Abstract: Stream-based programming models allow subscriber to observe a stream of stream items received from a source, such as event notifications and updates to observed data. Presented herein is a stream-based reactive programming platform that allows observers to discover sources and streams, and to specify queries applicable to sources that results in new streams, including conditions that apply to the properties of a federation of sources. Variations of the reactive programming platform include generating a new stream from a non-reactive data source; generating a graph of sources and observers; and providing a directory of discoverable elements respectively identified by uniform resource identifiers.

Abstract: Higher-order operators are subject to checkpointing as well as recovery. The state of a higher-order operator, comprising an outer subscription and one or more inner subscriptions, is captured and subsequently utilized to recover the operator. In one instance, a data representation of code that can produce an inner subscription is saved. In other instance, an outer subscription is decoupled from inner subscriptions of a higher-order operator.

Abstract: Computation can be encoded in a lightweight and optionally typed data representation. The data representation can be specified in a prefix-based notation potentially including nested function-argument pairs. Further, the data representation can comprise optional static type information associated with at least a portion of computation. Still further, the data representation can be programming language and platform independent or surfaced in a particular programming language or platform.

Abstract: Higher-order operators are subject to checkpointing as well as recovery. The state of a higher-order operator, comprising an outer subscription and one or more inner subscriptions, is captured and subsequently utilized to recover the operator. In one instance, a data representation of code that can produce an inner subscription is saved. In other instance, an outer subscription is decoupled from inner subscriptions of a higher-order operator.

Abstract: Stream-based programming models allow subscriber to observe a stream of stream items received from a source, such as event notifications and updates to observed data. Presented herein is a stream-based reactive programming platform that allows observers to discover sources and streams, and to specify queries applicable to sources that results in new streams, including conditions that apply to the properties of a federation of sources. Variations of the reactive programming platform include generating a new stream from a non-reactive data source; generating a graph of sources and observers; and providing a directory of discoverable elements respectively identified by uniform resource identifiers.

Abstract: Computation can be encoded in a lightweight and optionally typed data representation. The data representation can be specified in a prefix-based notation potentially including nested function-argument pairs. Further, the data representation can comprise optional static type information associated with at least a portion of computation. Still further, the data representation can be programming language and platform independent or surfaced in a particular programming language or platform.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.

Abstract: Creating and executing a distributed stream processing operator graph based on a query. The operator graph includes movable stream algebra operators for processing events received from high volume data streams. The operators are partially compiled and distributed to computing devices for completion of the compilation and subsequent execution. During execution, the operators maintain minimal state information associated with received events via an expiration time assigned to each of the event instances. Additional events are generated and aggregated by the operators for communication to a service responsible for the query.