Oracle International Corporation

Netapp, Inc.

Vikram Shukla

Anand Madihalli Srinivasan

Unmesh Anil Deshmukh

Hoyong Park

Eric Hsiao

Shrikanth Shankar

Jeffrey Toillion

Ananth Raghavan

Subhransu Basu

Alexandre De Castro Alves

Roger Bolsius

Varun Jobanputra

Gaurav Agarwal

Manish M Agarwal

Parul Jain

Anant Chaudhary

Sloan Johnson

Sridher Jeyachandran

Sandeep Bishnoi

Prathab Kali

A method may include receiving a continuous query identified by an archived relation associated with an application. The method may also include generating a physical query plan. Additionally, the method may include constructing a structured query language (SQL) equivalent expression corresponding to an attribute utilized by the operator and/or constructing an output SQL expression for the identified operator based at least in part on the SQL equivalent expression. Additionally, the method may include constructing the archiver query for the identified operator based at least in part on the output SQL expression. Further, the method may include executing the archiver query to obtain a result set of data records related to the application and/or generating a snapshot output of one or more data values related to the application based at least in part on the result set of data records.

Generation of archiver queries for continuous queries over archived relations

A continuous query identified by an archived relation of an application may be received. A physical query plan may be generated for the continuous query and/or a child operator plan may be identified. A buffer operator may be inserted between the child operator and its parent operator and/or the event information from the child operator may be stored in the buffer operator. A query operator may be identified in the physical query plan. It may be determined that the query operator identified in the physical query plan is a same type as a second query operator in a second continuous query concurrently executing. Further, a combined query plan may be generated based at least in part on the query operator identified in the physical query plan being the same type as the second query operator in the second continuous query.

Operator sharing for continuous queries over archived relations

Techniques for managing real-time business event analysis and monitoring are provided. In some examples, a logical request may be received at a business intelligence server configured with a continuous query service. Additionally, the continuous query service may be configured to translate the logical request into a physical request. Further, business intelligence information may be provided based at least in part on querying against an event data stream with a continuous query configured based at least in part on the physical request translated by the continuous query service.

Real-time business event analysis and monitoring

Techniques for managing continuous queries that include subqueries are provided. In some examples, a continuous query that includes at least a subquery may be identified. Additionally, the subquery may be processed to obtain a first result or generate a logical subquery plan. Further, in some instances, the continuous query may then be processed based at least in part on the first result from the subquery or by merging a logical continuous query plan with the logical subquery plan. This may result in obtaining a second result via querying a data source with the continuous query that is based at least in part on the first result from the subquery and/or the merged plans.

Managing continuous queries in the presence of subqueries

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.

Processing events for continuous queries on archived relations

Techniques for managing continuous queries with archived relations are provided. In some examples, a query that includes at least a data stream may be identified. Additionally, the query may be initialized with at least a portion of historical data. Further, in some instances, the query may be evaluated based at least in part on the data stream and the portion of the historical data.

Managing continuous queries with archived relations

A method may include receiving a continuous query identified by an archived view. The method may also include creating the archived view, the archived view identified by a join query related to two or more archived relations associated with an application and/or generating a query plan for the continuous query. The method may also include identifying a view root operator in the archived view, the view root operator identified as a join operator in the archived view and/or identifying a query operator in the query plan that topologically precedes the view root operator. Further, the method may include constructing an archiver query for the identified query operator that topologically precedes the view root operator, executing the archiver query to obtain a result set of data records related to the application, and/or generating a snapshot output of one or more data values related to the application.

State initialization for continuous queries over archived views

One embodiment of the invention includes a method of processing streaming data. The method includes initializing a stream of data and setting a time interval to apply to the stream of data. The time interval comprises a window for analyzing the data within the stream of data. The method further includes identifying one or more columns within the stream of data, designating one or more of the columns to be monitored for differences within the data over the time interval, and monitoring the designated columns over the time interval. Further, the method includes determining that at least one value from at least one of the designated columns has changed and in response to at least one value changing, outputting the changed values from the designated columns.

Support for a new insert stream (ISTREAM) operation in complex event processing (CEP)

Techniques for implementing the hybrid execution of continuous and scheduled queries are provided. In some examples, a query engine may be initialized with relational data from at least a first source. For example, the first source may include a database or other system that can provide historical data. Additionally, the query engine may be enabled to provide query results based at least in part on the relational data from at least the first source and streaming data from at least a second source. In some examples, the second source may be a data stream.

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Fremont, CA, United States of America

Vikram Shukla