Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying events in a stream computing system using hierarchical analytic models. One of the methods includes receiving, by a stream computing system, data representing the values of one or more data attributes of an event in a stream of events. The values of each of the one or more data attributes are evaluated according to respective attribute-specific and class-specific criteria of a hierarchical analytic model in a predetermined order defined by the model. When a first value of a first data attribute satisfies one or more particular criteria for a first class, the first class of the plurality of classes is assigned to the event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying events in a stream computing system using hierarchical analytic models. One of the methods includes receiving, by a stream computing system, data representing the values of one or more data attributes of an event in a stream of events. The values of each of the one or more data attributes are evaluated according to respective attribute-specific and class-specific criteria of a hierarchical analytic model in a predetermined order defined by the model. When a first value of a first data attribute satisfies one or more particular criteria for a first class, the first class of the plurality of classes is assigned to the event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying events in a stream computing system using hierarchical analytic models. One of the methods includes receiving, by a stream computing system, data representing the values of one or more data attributes of an event in a stream of events. The values of each of the one or more data attributes are evaluated according to respective attribute-specific and class-specific criteria of a hierarchical analytic model in a predetermined order defined by the model. When a first value of a first data attribute satisfies one or more particular criteria for a first class, the first class of the plurality of classes is assigned to the event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying events in a stream computing system using hierarchical analytic models. One of the methods includes receiving, by a stream computing system, data representing the values of one or more data attributes of an event in a stream of events. The values of each of the one or more data attributes are evaluated according to respective attribute-specific and class-specific criteria of a hierarchical analytic model in a predetermined order defined by the model. When a first value of a first data attribute satisfies one or more particular criteria for a first class, the first class of the plurality of classes is assigned to the event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for stream processing with contextual data affinity. One of the methods includes receiving an event at a computing node of a stream processing system that includes one or more computing nodes and data representing a topology of functional modules. At a particular functional module of the topology, an operation that requests access to context data related to the event is determined based on a data attribute of the event. The context data is partitioned among the one or more computing nodes. Context data related to the event is obtained from the computing node. The operation of the particular functional module is processed using the context data, and a modified event is generated. The modified event is provided to a subsequent functional module according to the topology of functional modules.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for stream processing with contextual data affinity. One of the methods includes receiving an event at a computing node of a stream processing system that includes one or more computing nodes and data representing a topology of functional modules. At a particular functional module of the topology, an operation that requests access to context data related to the event is determined based on a data attribute of the event. The context data is partitioned among the one or more computing nodes. Context data related to the event is obtained from the computing node. The operation of the particular functional module is processed using the context data, and a modified event is generated. The modified event is provided to a subsequent functional module according to the topology of functional modules.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying events in a stream computing system using hierarchical analytic models. One of the methods includes receiving, by a stream computing system, data representing the values of one or more data attributes of an event in a stream of events. The values of each of the one or more data attributes are evaluated according to respective attribute-specific and class-specific criteria of a hierarchical analytic model in a predetermined order defined by the model. When a first value of a first data attribute satisfies one or more particular criteria for a first class, the first class of the plurality of classes is assigned to the event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for stream processing with contextual data affinity. One of the methods includes receiving an event at a computing node of a stream processing system that includes one or more computing nodes and data representing a topology of functional modules. At a particular functional module of the topology, an operation that requests access to context data related to the event is determined based on a data attribute of the event. The context data is partitioned among the one or more computing nodes. Context data related to the event is obtained from the computing node. The operation of the particular functional module is processed using the context data, and a modified event is generated. The modified event is provided to a subsequent functional module according to the topology of functional modules.