AUTOMATIC GENERATION OF SUB-QUERIES

• US 20170161323A1
• Filed: 06/30/2014
• Published: 06/08/2017
• Est. Priority Date: 06/30/2014
• Status: Active Grant

• Current Assignee: Micro Focus LLC (Open Text Corporation)
• Original Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Inventors: Simitsis, Alkiviadis, Wilkinson, William K.
• Granted Patent: US 10,747,762 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/24535 of sub-queries or views
• CPC Class Codes: G06F 16/248 Presentation of query results

Abstract

Example implementations relate to automatic generation of sub-queries. For example, a computing device may include a processor. The processor may receive a query defining a particular set of data stored in at least one database. The processor may access metadata associated with the particular set of data and may select a data attribute associated with the particular set of data based on the metadata. The processor may automatically generate sub-queries of the query using the data attribute selected based on the metadata. The processor may process the sub-queries and provide a query result of the query that is a combination of sub-query results of the sub-queries.

Claims

1. A computing device comprising:

a processor to;

receive a query defining a particular set of data stored in at least one database;

access metadata associated with the particular set of data;

select a data attribute associated with the particular set of data based on the metadata;

automatically generate sub-queries of the query using the data attribute selected based on the metadata;

process the sub-queries; and

provide a query result of the query, the query result being a combination of sub-query results of the sub-queries.

2. The computing device of claim 1, wherein selecting the data attribute based on the metadata includes selecting the data attribute based on at least one of processing time of each sub-query, distribution of data between the sub-queries, a number of results for each sub-query, and user-specified criteria associated with the data attribute, wherein the sub-queries produce a disjoint subset of an original result of the query.

3. The computing device of claim 1, wherein the sub-queries correspond to disjoint ranges of data associated with the data attribute.

4. The computing device of claim 1, wherein the sub-queries correspond to disjoint ranges of key values relating to data associated with the data attribute.

5. The computing device of claim 1, wherein generating the sub-queries is based on a histogram of data associated with the data attribute.

6. A method comprising:

receiving, by a computing device, a query defining a particular set of data stored in at least one database;

accessing, by the computing device, metadata associated with the particular set of data;

identifying, by the computing device, a data attribute associated with the particular set of data based on the metadata;

automatically creating, by the computing device, sub-queries of the query using the data attribute identified based on the metadata;

analyzing, by the computing device, the sub-queries; and

calculating, by the computing device, a query result of the query, the query result including sub-query results of the sub-queries.

7. The method of claim 6, further comprising:

identifying the data attribute based on at least one of processing time of each sub-query, distribution of data between the sub-queries, a number of results for each sub-query, and user-specified criteria associated with the data attribute, wherein the sub-queries produce a disjoint subset of an original result of the query.

8. The method of claim 6, wherein the sub-queries correspond to disjoint ranges of data associated with the data attribute.

9. The method of claim 6, wherein the sub-queries correspond to disjoint ranges of key values relating to data associated with the data attribute.

10. The method of claim 6, wherein generating the sub-queries is based on a histogram of data associated with the data attribute.

11. A non-transitory machine-readable storage medium storing instructions that, if executed by at least one processor of a computing device, cause the computing device to:

receive a query defining a particular set of data stored in at least one database;

access metadata associated with the particular set of data;

determine a data attribute associated with the particular set of data based on the metadata;

automatically generate sub-queries of the query using the data attribute determined based on the metadata;

perform the sub-queries; and

determine a query result of the query, the query result being a combination of sub-query results of the sub-queries.

12. The non-transitory machine-readable storage medium of claim 11, wherein the instructions, if executed by the at least one processor, further cause the computing device to determine the data attribute based on at least one of processing time of each sub-query, distribution of data between the sub-queries, a number of results for each sub-query, and user-specified criteria associated with the data attribute, wherein the sub-queries produce a disjoint subset of an original result of the query.

13. The non-transitory machine-readable storage medium of claim 11, wherein the sub-queries correspond to disjoint ranges of data associated with the data attribute.

14. The non-transitory machine-readable storage medium of claim 11, wherein the sub-queries correspond to disjoint ranges of key values relating to data associated with the data attribute.

15. The non-transitory machine-readable storage medium of claim 11, wherein generating the sub-queries is based on a histogram of data associated with the data attribute.