Hybrid execution of continuous and scheduled queries

• US 9,715,529 B2
• Filed: 01/21/2016
• Issued: 07/25/2017
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Shukla, Vikram, Park, Hoyong, Srinivasan, Anand
• Primary Examiner(s): Uddin, Md. I
• Application Number:
  US15/003,646
• Publication Number:
  US 20160140180A1
• Time in Patent Office: 551 Days
• Field of Search: 707713, 707759, 707769, 707706, 707718
• CPC Class Codes: B29D 2030/0682 Inner liners tubeless tyres with impervious liner or coating on the tyre B60C5/14
• CPC Class Codes: B29D 30/0681 Parts of pneumatic tyres; accessories, auxiliary operations
• CPC Class Codes: B32B 27/08 of synthetic resin
• CPC Class Codes: B32B 27/34 comprising polyamides
• CPC Class Codes: B60C 1/0008 Compositions of the inner liner
• CPC Class Codes: B60C 5/14 with impervious liner or coating on the inner wall of the tyre
• CPC Class Codes: G06F 16/242 Query formulation
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/24535 of sub-queries or views
• CPC Class Codes: G06F 16/24539 using cached or materialised query results
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/24553 of query operations
• CPC Class Codes: G06F 16/2456 Join operations
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/2474 Sequence data queries, e.g. querying versioned data
• CPC Class Codes: G06F 16/2477 Temporal data queries
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/9024 : Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/951 : Indexing; Web crawling techniques

Abstract

Techniques for implementing the hybrid execution of continuous and scheduled queries are provided. In some examples, a query engine may be initialized with relational data from at least a first source. For example, the first source may include a database or other system that can provide historical data. Additionally, the query engine may be enabled to provide query results based at least in part on the relational data from at least the first source and streaming data from at least a second source. In some examples, the second source may be a data stream.

Claims

1. A system, comprising:

a memory storing a plurality of instructions; and

one or more processors configured to access the memory, wherein the one or more processors are further configured to execute the plurality of instructions to at least;

execute a hybrid query for combining a continuous query and a scheduled database query, the hybrid query refreshed based at least in part on a schedule;

generate a stream associated with an event processor configured to provide real-time data;

initialize a query engine with relational data from a relational database, wherein the query engine is configured to provide a query result based at least in part on the relational data and streaming data from a second data source;

provide a tactical query configured to pull data elements from the relational database based at least in part on a timer;

receive, from the relational database, a relational query result based at least in part on the scheduled database query, the scheduled database query being provided to a scheduler of the relational database, and the scheduler configured to perform the scheduled database query on the relational database based at least in part on the schedule;

include the relational data from the relational query result in the generated stream by automatically pushing the relational data to the continuous query;

enable the query engine to provide a continuous query result; and

provide a user interface configured to display a visualization based at least in part on the continuous query result.

2. The system of claim 1, wherein the continuous query is configured to query the stream.

3. The system of claim 1, wherein the continuous query result is enabled to be provided to the query engine based at least in part on an event of the stream received by the query engine.

4. The system of claim 3, wherein the continuous query result is enabled to be provided to the query engine based at least in part on an event of the stream received by the query engine.

5. The system of claim 3, wherein enabling the query engine to provide the continuous query result comprises at least joining the relational data and the streaming events.

6. The system of claim 1, wherein enabling the query engine to provide the continuous query result comprises at least providing a second query that comprises the relational data to a continuous query language engine.

7. The system of claim 6, wherein enabling the query engine to provide the continuous query result includes at least receiving the continuous query result from the continuous query language engine based at least in part on the scheduled database query that includes the relational data.

8. A computer-readable memory storing a plurality of instructions executable by one or more processors, the plurality of instructions comprising:

instructions that cause the one or more processors to execute a hybrid query for combining a continuous query and a scheduled database query, the hybrid query refreshed based at least in part on a schedule;

instructions that cause the one or more processors to generate a stream associated with an event processor configured to provide real-time data;

instructions that cause the one or more processors to initialize a query engine with relational data from a relational database, wherein the query engine is configured to provide a query result based at least in part on the relational data and streaming data from a second data source;

instructions that cause the one or more processors to provide a tactical query configured to pull data elements from the relational database based at least in part on a timer;

instructions that cause the one or more processors to receive, from the relational database, a relational query result based at least in part on the scheduled database query, the scheduled database query being provided to a scheduler of the relational database, and the scheduler configured to perform the scheduled database query on the relational database based at least in part on the schedule;

instructions that cause the one or more processors to include the relational data from the relational query result in the generated stream by automatically pushing the relational data to the continuous query;

instructions that cause the one or more processors to enable the query engine to provide a continuous query result; and

instructions that cause the one or more processors to provide a user interface configured to display a visualization based at least in part on the continuous query result.

9. The computer-readable memory of claim 8, wherein the stream is generated based at least in part on a data definition language.

10. The computer-readable memory of claim 8, wherein the stream is configured to operate with an event processing engine.

11. The computer-readable memory of claim 8, wherein the continuous query is configured to query the stream.

12. The computer-readable memory of claim 9, wherein the continuous query result is enabled to be provided to the query engine based at least in part on an event of the stream received by the query engine.

13. The computer-readable memory of claim 8, wherein the continuous query result is enabled to be provided to the query engine based at least in part on an event of the stream received by the query engine.

14. A computer-implemented method, comprising:

executing a hybrid query for combining a continuous query and a scheduled database query, the hybrid query refreshed based at least in part on a schedule;

generating a stream associated with an event processor configured to provide real-time data;

initializing a query engine with relational data from a relational database, wherein the query engine is configured to provide a query result based at least in part on the relational data and streaming data from a second data source;

provide a tactical query configured to pull data elements from the relational database based at least in part on a timer;

receiving, from the relational database, a relational query result based at least in part on the scheduled database query, the scheduled database query being provided to a scheduler of the relational database, and the scheduler configured to perform the scheduled database query on the relational database based at least in part on the schedule;

including the relational data from the relational database in the generated stream by automatically pushing the relational data to the continuous query;

enabling the query engine to provide a continuous query result; and

providing a user interface configured to display a visualization based at least in part on the continuous query result.

16. The computer-implemented method of claim 14, wherein the relational database includes at least historical performance indicators.

17. The computer-implemented method of claim 14, wherein the continuous query result is enabled to be provided to the query engine based at least in part on an event of the stream received by the query engine.

18. The computer-implemented method of claim 14, wherein the continuous query result is enabled to be provided to the query engine based at least in part on an event of the stream received by the query engine.

19. The computer-implemented method of claim 14, wherein including the relational query result from the relational database in the stream comprises at least generating the stream to include an identifier associated with the relational query result.

15. The computer-implemented method of 14, wherein the query engine is configured based at least in part on a continuous query language.