MANAGING RISK WITH CONTINUOUS QUERIES

• US 20140095541A1
• Filed: 03/14/2013
• Published: 04/03/2014
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Herwadkar, Rahul, Hsiao, Eric
• Granted Patent: US 9,852,186 B2
• Time in Patent Office: Days
• US Class Current: 707/774
• CPC Class Codes: B29D 2030/0682 Inner liners
• 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 managing risks with continuous queries are provided. In some examples, a selection of a data object enabled to provide a real-time stream of business event data may be received. The selection may be received by a user associated with the business event data. Additionally, a continuous query language query may be generated. The query may be configured to monitor the real-time stream of business event data for a first metric. In some examples, the a risk indicator associated with a second metric that affects the first metric may be identified. Output events of a pre-existing continuous query language query may be listened to. Further, a real-time visualization of the first metric and/or the second metric may be provided.

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;

implement a first query against a stream of business event data to receive data corresponding to a first metric associated with the business event data;

identify a second metric based at least in part on the first metric;

receive data corresponding to the second metric based at least in part on a second query implemented against the stream; and

provide at least information associated with the data corresponding to the first metric and the data corresponding to the second metric for display.

2. The system of claim 1, wherein the first metric identifies a key performance indicator of the business event data.

3. The system of claim 2, wherein the second metric identifies a risk indicator associated with the key performance indicator.

4. The system of claim 1, wherein the second metric is identified automatically by the system utilizing the received data corresponding to the first metric.

5. The system of claim 1, wherein the second metric is identified by a user associated with the business event data.

6. The system of claim 1, wherein at least one of the first or second queries is a continuous query configured to query against the stream of business event data.

7. The system of claim 6, wherein the continuous query is based at least in part on a continuous query language.

8. The system of claim 1, wherein receiving the data corresponding to the second metric includes at least listening to event output of the second query.

9. The system of claim 8, wherein the second query is implemented prior to implementation of the first query.

10. The system of claim 1, wherein the information is provided to a user via a graphical user interface.

11. 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 generate a continuous query for monitoring a first metric of streaming business event data;

instructions that cause the one or more processors to listen to a pre-existing query that outputs a second metric of the streaming business event data, the second metric affecting the first metric; and

instructions that cause the one or more processors to provide a real-time visualization of at least the first metric and the second metric.

12. The computer-readable memory of claim 11, wherein the first metric indicates a key performance indicator of the streaming business event data.

13. The computer-readable memory of claim 12, wherein the second metric indicates a risk indicator associated with a measure that affects the key performance indicator.

14. The computer-implemented method of claim 13, wherein the risk indicator is selected by a user associated with the business event data.

15. The computer-implemented method of claim 13, wherein the risk indicator is automatically determined by the one or more processors based at least in part on information associated with the key performance indicator.

16. The computer-implemented method of claim 13, wherein the risk indicator identifies a risk level associated with the key performance indicator reaching a threshold.

17. A computer-implemented method, comprising:

receiving selection, from a user associated with business event data, of a data object enabled to provide a real-time stream of the business event data;

generating a continuous query language query configured to monitor the real-time stream of the business event data for a first metric;

identifying a risk indicator associated with a second metric that affects the first metric;

listening to output events of a pre-existing continuous query language query configured to monitor the real-time stream of the business event data for the second metric; and

providing a real-time visualization of at least the first metric and the risk indicator.

20. The computer-implemented method of claim 17, wherein the selection of the data object is implemented via an application programming interface method performed by the user.

18. The computer-implemented method of 17, wherein the first metric identifies a key performance indicator of the business event data.

19. The computer-implemented method of 18, wherein identifying the risk indicator includes automatically determining one or more risk indicators that affect the key performance indicator.