Pivotal Software, Inc.

Emc Corporation

David Russell Brown

Michael Brand

Kee Siong Ng

Lyndon John Adams

Jeffrey Mark Nick

Vinesh Prasanna Manoharan

David Stephen Reiner

Nihar Nanda

John D Hushon, Jr

Jagannathan Ramnarayanan

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for routing events of an event stream in a stream processing system. One of the methods includes receiving, by a router, an event stream of events; identifying, for each event, by the router, a respective partition of context data that includes context data related to the event and providing the event to a respective local modeler that stores the partition of context data identified for the event in operational memory of the local modeler; processing, by each local modeler, events received from the router and aggregating information associated with each event to generate aggregated information; providing, by one or more of the local modelers, to a central modeler, the respective aggregated information; and determining, by the central modeler, a plurality of parameters of a machine learning model using the received aggregated information.

Compute intensive stream processing with context data routing

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for stream processing. One method includes receiving an event stream of events by a first plurality of local modelers of a stream processing system. Each local modeler processes a portion of received events of the event stream according to a first set of operations, the operations including aggregating information associated with each event to generate aggregated information. One or more local modelers provide, to a first central modeler executing on the system, the respective aggregated information generated by one or more of the local modelers. A set of parameters of a respective machine learning model is determined using the received aggregated information.

Compute intensive stream processing

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for stream processing. One method includes receiving an event stream of first events by a first plurality of first local modelers of a stream processing system. Each local modeler processes a portion of received events of the event stream according to a first set of operations, the operations including aggregating information associated with each event to generate first aggregated information. A second plurality of second local modelers similarly generates second aggregated information from an event stream of second events. First and second local modelers provide, to a first central modeler, first and second aggregated information. A set of parameters of a respective machine learning model is determined by the first central modeler using the received aggregated information.

Stream processing with multiple connections between local and central modelers

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for routing events of an event stream. One of the methods includes operations of receiving, by a router, events of an event stream; providing each event, by the router, to a respective local modeler selected by the router according to an initial routing strategy, the respective local modeler being selected from multiple local modelers; aggregating, by each local modeler in parallel, information associated with each event received by the local modeler to generate aggregated information; providing, to a central modeler, the aggregated information generated by the one or more local modelers; determining, by the central modeler, parameters of a machine learning model using the aggregated information received by the central modeler and generating an updated routing strategy based on the parameters of the machine learning model; and providing the updated routing strategy to the router.

Stream processing with dynamic event routing

Example embodiments of the present invention relate to a method, a system, and a computer program product for federated service requests of a logical data store comprising a plurality of heterogeneous data stores. The method includes providing a data abstraction services layer as a control plane for federated service requests of a logical data store, comprising a plurality of heterogeneous data stores, by an application operating on a processing device, receiving a service request at the data abstraction services layer from the application operating on the processing device directed to the logical data store, and returning results of the service request from the data abstraction services layer to the application operating on the processing device.

Coordinated configuration, management, and access across multiple data stores

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.

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San Marcos, CA, United States of America

David Russell Brown