PROGRESSIVE QUERY COMPUTATION USING STREAMING ARCHITECTURES

• US 20150269228A1
• Filed: 12/21/2012
• Published: 09/24/2015
• Est. Priority Date: 07/12/2012
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Fisher, Danyel A., Drucker, Steven M., Chandramouli, Badrish, DeLine, Robert A., Platt, John C., Barnett, Mike, Goldstein, Jonathan D.
• Granted Patent: US 9,607,045 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24554 Unary operations; Data partitioning operations
• CPC Class Codes: G06F 16/24565 Triggers; Constraints
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2477 Temporal data queries
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

The described implementations relate to processing of electronic data. One implementation is manifest as a technique that can include obtaining a relational query that references one or more data items and associating progress intervals with the data items. The technique can also include converting the relational query into a corresponding streaming query, and providing the streaming query and the data items with the progress intervals to a stream engine that produces incremental results of the query. For example, the progress intervals can be based on row numbers of a relational database table. The progress intervals can be used to define event lifetimes of streaming events that are provided as inputs to the stream engine.

Claims

1. A method comprising:

obtaining a relational query that references one or more data items;

associating progress intervals with the data items;

converting the relational query into a corresponding streaming query; and

providing the streaming query and the data items with the progress intervals to a stream engine that produces incremental results of the query,

wherein at least the associating is performed by a computing device.

2. The method of claim 1, further comprising:

receiving script code; and

processing the script code to obtain the relational query.

3. The method of claim 1, wherein the progress intervals are based on row numbers of a table storing the data items or the progress intervals are based on an attribute of the table.

4. The method of claim 1, further comprising:

obtaining another relational query that depends on the relational query;

converting the another relational query to another streaming query; and

providing the incremental results of the relational query as inputs to the another streaming query.

5. The method of claim 1, further comprising:

obtaining the incremental results from the stream engine; and

updating a user interface as the incremental results are obtained.

6. The method of claim 5, wherein updating the user interface comprises updating a visualization of the incremental results as the incremental results are obtained.

7. The method of claim 6, wherein the visualization comprises a histogram and the updating comprises updating confidence intervals of the histogram as the incremental results are obtained.

8. One or more computer-readable storage media comprising instructions which, when executed by one or more processors, cause the one or more processors to perform acts comprising:

processing a relational query using a stream engine configured to process streaming queries; and

updating an interface with incremental results produced by the stream engine.

9. The one or more computer-readable storage media of claim 8, wherein processing the relational query using the stream engine comprises:

converting the relational query to a corresponding streaming query; and

executing the corresponding streaming query using the stream engine.

10. The one or more computer-readable storage media of claim 8, the acts further comprising:

obtaining multiple data items of a data table that is referenced by the relational query;

creating events corresponding to multiple data items; and

providing the events to the stream engine.

11. The one or more computer-readable storage media of claim 8, the acts further comprising:

setting different lifetimes for the events, wherein individual lifetimes correspond to progress intervals of the stream engine.

12. The one or more computer-readable storage media of claim 11, the acts further comprising:

setting different begin times for different sets of events, wherein the different begin times correspond to different progress intervals.

13. The one or more computer-readable storage media of claim 12, the acts further comprising:

setting a common end time for the different sets of the events, so that each of the different sets of events will contribute to a final result produced by the stream engine.

14. A system comprising:

logic configured to;

receive a first code entry,

receive a second code entry that relies on results of the first code entry, and

provide a visualization of progressive results of the first code entry and the second code entry; and

at least one processing device configured to execute the logic.

15. The system of claim 14, wherein the visualization is provided responsive to a user entering the second code entry without the user explicitly requesting the visualization.

16. The system of claim 14, wherein the logic is further configured to:

obtain a first streaming query based on the first code entry and a second streaming query based on the second code entry, and

provide the first streaming query and the second streaming query to a stream engine that produces the progressive results.

17. The system according to claim 16, wherein the logic is further configured to:

receive a user input to stop computation of the progressive results; and

stop the stream engine from producing further progressive results when the user input is received.

18. The system according to claim 16, wherein the logic is further configured to determine lifetimes of events and provide the lifetimes to the stream engine, wherein the lifetimes configure the stream engine to discard at least some internal state information after processing the events.

19. The system of claim 14, wherein the logic is further configured to identify one or more input data items that contribute to the progressive results.

20. The system according to claim 14, wherein the first code entry and the second code entry are entered during a scripting session and the logic is further configured to persist the scripting session in storage after the scripting session ends.