IP Library Granted Patent US 9,992,248
Granted Patent B2
US 9,992,248 · App. 14/993,160 · Granted Jun 5, 2018

Scalable event stream data processing using a messaging system

Inventors: Timothy M. Fox (Lakewood, OH); Anyi Li (Rocky River, OH); Scott J. McCallen (Stow, OH); Douglas S. Meil (Chagrin Falls, OH); Kaveh Noorbakhsh (Mayfield Heights, OH)
Assignee: International Business Machines Corporation
H04L65/4076G06F11/2007G06F17/30516G06F19/322G06F2201/85
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Quick Facts
Patent No.
US 9,992,248
App. No.
14/993,160
Granted
Jun 5, 2018
Kind
B2
Abstract

A system processes streaming data and includes at least one processor. The system may write streaming data received from a data source as messages in queues at a queuing cluster. The queuing cluster includes a coordinator node to direct the messages to non-coordinator nodes of the queuing cluster. The system may retrieve the data from the queues based on subscription of topics and store the retrieved data in a consumable repository.

Claims (37)

1. A system for processing data to generate consumable data for downstream consumers comprising:

at least one processor configured to:

write streaming data received from a data source as messages in queues at a queuing cluster, wherein the queuing cluster includes a coordinator node to direct the messages to non-coordinator nodes of the queuing cluster;

retrieve the data from the queues based on subscription of topics;

store the retrieved data in a consumable repository;

wherein the at least one processor is further configured to:

listen for the streaming data to be available in the queues by a processing node, the streaming data being event data for one or more events at the data source;

read each event from the queues by the processing node; and

transform the events to a data model of the consumable repository.

2. The system of claim 1 , wherein the at least one processor is further configured to:

manage the processing node by a coordinator node of a processing cluster; and

retry processing of the streaming data on a different processing node until successful in response to the processing node encountering a failure.

3. The system of claim 1 , wherein the streaming data includes patient data received from a healthcare network.

4. The system of claim 2 , wherein the consumable repository is a queuing system including a coordinator node to direct the processing node to write the retrieved data to a non-coordinator node in the consumable repository.

5. The system of claim 4 , wherein the queuing cluster and consumable repository each include multiple non-coordinator nodes that provide automated replication and failover through management by the respective coordinator nodes.

6. The system of claim 1 , wherein the at least one processor is further configured to perform one or more operations from a group of:

routing the retrieved data to different long term storage; and

pushing the retrieved data to a number of different services that satisfy specific business needs.

7. The system of claim 1 , wherein the at least one processor is further configured to concurrently retrieve data from the consumable repository by a plurality of consumers, wherein the consumers maintain respective pointers to track data that each consumer has processed.

8. A computer program product for linking data objects for common entities across source systems, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by at least one processor to cause the at least one processor to:

write streaming data received from a data source as messages in queues at a queuing cluster, wherein the queuing cluster includes a coordinator node to direct the messages to non-coordinator nodes of the queuing cluster;

retrieve the data from the queues based on subscription of topics;

store the retrieved data in a consumable repository;

wherein the at least one processor is further caused to:

listen for the streaming data to be available in the queues by a processing node, the streaming data being event data for one or more events at the data source;

read each event from the queues by the processing node; and

transform the events to a data model of the consumable repository.

9. The computer program product of claim 8 , wherein the at least one processor is further caused to:

manage the processing node by a coordinator node of a processing cluster; and

retry processing of the streaming data on a different processing node until successful in response to the processing node encountering a failure.

10. The computer program product of claim 8 , wherein the streaming data includes patient data received from a healthcare network.

11. The computer program product of claim 9 , wherein the consumable repository is a queuing system including a coordinator node to direct the processing node to write the retrieved data to a non-coordinator node in the consumable repository.

12. The computer program product of claim 11 , wherein the queuing cluster and consumable repository each include multiple non-coordinator nodes that provide automated replication and failover through management by the respective coordinator nodes.

13. The computer program product of claim 8 , wherein the at least one processor is further caused to perform one or more operations from a group of:

routing the retrieved data to different long term storage; and

pushing the retrieved data to a number of different services that satisfy specific business needs.

14. The computer program product of claim 8 , wherein the at least one processor is further caused to concurrently retrieve data from the consumable repository by a plurality of consumers, wherein the consumers maintain respective pointers to track data that each consumer has processed.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 12, 2016
From: FOX, TIMOTHY M.; LI, ANYI; MCCALLEN, SCOTT J.; MEIL, DOUGLAS S.; NOORBAKHSH, KAVEH
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 037461/0284 →
Continuity (1)
Related Publication 20170201556A1 · Jul 13, 2017