Hybrid execution of continuous and scheduled queries

• US 9,286,352 B2
• Filed: 03/14/2013
• Issued: 03/15/2016
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Park, Hoyong, Srinivasan, Anand, Shukla, Vikram
• Primary Examiner(s): Uddin, MD. I
• Application Number:
  US13/828,640
• Publication Number:
  US 20140095462A1
• Time in Patent Office: 1,097 Days
• Field of Search: 707/713, 707/759, 707/769, 707/622, 707/706, 707/714, 707/792
• US Class Current: 1/1
• 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 or a time interval;

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

initialize a query engine with relational data from at least a second source;

identify the continuous query for querying the generated stream;

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

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

include the relational data from the second source in the generated stream by automatically pushing the relational data to the continuous query configured to query the generated stream;

enable the query engine to provide a continuous query result based at least in part on an event of the generated stream received by the query engine, the event from a plurality of events of the generated stream including streaming events from the event processor and the relational data; and

provide a user interface configured to display an active visualization based at least in part on data pushed to the query engine.

2. The system of claim 1, wherein the streaming data from at least the first source includes the real-time data provided by the event processor.

3. The system of claim 1, wherein enabling the query engine to provide the continuous query result includes at least joining the relational data and the streaming data.

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

5. The system of claim 4, 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 provided second query that includes the relational data.

6. 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 or a time interval;

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

instructions that cause the one or more processors to register the generated stream with a query engine;

instructions that cause the one or more processors to receive, by the query engine, a relational query result from a data source;

instructions that cause the one or more processors to identify the continuous query for querying the generated stream;

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

instructions that cause the one or more processors to receive, from the data source, a relational query result based at least in part on the tactical query, the tactical query being provided to a scheduler of the relational database, and the scheduler configured to perform the tactical 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 query result from the second source in the generated stream by automatically pushing the relational query result to the continuous query configured to query the generated stream;

instructions that cause the one or more processors to provide a continuous query result based at least in part on an event of the generated stream received by the query engine, the event from a plurality of events of the generated stream including streaming events from the complex event processor and the relational query result; and

instructions that cause the one or more processors to provide a user interface configured to display an active visualization based at least in part on data pushed to the query engine.

7. The computer-readable memory of claim 6, wherein the stream is generated based at least in part on a data definition language.

8. The computer-readable memory of claim 6, wherein the stream is configured to operate with an event processing engine corresponding to the complex event processor.

9. The computer-readable memory of claim 6, wherein the relational query result is received based at least in part on a schedule.

10. The computer-readable memory of claim 6, wherein including the relational query result from the data source in the generated stream includes at least generating the stream to include an identifier associated with the relational query result.

11. 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 or a time interval;

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

registering, by the computing system, the generated stream with a query engine;

identifying the continuous query for querying the registered stream;

providing, to a data source that comprises a relational database, a tactical query configured to pull data elements from the data source based at least in part on a timer;

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

including, by the computing system, the relational query result from the data source in the registered stream by automatically pushing the relational query result to the continuous query configured to query the registered stream;

providing, by the computing system, a continuous query result based at least in part on an event of the generated stream received by the query engine, the event from a plurality of events of the generated stream including streaming events from the event processor and the relational query result; and

providing a user interface configured to display an active visualization based at least in part on data pushed to the query engine.

13. The computer-implemented method of claim 11, wherein the relational database includes at least historical performance indicators.

14. The computer-implemented method of claim 11, wherein including the relational query result from the data source in the registered stream includes at least generating the stream to include an identifier associated with the relational query result.

12. The computer-implemented method of 11, wherein the query engine is configured based at least in part on a continuous query language.