Processing events for continuous queries on archived relations

• US 9,990,401 B2
• Filed: 03/14/2013
• Issued: 06/05/2018
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Toillion, Jeffrey, Deshmukh, Unmesh Anil, Srinivasan, Anand, Shukla, Vikram
• Primary Examiner(s): Kerzhner, Aleksandr
• Assistant Examiner(s): GIULIANI, GIUSEPPI J
• Application Number:
  US13/830,428
• Publication Number:
  US 20140095483A1
• Time in Patent Office: 1,909 Days
• 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 counting event changes with archived relations are provided. In some examples, a query that identifies at least a data object may be identified. Additionally, the query may be evaluated against historical data associated with the data object. Additionally, in some instances, a listening service may be registered with the data object. Further, the query may be evaluated based at least in part on the data object and the historical data.

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;

identify, by a query engine, that a continuous query is to be utilized for processing data of an archived relation that comprises a bounded data set of historical event data corresponding to a stream of business event data, the archived relation comprising a startup state;

identify, from a data definition language statement, annotations about the archived relation;

create the continuous query based at least in part on the annotations;

generate a data structure for a query operator graph that represents the continuous query, the data structure comprising nodes that represent each operator of the continuous query;

traverse, by the query engine, the data structure topologically from a source of the query operator graph;

identify, by the query engine, a particular stateful operator of the data structure that is a lowest stateful operator reached while traversing the data structure;

register a listening service with the stream of business event data prior to creating the archived relation;

receive, from a user, a window size for configuring the archived relation;

create, using the query engine, the archived relation to include the bounded data set of historical event data upon creation, the archived relation being non-empty at its creation, the creation of the archived relation comprising;

applying a window that corresponds to the window size on the stream of business event data; and

evaluating a snapshot query against the historical event data associated with the stream of business event data, the evaluation of the snapshot query comprising;

executing a structure query language (SQL) query to collect historical data;

receiving the historical data, via the SQL query, corresponding to the particular stateful operator of the data structure that was identified as the lowest stateful operator reached while traversing the data structure; and

initializing the continuous query with the historical data corresponding to the lowest stateful operator reached while traversing the data structure; and

evaluate the continuous query with respect to the archived relation after completion of the evaluation of the snapshot query against the historical data associated with the stream of business event data.

2. The system of claim 1, wherein the listening service is registered with the stream of business event data prior to evaluating the snapshot query against the historical data.

3. The system of claim 2, wherein changes identified by the listening service are processed after completion of evaluation of the snapshot query against the historical data.

4. The system of claim 1, wherein the processors are further configured to execute the plurality of instructions to at least receive a transaction identifier for at least a change identified by the listening service.

5. The system of claim 4, wherein the transaction identifier comprises a monotonically increasing integer that increases for each change associated with the data object.

6. The system of claim 4, wherein the processors are further configured to execute the plurality of instructions to at least:

compare the received transaction identifier with a highest transaction identifier associated with the historical data; and

process the change identified by the listening service only when the received transaction identifier is greater than the highest transaction identifier associated with the historical data.

7. The system of claim 1, wherein the continuous query is configured to process the data of the stream of business event data.

8. The system of claim 1, wherein the historical data comprises at least a portion of the business event data from the data stream at a time before initializing the continuous query.

9. The system of claim 1, wherein the evaluation of the snapshot query against the historical data associated with the stream of business event data is configured to initialize a query engine of the system.

10. A non-transitory 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 implement a query engine for identifying that a continuous query is to be utilized for processing data of an archived relation that comprises a bounded data set of historical event data corresponding to a stream of business event data, the archived relation comprising a startup state;

instructions that cause the one or more processors to identify, from a data definition language statement, annotations about the archived relation;

instructions that cause the one or more processors to create the continuous query based at least in part on the annotations;

instructions that cause the one or more processors to generate a data structure for a query operator graph that represents the continuous query, the data structure comprising nodes that represent each operator of the continuous query;

instructions that cause the one or more processors to traverse, by the query engine, the data structure topologically from a source of the query operator graph;

instructions that cause the one or more processors to identify, by the query engine, a particular stateful operator of the data structure that is a lowest stateful operator reached while traversing the data structure;

instructions that cause the one or more processors to register a listening service with the stream of business event data prior to creating the archived relation;

instructions that cause the one or more processors to receive, from a user, a window size for configuring the archived relation;

instructions that cause the one or more processors to create, using the query engine, the archived relation to include the bounded data set of historical event data upon creation, the archived relation being non-empty at its creation, the creation of the archived relation comprising;

instructions that cause the one or more processors to apply a window that corresponds to the window size on the stream of business event data; and

instructions that cause the one or more processors to evaluate a snapshot query against the historical event data associated with the stream of business event data after registration of the listening service with the stream of business event data to initialize the archived relation, the evaluation of the snapshot query comprising;

executing a structure query language (SQL) query to collect historical data;

receiving the historical data, via the SQL query, corresponding to the particular stateful operator of the data structure that was identified as the lowest stateful operator reached while traversing the data structure; and

initializing the continuous query with the historical data corresponding to the lowest stateful operator reached while traversing the data structure;

instructions that cause the one or more processors to process changes identified by the listening service after completion of the evaluation of the snapshot query against the historical data; and

instructions that cause the one or more processors to evaluate the continuous query with respect to the archived relation.

11. The non-transitory computer-readable memory of claim 10, wherein the plurality of instructions further comprise instructions that cause the one or more processors to receive a transaction identifier for at least a change identified by the listening service.

12. The non-transitory computer-readable memory of claim 11, wherein the transaction identifier comprises a monotonically increasing integer that increases for each change associated with the archived relation.

13. The non-transitory computer-readable memory of claim 11, wherein the plurality of instructions further comprise instructions that cause the one or more processors to compare the received transaction identifier with a highest transaction identifier associated with the historical data.

14. The non-transitory computer-readable memory of claim 13, wherein the plurality of instructions further comprise instructions that cause the one or more processors to process the change identified by the listening service only when the received transaction identifier is greater than the highest transaction identifier associated with the historical data.

15. A computer-implemented method, comprising:

identifying, by a query engine, that a continuous query is to be utilized for processing data of an archived relation that comprises a bounded data set of historical event data corresponding to a stream of business event data, the archived relation comprising a startup;

identifying, from a data definition language statement, annotations about the archived relation;

creating the continuous query based at least in part on the annotations;

generating a data structure for a query operator graph that represents the continuous query, the data structure comprising nodes that represent each operator of the continuous query;

traversing, by the query engine, the data structure topologically from a source of the query operator graph;

identifying, by the query engine, a particular stateful operator of the data structure that is a lowest stateful operator reached while traversing the data structure;

registering a listening service with the stream of business event data prior to initializing the archived relation;

receiving, from a user, a window size for configuring the archived relation;

creating, using the query engine, the archived relation to include the bounded data set of historical event data upon creation, the archived relation being non-empty at its creation, the creation of the archived relation comprising;

applying a window that corresponds to the window size on the stream of business event data; and

evaluating a snapshot query against the historical data associated with the stream of business event data, the evaluation of the snapshot query comprising;

executing a structure query language (SQL) query to collect historical data;

receiving the historical data, via the SQL query, corresponding to the particular stateful operator of the data structure that was identified as the lowest stateful operator reached while traversing the data structure; and

initializing the continuous query with the historical data corresponding to the lowest stateful operator reached while traversing the data structure;

receiving a transaction identifier for at least a change identified by the listening service;

comparing the received transaction identifier with a highest transaction identifier associated with the historical data;

processing the change identified by the listening service, after completion of the evaluation of the continuous query against the historical data associated with the stream of business event data, when the received transaction identifier is greater than the highest transaction identifier associated with the historical data; and

evaluating the continuous query with respect to the archived relation.

17. The computer-implemented method of claim 15, further comprising not processing the change identified by the listening service when the received transaction identifier is less than the highest transaction identifier associated with the historical data or equal to the highest transaction identifier associated with the historical data.

18. The computer-implemented method of claim 15, wherein a state of the archived relation is re-initialized using a second snapshot query after restart of the continuous query.

16. The computer-implemented method of 15, wherein the snapshot query is evaluated against the historical data associated with the stream of business event data after registration of the listening service with the stream of business event data.