SYSTEMS AND METHODS TO CREATE CONTINUOUS QUERIES ASSOCIATED WITH PUSH-TYPE AND PULL-TYPE DATA

• US 20100017380A1
• Filed: 07/16/2008
• Published: 01/21/2010
• Est. Priority Date: 07/16/2008
• Status: Active Grant

• Current Assignee: Business Objects SA (SAP SE)
• Original Assignee: Business Objects SA (SAP SE)
• Inventors: Grosselin, Jean-Claude, Naibo, Alexis, Marinescu, Dan Cristian
• Granted Patent: US 9,135,583 B2
• Time in Patent Office: Days
• US Class Current: N/A
• CPC Class Codes: G06F 16/2428 Query predicate definition using graphical user interfaces, including menus and forms G06F16/2423 takes precedence
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system, method, means, and/or computer program code may be provided to facilitate query creation and a presentation of information to a user. According to some embodiments, continuous query definition parameters are received from a user via a graphical user interface. Moreover, semantic layer information associated with an event processing engine may be retrieved, the event processing engine being adapted to receive an event stream. Based on the continuous query definition parameters, a pre-fetch query may be automatically created to pre-fetch historical data from a database. An event processing language statement may also be created based on (i) the continuous query definition parameters and (ii) the semantic layer information. The event processing language statement may be provided to the complex event processing engine so as to establish a continuous query. A response to the query may be output based on both the pre-fetched historical data and events in the event stream.

Claims

1. A computer-readable medium having stored thereon processor-executable instructions that when executed by a processor result in the following:

receiving, at a query technique engine, continuous query definition parameters from a user via a graphical user interface;

retrieving, at the query technique engine, semantic layer information associated with an event processing engine, the event processing engine being adapted to receive an event stream;

based on the continuous query definition parameters from the user, automatically creating at the query technique engine a pre-fetch query to pre-fetch historical data from a database;

automatically creating an event processing language statement at the query technique engine, the event processing language statement being created based on (i) the continuous query definition parameters from the user and (ii) the semantic layer information; and

providing the event processing language statement to the complex event processing engine so as to establish a continuous query, the continuous query providing output data based on both the pre-fetched historical data and events in the event stream.

2. The computer-readable medium of claim 1, wherein the historical data is associated with a pull-model and the events in the event stream are associated with a push-model.

3. The computer-readable medium of claim 1, wherein execution of the instructions further results in:

joining the historical data with information associated with events in the event stream.

4. The computer-readable medium of claim 3, wherein the joining is associated with at least one of:

(i) an inner join, (ii) an outer join, (iii) a left join, (iv) a right join, or (v) a full join.

5. The computer-readable medium of claim 1, wherein the semantic layer information includes at least one of:

(i) schema definitions, (ii) tables defining attributes, (iii) business object metadata, (iv) metadata based on an entity relationship model, (v) a metadata name, (vi) a metadata description, (vii) a metadata object type, (viii) dimension, measure, detail, or pre-condition object definitions, (ix) a metadata data type, (x) a metadata aggregation type, (xi) metadata distinction information, (xii) metadata formula information, (xiii) stream adapter metadata, (xiv) event driven universe metadata, or (xv) query panel information.

6. The computer readable medium of claim 1, wherein the semantic layer information includes at least one of:

(i) window information defining a bounded portion of the event stream, (ii) a window time parameter, (iii) a window count parameter, (iv) window sliding information, (v) window cycling information, (vi) window unique information, (vii) window top information, or (viii) window bottom information.

7. The computer-readable medium of claim 1, wherein the continuous query definition parameters from the user include at least one of:

(i) an event driven universe, (ii) an event driven query, (iii) a class, (iv) an object, (v) an adapter, (vi) a source stream, (vii) a target, or (viii) a filter.

8. The computer-readable medium of claim 1, wherein execution of the instructions further results in:

responsive to the output data, transmitting information to a remote business user via a push-model.

9. The computer-readable medium of claim 8, wherein the transmitted information is associated with at least one of:

(i) a web service associated with a client, (ii) a desktop widget application associated with a client, (iii) a dashboard application associated with a client, (iv) a web analytic application associated with a client, or (v) a web browser application associated with a client.

10. The computer-readable medium of claim 8, wherein the information is transmitted to at least one of:

(i) a personal computer, or (ii) a wireless device.

11. The computer-readable medium of claim 1, wherein at least some of the semantic layer information is associated with a first stream adapter metadata component associated with the event stream and a second stream adapter metadata component associated with the database.

12. The computer-readable medium of claim 1, wherein at least some of the semantic layer information is associated with an event driven universe specification module that enables creation of an event driven universe specification with entities and relationships between entities.

13. The computer-readable medium of claim 1, wherein the continuous query is further associated with user security information.

14. A method, comprising:

receiving query definition parameters from a user via a graphical user interface;

based on the query definition parameters, automatically creating a pull-type query to pull data from a database;

based on the query definition parameters, automatically creating a push-type continuous event query; and

establishing a continuous user-query, the continuous user-query providing user output data based on both the pull-type query and the push-type continuous event query.

15. The method of claim 14, wherein the automatic creation of the pull-type query is associated with semantic layer information.

16. The method of claim 15, wherein the automatic creation of the push-type continuous event query is also associated with the semantic layer information.

17. The method of claim 15, wherein the query definition parameters from the user create a query on a universe pointing to a database.

18. The method of claim 17, wherein the query definition parameters from the user define a database query with universe business objects.

19. The method of claim 15, wherein the graphical user interface lets the user graphically connect pull-type information with push-type information.

20. An apparatus, comprising:

a semantic layer component;

a relational database interface;

a query technique engine to receive (i) continuous query definition parameters from a graphical user interface component, (ii) semantic layer information from the semantic layer component, and (iii) pre-fetch information from the relational database interface; and

a complex event processing engine to receive an event processing language statement from the query technique engine along with at least one event stream from a business intelligence data source.

21. The apparatus of claim 20, wherein the relational database interface is associated with at least one of:

(i) an online analytic programming data source, or (ii) a hypercube.