Abstract: An event processing system is disclosed that processes events of an event stream and performs the recovery of events during system failure. The recovery of events is performed by generating output sequence numbers for each deterministic output event generated by the event processing system. In an embodiment, the event processing system determines a current output sequence number of a most recently transmitted output event in a output stream of events, a last output sequence number of an output event corresponding to a most recently processed batch of input events and determines a set of one or more output events of the output stream to be transmitted based on the current sequence number and the last output sequence number. The event processing system then transmits the output events related to the application.

Abstract: Systems and methods for guaranteeing the event order for multi-stage processing in distributed systems are disclosed. In some examples, a warm-up period is used to accurately determine a starting point for ordered events of an event stream. Skip-beats may be utilized as dummy events so that the event processor does not wait too long for events that were filtered out at earlier stages.

Abstract: An event processing system is disclosed that processes events of an event stream, performs the recovery of events during system failure and preserves the state of the system reliably and accurately while achieving desired system performance. In an embodiment, the event processing system processes a first batch of events of a continuous input stream of events using a continuous query and generates an output stream of events related to an application. The event processing system identifies one or more operators of the continuous query and determines that an operator is a journaled operator. The event processing system generates a journaled snapshot of a current state of the system based on execution of the journaled operator on at least the first batch of events and stores the journaled snapshot of the current state of the system.

Abstract: Techniques for tracking large numbers of moving objects in an event processing system are provided. An input event stream can be received, where the events in the input event stream represent the movement of a plurality of geometries or objects. The input event stream can then be partitioned among a number of processing nodes of the event processing system, thereby enabling parallel processing of one or more continuous queries for tracking the objects. The partitioning can be performed such that each processing node is configured to track objects in a predefined spatial region, and the spatial regions for at least two nodes overlap. This overlapping window enables a single node to find, e.g., all of the objects within a particular distance of a target object, even if the target object is in the process of moving from the region of that node to the overlapping region of another node.

Abstract: Techniques for tracking large numbers of moving objects in an event processing system are provided. An input event stream can be received, where the events in the input event stream represent the movement of a plurality of geometries or objects. The input event stream can then be partitioned among a number of processing nodes of the event processing system, thereby enabling parallel processing of one or more continuous queries for tracking the objects. The partitioning can be performed such that each processing node is configured to track objects in a predefined spatial region, and the spatial regions for at least two nodes overlap. This overlapping window enables a single node to find, e.g., all of the objects within a particular distance of a target object, even if the target object is in the process of moving from the region of that node to the overlapping region of another node.

Abstract: Techniques for extending the capabilities of an event processing system to support the processing of spatial data. In one set of embodiments, this extensibility can be provided via a plug-in extension component referred to herein as a spatial data cartridge. The spatial data cartridge can enable the event processing system to support spatial data types (e.g., point, polygon, etc.) and various operations related to such data types (e.g., proximity determinations, overlap determinations, etc.). The spatial data cartridge can also define an indexing scheme that can be integrated with the capabilities of the event processing system to support the indexing of spatial data. Using the spatial data cartridge, the event processing system can operate on spatial data even if spatial data formats are not natively supported by the system.

Abstract: 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.

Abstract: A method including receiving, at a computer system, debugging configuration information specifying a functional area of a data stream processing server to be debugged, is described. Furthermore, the method includes identifying, by the computer system, an object associated with the functional area that has been instantiated by the data stream processing server, determining, by the computer system, that tracing for the object is enabled to perform the debugging, and instantiating, by the computer system, a tracelet associated with the object. Further, the method includes stepping, by the computer system, through the tracelet associated with the object to debug the object, and displaying, by the computer system, a visual representation of debugging results associated with the object.

Abstract: Embodiments implement a plug-in architecture supporting adding new data sources to a legacy federated database without the need to recode a federated database manager software module. The federated database manager software module includes an administrative tool and a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The administrative tool generates presentation panes including new data sources added to the legacy federated database.

Abstract: Embodiments implement a plug-in architecture supporting adding new data sources to a federated database without the need to recode a federated database manager software module. The federated database manager software module includes a plug-in framework for interfacing with a data source cartridge. The data source cartridge supplies metadata including a feature table of a newly added data source to the framework and creates a physical query for the newly added data source based on an execution plan generated by the federated database manager software module. The data source cartridge returns the result set of the query of the new added data source to the federated database manager software module.

Abstract: A framework or infrastructure (extensibility framework/infrastructure) for extending the indexing capabilities of an event processing system. The capabilities of an event processing system may be extended to support indexing schemes, including related data types and operations, which are not natively supported by the event processing system. The extensibility is enabled by one or more plug-in extension components called data cartridges.

Abstract: 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.

Abstract: Techniques for tracking large numbers of moving objects in an event processing system are provided. An input event stream can be received, where the events in the input event stream represent the movement of a plurality of geometries or objects. The input event stream can then be partitioned among a number of processing nodes of the event processing system, thereby enabling parallel processing of one or more continuous queries for tracking the objects. The partitioning can be performed such that each processing node is configured to track objects in a predefined spatial region, and the spatial regions for at least two nodes overlap. This overlapping window enables a single node to find, e.g., all of the objects within a particular distance of a target object, even if the target object is in the process of moving from the region of that node to the overlapping region of another node.

Abstract: Techniques for tracking large numbers of moving objects in an event processing system are provided. An input event stream can be received, where the events in the input event stream represent the movement of a plurality of geometries or objects. The input event stream can then be partitioned among a number of processing nodes of the event processing system, thereby enabling parallel processing of one or more continuous queries for tracking the objects. The partitioning can be performed such that each processing node is configured to track objects in a predefined spatial region, and the spatial regions for at least two nodes overlap. This overlapping window enables a single node to find, e.g., all of the objects within a particular distance of a target object, even if the target object is in the process of moving from the region of that node to the overlapping region of another node.

Abstract: A framework for extending the capabilities of an event processing system using one or more plug-in components referred to herein as data cartridges. In one set of embodiments, the data cartridge framework described herein can enable an event processing system to support one or more extension languages that are distinct from the native event processing language supported by the system. For example, certain “extension language” data cartridges can be provided that enable an event processing system to support complex data types and associated methods/operations that are common in object-oriented languages, but are not common in event processing languages. In these embodiments, an event processing system can access an extension language data cartridge to compile and execute queries that are written using a combination of the system's native event processing language and the extension language.

Abstract: Techniques for reducing the memory used for processing events received in a data stream are provided. This may be achieved by reducing the memory required for storing tuples. A method for processing a data stream includes receiving a tuple and determining a tuple specification that defines a layout of the tuple. The layout identifies one or more data types that are included in the tuple. A tuple class corresponding to the tuple specification may be determined. A tuple object based on the tuple class is instantiated, and during runtime of the processing system. The tuple object is stored in a memory.

Abstract: Techniques for implementing mechanisms for chaining continuous queries are provided. In some examples, results of a first continuous query may be stored in a data object. For example, the first continuous query may be configured to process business event data and store the results in the data object. Additionally, a second continuous query may then be processed based at least in part on the results stored in the data object.

Abstract: 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.

Abstract: 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.

Abstract: 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.