Virtual Environment Spanning Desktop and Cloud

• US 20100114867A1
• Filed: 11/06/2008
• Published: 05/06/2010
• Est. Priority Date: 11/06/2008
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Olston, Christopher
• Granted Patent: US 8,838,527 B2
• Time in Patent Office: Days
• US Class Current: 707/713
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/256 in federated or virtual databases
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

A method and system are given for providing a virtual environment spanning a desktop and a cloud. In one example, the method includes receiving a query template over a data set that resides in the cloud, optimizing the query template to segment the query template into an offline phase and an online phase, executing the offline phase on the cloud to build one or more indexes, and sending the one or more indexes to the desktop.

Claims

1. A method for providing a virtual environment spanning a desktop and a cloud, the method comprising:

receiving a query template over a data set that resides in the cloud;

optimizing the query template to segment the query template into an offline phase and an online phase;

executing the offline phase on the cloud to build one or more indexes; and

sending the one or more indexes to the desktop.

2. The method of claim 1, wherein the query template is defined by a user, and wherein the optimizing the query template comprising optimizing the offline without having predefined parameters.

3. The method of claim 1, further comprising at least one of:

determining that the one or more indexes are too big to fit in the desktop; and

negotiating with a user to get properly sized indexes.

4. The method of claim 1, further comprising at least one of:

determining that the one or more indexes are properly sized to fit in the desktop;

receiving one or more bindings for parameters of the online phase; and

executing the online phase on the desktop using the one or more bindings and reading from the one or more indexes.

5. The method of claim 1, wherein the optimizing, the executing and the sending are automated steps that facilitate a query template segmentation process and that are transparent to a user.

6. The method of claim 1, further comprising supporting long-term user sessions that span periods of disconnected operation while the user waits for the outcome of offline processing steps.

7. The method of claim 1, further comprising at least one of:

providing a versioning of a query template to help a user backtrack to correct a mistake;

receiving a request to correct a mistake; and

returning to a previous version of a query template.

8. The method of claim 1, further comprising at least one of:

expressing the query template in SQL; and

performing all expensive and data-expanding operations in the offline phase.

9. The method of claim 1, wherein the optimizing the query template allows for relatively fast querying in the online phase.

10. The method of claim 1, wherein the one or more indexes are at least one of:

a conventional information retrieval index;

a relational index; and

a non-standard index.

11. A system for providing a virtual environment spanning a desktop and a cloud, wherein the system is configured for:

receiving a query template over a data set that resides in the cloud;

optimizing the query template to segment the query template into an offline phase and an online phase;

executing the offline phase on the cloud to build one or more indexes; and

sending the one or more indexes to the desktop.

12. The system of claim 11, wherein the query template is defined by a user, and wherein the optimizing the query template comprising optimizing the offline without having predefined parameters.

13. The system of claim 11, wherein the system is further configured for at least one of:

determining that the one or more indexes are too big to fit in the desktop; and

negotiating with a user to get properly sized indexes.

14. The system of claim 11, wherein the system is further configured for at least one of:

determining that the one or more indexes are properly sized to fit in the desktop;

receiving one or more bindings for parameters of the online phase; and

executing the online phase on the desktop using the one or more bindings and reading from the one or more indexes.

15. The system of claim 11, wherein the optimizing, the executing and the sending are automated steps that facilitate a query template segmentation process and that are transparent to a user.

16. The system of claim 11, wherein the system is further configured for supporting long-term user sessions that span periods of disconnected operation while the user waits for the outcome of offline processing steps.

17. The system of claim 11, wherein the system is further configured for at least one of:

providing a versioning of a query template to help a user backtrack to correct a mistake;

receiving a request to correct a mistake; and

returning to a previous version of a query template.

18. The system of claim 11, wherein the system is further configured for at least one of:

expressing the query template in SQL; and

performing all expensive and data-expanding operations in the offline phase.

19. The system of claim 11, wherein the optimizing the query template allows for relatively fast querying in the online phase.

20. The system of claim 11, wherein the one or more indexes are at least one of:

a conventional information retrieval index;

a relational index; and

a non-standard index.

21. A computer readable medium carrying one or more instructions for providing a virtual environment spanning a desktop and a cloud, wherein the one or more instructions, when executed by one or more processors, cause the one or more processors to perform the steps of:

receiving a query template over a data set that resides in the cloud;

optimizing the query template to segment the query template into an offline phase and an online phase;

executing the offline phase on the cloud to build one or more indexes; and

sending the one or more indexes to the desktop.