribute data record in the current file by a count equal to the number of attribute conditions satisfied.

11. The system of claim 10, wherein the logic circuits are configured to identify keys associated with the product attribute data records that satisfy at least one group of attribute conditions in the query by confirming that effective group count ascribed to an identified key, after processing all of the set of vertically split attribute data files, equals an initial group count of the attribute conditions in at least one group of attribute conditions in the query.

12. The system of claim 10, wherein the logic circuits are further configured to determine which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query by filtering the current file using the at least one group of attribute conditions.

13. The system of claim 12, wherein the logic circuits are configured to filter the current file using the at least one group of attribute conditions by determining attribute criteria from file column data, determining hierarchy criteria from file column data, building a hierarchy query and building a regular expression query to filter the current file.

14. The system of claim 8, wherein the logic circuits are configured to map attribute field names used in the query to equivalent attribute field names used in the set of vertically split attribute data files and/or transaction data file.

15. A non-transitory computer readable storage medium having instructions stored thereon, including instructions which, when executed by a microprocessor, cause a computer system to:

receive a query including one or more alternate groups of attribute conditions for filtering the product transaction data file, the attribute conditions being applicable to product attribute data records present across a set of vertically split attribute data files;

determine which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query;

identify keys associated with the product attribute data records that satisfy at least one group of attribute conditions in the query; and

use the identified keys to filter product data records in the transaction data file.

16. The non-transitory computer readable storage medium of claim 15, wherein instructions stored thereon include instructions, which when executed cause the computer system to initialize group counts of the attribute conditions in the one or more groups of attribute conditions in the query.

17. The non-transitory computer readable storage medium of claim 15, wherein instructions stored thereon include instructions, which when executed cause the computer system to determine which of the product attribute data records split across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query by processing the set of vertically split attribute data files one file at a time, and when a product attribute data record in a current file satisfies a number of attribute conditions in a group of attribute conditions in the query, increase an effective group count for the key associated with the product attribute data record in the current file by a count equal to the number of attribute conditions satisfied.

18. The non-transitory computer readable storage medium of claim 17, wherein the instructions stored thereon include instructions, which when executed cause the computer system to identify keys associated with the product attribute data records that satisfy at least one group of attribute conditions in the query by confirming that effective group count ascribed to an identified key, after processing all of the set of vertically split attribute data files, equals an initial group count of the attribute conditions in at least one group of attribute conditions in the query.

19. The non-transitory computer readable storage medium of claim 17, wherein the instructions stored thereon include instructions, which when executed cause the computer system to determine which of the product attribute data records present across the set of vertically split attribute data files satisfy at least one group of attribute conditions in the query by filtering the current file using the at least one group of attribute conditions.

20. The non-transitory computer readable storage medium of claim 19, wherein the instructions stored thereon include instructions, which when executed cause the computer system to filter the current file using the at least one group of attribute conditions by determining attribute criteria from file column data, determining hierarchy criteria from file column data, building a hierarchy query and building a regular expression query to filter the current file.