Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: The disclosed architecture utilizes realtime continuous event processing (CEP) to address the use of a general input interface framework to import a dynamic set of event types (e.g., assets), and a declarative, expressive query model to implement monitoring and management tasks on an asset level. In one implementation, a realtime event processing system is provided, comprising a synchronization component configured to synchronize realtime event data and static event data of assets, and a realtime merge component configured to merge the synchronized realtime event data and static event data into a realtime event stream using one or more operators. The merged synchronized realtime event data and static event data is queriable as a single event type using a query to return related asset items.

Abstract: Methods, systems, and computer-readable media are disclosed for event processing with a query based on a reusable XML query template. A particular method includes receiving a plurality of events from a source and generating a plurality of event objects based on the plurality of events. A query represented by an XML file based on a reusable XML query template is executed with respect to the plurality of event objects to produce a plurality of result objects. Each result object is produced based on an application of at least one operator of the query. A plurality of results is generated based on the plurality of result objects, and the plurality of results is transmitted to a sink.

Abstract: Methods, systems, and computer-readable media are disclosed for event processing with a query based on a reusable XML query template. A particular method includes receiving a plurality of events from a source and generating a plurality of event objects based on the plurality of events. A query represented by an XML file based on a reusable XML query template is executed with respect to the plurality of event objects to produce a plurality of result objects. Each result object is produced based on an application of at least one operator of the query. A plurality of results is generated based on the plurality of result objects, and the plurality of results is transmitted to a sink.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: Methods, systems, and computer-readable media are disclosed for event processing with a query based on a reusable XML query template. A particular method includes receiving a plurality of events from a source and generating a plurality of event objects based on the plurality of events. A query represented by an XML file based on a reusable XML query template is executed with respect to the plurality of event objects to produce a plurality of result objects. Each result object is produced based on an application of at least one operator of the query. A plurality of results is generated based on the plurality of result objects, and the plurality of results is transmitted to a sink.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: Methods, systems, and computer-readable media are disclosed for time-based event processing using punctuation events. A particular method includes receiving a first event object comprising a first validity start time and a first validity end time, where the first validity end time is initially undefined. A punctuation object is received after the first event object. The punctuation event object has a punctuation timestamp indicating a time subsequent to the first validity start time. The punctuation event object indicates that event objects to be received at the computer system after the punctuation event object have validity start times later than the time indicated by the punctuation timestamp. The method includes setting the first validity end time to a value later than or equal to the time indicated by the punctuation timestamp.

Abstract: Methods, systems, and computer-readable media are disclosed for implementing adapters for event processing systems. A particular system includes an input adapter configured to store event objects received from a source at an input queue. The system also includes a query engine configured to remove event objects from the input queue, to perform a query with respect to the removed event objects to generate result objects, and to insert result objects into an output queue. The system also includes an output adapter configured to remove result objects from the output queue and to transmit the result objects to a sink.

Abstract: An extensibility framework that allows a user to write user-defined modules that include user-defined operators (UDO) and user-defined aggregators (UDA) in a non-temporal fashion without the need to worry about temporal attributes of events (or event types). The temporal domain is managed on behalf of the user, and allows the user to write operators and aggregates in the temporal data streaming domain as well as to port existing libraries of non-temporal UDOs/UDAs to the temporal data streaming domain. Temporal attributes and event types are managed for non-temporal UDOs/UDAs by the extensibility framework on behalf of the UDO/UDA writer. Windows can be employed to bridge the gap between the non-temporal domains and temporal domains. Support for complex event processing (CEP) is provided in UDOs/UDAs for base classes related to a CEP operator, CEP aggregate, CEP time sensitive operator, and CEP time sensitive aggregate.

Abstract: The subject disclosure is directed towards processing a query corresponding to event data in a foreign representation. In order to produce results for the query, an event structure is defined for each requested event type. Information is automatically generated for configuring adapters to identify attribute data associated with the each requested event type and return the attribute data according to the event structure. These adapters search historical event data or real-time event data for the event-related data.

Abstract: Methods, systems, and computer-readable media are disclosed for partitioned query execution in event processing systems. A particular method includes receiving a plurality of events via an input stream. The plurality of events is partitioned into one or more groups, and a query application module is instantiated for each of the one or more groups based on a compiled query application plan. Each particular query application module for a particular group is configured to apply a query to events of the particular group to generate partial results. The method includes merging the partial results of each of the query application modules to generate merged output results and providing the output results to an output stream.

Abstract: Methods, systems, and computer-readable media are disclosed for implementing adapters for event processing systems. A particular system includes an input adapter configured to store event objects received from a source at an input queue. The system also includes a query engine configured to remove event objects from the input queue, to perform a query with respect to the removed event objects to generate result objects, and to insert result objects into an output queue. The system also includes an output adapter configured to remove result objects from the output queue and to transmit the result objects to a sink.

Abstract: Methods, systems, and computer-readable media are disclosed for implementing adapters for event processing systems. A particular system includes an input adapter configured to store event objects received from a source at an input queue. The system also includes a query engine configured to remove event objects from the input queue, to perform a query with respect to the removed event objects to generate result objects, and to insert result objects into an output queue. The system also includes an output adapter configured to remove result objects from the output queue and to transmit the result objects to a sink.

Abstract: The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Abstract: An extensibility framework that allows a user to write user-defined modules that include user-defined operators (UDO) and user-defined aggregators (UDA) in a non-temporal fashion without the need to worry about temporal attributes of events (or event types). The temporal domain is managed on behalf of the user, and allows the user to write operators and aggregates in the temporal data streaming domain as well as to port existing libraries of non-temporal UDOs/UDAs to the temporal data streaming domain. Temporal attributes and event types are managed for non-temporal UDOs/UDAs by the extensibility framework on behalf of the UDO/UDA writer. Windows can be employed to bridge the gap between the non-temporal domains and temporal domains. Support for complex event processing (CEP) is provided in UDOs/UDAs for base classes related to a CEP operator, CEP aggregate, CEP time sensitive operator, and CEP time sensitive aggregate.