Mechanism to chain continuous queries

• US 9,946,756 B2
• Filed: 03/14/2013
• Issued: 04/17/2018
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Hsiao, Eric, Park, Hoyong, Srinivasan, Anand
• Primary Examiner(s): Syed, Farhan
• Application Number:
  US13/830,735
• Publication Number:
  US 20140095540A1
• Time in Patent Office: 1,860 Days
• Field of Search: None
• 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 mechanisms for chaining continuous queries are provided. In some examples, results of a first continuous query may be stored in a data object. For example, the first continuous query may be configured to process business event data and store the results in the data object. Additionally, a second continuous query may then be processed based at least in part on the results stored in the data object.

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;

process a first continuous query on an archived relation of business event data, the archived relation of business event data comprising a first data source for the first continuous query and comprising an unordered, time-varying set of tuples associated with the first data source;

collect first results of the first continuous query during a time interval;

store the first results of the first continuous query in a first data object for at least a time period, wherein the time period is determined based at least in part on performance criteria associated with the first data object;

implement a second continuous query configured to only process “

insert”

instructions found within the first results stored in the first data object, the first results comprising a second data source for the second continuous query, and wherein processing only “

insert”

instructions comprises not processing other instructions found within the first results stored in the first data object;

collect second results from processing the second continuous query;

store the second results of the second continuous query in a second data object;

implement a pattern match query on the second results stored in the second data object;

perform trend analysis on the pattern match query results;

provide, for display by a user interface, a mapping of the trend analysis to a visualization;

identifying a pattern corresponding to a performance indicator from the trend analysis; and

provide an alert in the user interface based at least in part on the pattern identified from the trend analysis.

2. The system of claim 1, wherein the one or more processors are further configured to execute the plurality of instructions to at least audit the first results stored in the data object.

3. The system of claim 1, wherein the first data object is configured as a stream data object.

4. The system of claim 1, wherein the one or more processors are further configured to execute the plurality of instructions to at least map the first data object to a visualization.

5. The system of claim 4, wherein the one or more processors are further configured to execute the plurality of instructions to at least prepare the visualization for display by the user interface of a user associated with the business event data.

6. The system of claim 1, wherein the second continuous query is processed prior to completion of the first period of time.

7. The system of claim 1, wherein the one or more processors are further configured to execute the plurality of instructions to at least enable modification of the first data object.

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 process a first continuous query on an archived relation of business event data associated with a user to collect first results during a time interval, the archived relation of business event data comprising a first data source for the first continuous query and comprising an unordered, time-varying set of tuples associated with the first data source;

instructions that cause the one or more processors to store the first results in memory as a first data object for at least a time period, wherein the time period is determined based at least in part on performance criteria associated with the first data object;

instructions that cause the one or more processors to implement, based at least in part on receipt of a trigger, a second continuous query configured to only process “

insert”

instructions found within the first results of the first data object, the first results comprising a second data source for the second continuous query, and wherein processing only “

insert”

instructions comprises not processing other instructions found within the first results stored in the first data object;

instructions that cause the one or more processors to collect second results from the processing of the second continuous query;

instructions that cause the one or more processors to store the second results of the second continuous query in a second data object

instructions that cause the one or more processors to implement a pattern match query on the second results stored in the second data object;

instructions that cause the one or more processors to perform trend analysis on the pattern match query results;

instructions that cause the one or more processors to provide, for display by a user interface, a mapping of the trend analysis to a visualization;

instructions that cause the one or more processors to identify a pattern corresponding to a performance indicator from the trend analysis; and

instructions that cause the one or more processors to provide an alert in the user interface based at least in part on the pattern identified from the trend analysis.

9. The computer-readable memory of claim 8, wherein the first results are collected based on a moving window.

10. The computer-readable memory of claim 9, wherein at least one of the moving window or the time interval is determined by the user.

11. The computer-readable memory of claim 8, wherein the trigger indicates a change in the first results stored in the first data object.

12. A computer-implemented method, comprising:

processing a first continuous query on archived relation of business event data associated with a user to collect first results during a time interval, the archived relation of business event data comprising a first data source for the first continuous query and comprising an unordered, time-varying set of tuples associated with the first data source;

storing the first results in memory as a first data object for at least a time period, wherein the time period is determined based at least in part on performance criteria associated with the first data object;

implementing, based at least in part on receipt of a trigger, a second continuous query configured to only process “

insert”

instructions found within the first results stored in the first data object to collect second results, the first results comprising a second data source for the second continuous query, and wherein processing only “

insert”

instructions comprises not processing other instructions found within the first results stored in the first data object;

collecting second results from the processing of the second continuous query;

storing the second results of the second continuous query in a second data object;

implementing a pattern match query on the second results stored in the second data object;

performing trend analysis on the pattern match query results;

providing, for display by a user interface of the user, a mapping of the trend analysis to a visualization;

identifying a pattern corresponding to a performance indicator from the trend analysis; and

providing an alert to the user based at least in part on the pattern identified from the trend analysis.

13. The computer-implemented method of claim 12, wherein the mapping is configured to provide a real-time visualization of changes of the trend analysis.