Integrating flexible rule execution into a near real-time streaming environment

• US 10,643,137 B2
• Filed: 12/23/2016
• Issued: 05/05/2020
• Est. Priority Date: 12/23/2016
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: Osborne, Elizabeth Fay, Siebers, Scott Gordon, Hays, Chad G., Komarek, Jason Andrew, Bechtel, Todd
• Primary Examiner(s): Woolwine, Shane D
• Application Number:
  US15/389,532
• Publication Number:
  US 20180181870A1
• Time in Patent Office: 1,229 Days
• Field of Search: 706 47
• CPC Class Codes: G06F 9/542 Event management; Broadcasting; Multicasting; Notifications
• CPC Class Codes: G06N 5/025 Extracting rules from data
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems

Abstract

The present invention is directed to a system and methods for integrating flexible event detection into a near real-time streaming environment. A streaming platform streams raw data from multiple sources, adds contextual information to the raw data, and makes inferences from the enriched information. A rule execution operator, being integrated within the streaming platform, executes rules against the enriched information to detect events, using a rule repository that stores a plurality of flexible, dynamic, and customizable rules. When an event is detected by the rule execution operator, the streaming platform may use a middleware component to instantiate actions that are responsive to a detected event. Actions may be directly performed, and/or the actions and instructions for implementing or performing those actions are communicated to external devices.

Claims

1. A complex event processing system, the system comprising:

a rule repository that stores a plurality of rule sets in persistent memory, wherein the plurality of rule sets comprise temporal reasoning;

a platform that;

receives streamed raw data;

identifies, in near real-time and using the streamed raw data, contextual information from an external source that is associated with the streamed raw data;

generates new enriched streamed data in near real time by fusing the streamed raw data with the identified contextual information from the external source; and

communicates the new enriched streamed data to a rule execution operator in near real time; and

a rule execution operator that;

executes in near real-time one or more rules of the plurality of rule sets in the rule repository against the new enriched streamed data to detect an event; and

when an event is detected based on the contextual information and the temporal reasoning, communicates a notification of the event to the platform, wherein the rule execution operator is integrated within the platform.

2. The system of claim 1, wherein the platform builds a plurality of person-specific records in cache memory in near real time.

3. The system of claim 2, wherein each of the plurality of person-specific records in cache memory is built by caching an association of a person identifier unique to a first person with the streamed raw data identified as corresponding to the first person.

4. The system of claim 3, wherein in response to receiving the notification of the event, the platform identifies one of the plurality of person-specific records in cache memory that corresponds to the event.

5. The system of claim 1, wherein the rule execution operator assigns the new enriched streamed data to a plurality of sessions, each of the plurality of sessions corresponding to different person identifiers.

6. The system of claim 5, wherein the rule execution operator executes the one or more rules of the plurality of rule sets against each of the plurality of sessions.

7. The system of claim 1, wherein the rule execution operator includes an input mapper that maps the new enriched streamed data to one or more sessions.

8. The system of claim 7, wherein the input mapper maps a first tuple of the new enriched streamed data to a first session associated with a first person identifier by identifying that the first tuple corresponds to new enriched streamed data of a first person, the first person corresponding to the first person identifier.

9. The system of claim 1, wherein the rule execution operator includes an output mapper that creates output using the detected event and communicates the detected event to the platform for communication to a user application.

10. The system of claim 9, wherein the output mapper interfaces with the platform.

11. The system of claim 1, wherein the rule execution operator includes:

a rule set manager that defines usage of the plurality of rule sets in the rule repository, wherein the rule set manager is an application program interface.

12. The system of claim 1, wherein the rule execution operator includes:

a rule session manager that creates one or more rule sessions using the new enriched streamed data and that destroys the one or more rule sessions.

13. The system of claim 1, further comprising:

a middleware component that, upon receiving the notification of the detected event via the platform, performs one or more of storing the detected event in an electronic health record, adding the detected event to a workflow, or triggering an alert.

14. One or more non-transitory computer-readable media having stored therein instructions executable by a processor for complex event processing, the media comprising instructions for:

via a rule execution operator integrated within a streaming platform;

receiving enriched streamed data from a streaming platform in near real time, wherein the enriched streamed data comprises contextual information from an external source added to raw streamed data in near real-time by the streaming platform when the streaming platform identifies that the contextual information is associated with the raw streamed data;

assigning the enriched streamed data to a plurality of sessions;

accessing at least one rule stored in a rule repository, wherein the rule repository stores a plurality of rules in persistent memory, and wherein the plurality of rules comprise temporal reasoning;

executing the at least one rule against the enriched streamed data assigned to one or more of the plurality of sessions to detect an event based on the contextual information and the temporal reasoning; and

when an event is detected in near real-time based on the execution of the at least one rule against the enriched streamed data, communicating a notification of the event to the streaming platform.

15. The media comprising instructions of claim 14, wherein via the rule execution operator:

for each of the plurality of sessions, identifying one or more rules of the plurality of rules to execute against the corresponding enriched streamed data, wherein the one or more rules are specifically identified based on content of the enriched streamed data.

16. The media comprising instructions of claim 14, wherein via the rule execution operator:

when the event is detected based on the execution of the at least one rule against the enriched streamed data, activating one or more additional rules for execution against a subsequent session.

17. The media comprising instructions of claim 14, wherein assigning the enriched streamed data to the plurality of sessions further comprises assigning a first portion of the enriched streamed data corresponding to a first person to a first session, and assigning a second portion of the enriched streamed data corresponding to a second person to a second session, wherein the first and second sessions are associated with different session identifiers.

18. The media comprising instructions of claim 17, wherein accessing the at least one rule stored in a rule repository further comprises determining the at least one rule is to be applied to the first session based on content of the first portion of the enriched streamed data corresponding to the first person.

19. The media comprising instructions of claim 14, wherein executing the at least one rule against one or more of the plurality of sessions to detect an event is performed in near real time, and the enriched streamed data is provided to the rule execution operator in an ongoing manner from the streaming platform.

20. A method for complex event processing, the method comprising:

receiving enriched streamed data from a streaming platform, wherein the enriched streamed data comprises contextual information from an external source added to raw streamed data in near real-time by the streaming platform when the streaming platform identifies that the contextual information is associated with the raw streamed data;

accessing at least one rule stored in a rule repository, wherein the rule repository stores a plurality of rules in persistent memory, and wherein the plurality of rules comprise temporal reasoning;

executing the at least one rule against the enriched streamed data in order to detect an event based on the contextual information and the temporal reasoning; and

when an event is detected in near real-time based on the execution of the at least one rule against the enriched streamed data, communicating a notification of the event to the streaming platform.