Abstract: The present systems and methods allow for rapid processing of large volumes of events. A producer node in a cluster determines a sharding key for a received event from an event stream. The producer node uses a sharding map to correlate the sharding key for the event with a producer channel, and provides the event to a producer event buffer associated with the producer channel. The producer event buffer transmits the event to a corresponding consumer event buffer associated with a consumer channel on a consumer node. The event processing leverages a paired relationship between producer channels on the producer node and consumer channels on the consumer node, so as to generate enhanced throughput. The event processing also supports dynamic rebalancing of the system in response to adding or removing producer or consumer nodes, or adding or removing producer or consumer channels to or from producer or consumer nodes.

Abstract: The present systems and methods allow for rapid processing of large volumes of events. A producer node in a cluster determines a sharding key for a received event from an event stream. The producer node uses a sharding map to correlate the sharding key for the event with a producer channel, and provides the event to a producer event buffer associated with the producer channel. The producer event buffer transmits the event to a corresponding consumer event buffer associated with a consumer channel on a consumer node. The event processing leverages a paired relationship between producer channels on the producer node and consumer channels on the consumer node, so as to generate enhanced throughput. The event processing also supports dynamic rebalancing of the system in response to adding or removing producer or consumer nodes, or adding or removing producer or consumer channels to or from producer or consumer nodes.

Abstract: The present systems and methods allow for rapid processing of large volumes of events. A producer node in a cluster determines a sharding key for a received event from an event stream. The producer node uses a sharding map to correlate the sharding key for the event with a producer channel, and provides the event to a producer event buffer associated with the producer channel. The producer event buffer transmits the event to a corresponding consumer event buffer associated with a consumer channel on a consumer node. The event processing leverages a paired relationship between producer channels on the producer node and consumer channels on the consumer node, so as to generate enhanced throughput. The event processing also supports dynamic rebalancing of the system in response to adding or removing producer or consumer nodes, or adding or removing producer or consumer channels to or from producer or consumer nodes.

Abstract: A method comprises selecting at least a first data set and a second data set on which to apply a query. The method also comprises causing generating of a first cursor based and a second cursor based on a first application of the query on the first data set and a second cursor based on a second application of the query on the second data set. A third cursor based on a combination of a result set returned by the first cursor and second cursor is then generated in response to the query.

Abstract: An approach is provided for providing data based on granularity information. The policy platform determines to act on a request, from an application or a service, for data associated with a device, a user of the device or a combination thereof. Next, the policy platform determines a granularity level for the data based, at least in part, on at least one privacy policy associated with the data, the application, the service, the device, the user of the device or a combination thereof. Then, the policy platform processes and/or facilitates a processing of the data to generate transformed data based, at least in part, on the granularity level.

Abstract: The present systems and methods allow for rapid processing of large volumes of events. A producer node in a cluster determines a sharding key for a received event from an event stream. The producer node uses a sharding map to correlate the sharding key for the event with a producer channel, and provides the event to a producer event buffer associated with the producer channel. The producer event buffer transmits the event to a corresponding consumer event buffer associated with a consumer channel on a consumer node. The event processing leverages a paired relationship between producer channels on the producer node and consumer channels on the consumer node, so as to generate enhanced throughput. The event processing also supports dynamic rebalancing of the system in response to adding or removing producer or consumer nodes, or adding or removing producer or consumer channels to or from producer or consumer nodes.

Abstract: An approach is provided for backend based computation closure oriented distributed computing. A computational processing support infrastructure receives a request for specifying one or more processes executing on a device for distribution over a computation space. The computational processing support infrastructure also causes, at least in part, serialization of the one or more processes as one or more closure primitives, the one or more closure primitives representing computation closures of the one or more processes. The computational processing support infrastructure further causes, at least in part, distribution of the one or more closure primitives over the computation space based, at least in part, on a cost function.

Abstract: A method is provided that includes receiving a first triple including a subject, predicate and object, where the object is of a literal-type. For the first triple, then, the method includes identifying a subtype of the object; semantically marking the object with the identified subtype, including generating second and third triples; and storing the second and third triples in a triple store. In this regard, the second triple includes the subject and predicate of the first RDF triple as the subject and predicate thereof, and the third RDF triple includes the object of the first RDF triple or a representation of the object of the first RDF triple as the object thereof.

Abstract: An approach is provided for enabling the accounting of closures to support query requests established by a device. A computation processing and accounting infrastructure determines one or more closures based, at least in part, on a query request. One of the one or more closures based, at least in part, on one or more predetermined policies is selected to generate a response to the query.

Abstract: A method is provided that includes receiving a first triple including a subject, predicate and object, where the object is of a literal-type. For the first triple, then, the method includes identifying a subtype of the object; semantically marking the object with the identified subtype, including generating second and third triples; and storing the second and third triples in a triple store. In this regard, the second triple includes the subject and predicate of the first RDF triple as the subject and predicate thereof, and the third RDF triple includes the object of the first RDF triple or a representation of the object of the first RDF triple as the object thereof.

Abstract: An approach is provided for dynamic modification of inference rules and deduction engines in an information base. Authorized agents are allowed to insert, delete or modify inference rules and deduction engines dynamically by signing their input using an authorized signature. Additionally, the functionalities of dynamic modification of inference rules and deduction engines can be provided through a direct application programming interface (API).

Abstract: An approach is provided for providing data based on granularity information. The policy platform determines to act on a request, from an application or a service, for data associated with a device, a user of the device or a combination thereof. Next, the policy platform determines a granularity level for the data based, at least in part, on at least one privacy policy associated with the data, the application, the service, the device, the user of the device or a combination thereof. Then, the policy platform processes and/or facilitates a processing of the data to generate transformed data based, at least in part, on the granularity level.

Abstract: An approach is provided for providing persistent computations. A persistent computation manager determines at least one non-volatile memory space of a device. The persistent computation manager also determines at least one other non-volatile memory space of at least one other device. The persistent computation manager further determines to form a persistent memory address space based, at least in part, on the at least one non-volatile memory space and the at least one other non-volatile memory space.

Abstract: A method is provided that includes receiving a first triple including a subject, predicate and object, where the object is of a literal-type. For the first triple, then, the method includes identifying a subtype of the object; semantically marking the object with the identified subtype, including generating second and third triples; and storing the second and third triples in a triple store. In this regard, the second triple includes the subject and predicate of the first RDF triple as the subject and predicate thereof, and the third RDF triple includes the object of the first RDF triple or a representation of the object of the first RDF triple as the object thereof.

Abstract: An approach is provided for backend based computation closure oriented distributed computing. A computational processing support infrastructure receives a request for specifying one or more processes executing on a device for distribution over a computation space. The computational processing support infrastructure also causes, at least in part, serialization of the one or more processes as one or more closure primitives, the one or more closure primitives representing computation closures of the one or more processes. The computational processing support infrastructure further causes, at least in part, distribution of the one or more closure primitives over the computation space based, at least in part, on a cost function.

Abstract: An approach is provided for enabling the accounting of closures to support query requests established by a device. A computation processing and accounting infrastructure determines one or more closures based, at least in part, on a query request. One of the one or more closures based, at least in part, on one or more predetermined policies is selected to generate a response to the query.

Abstract: A method comprises selecting at least a first data set and a second data set on which to apply a query. The method also comprises causing generating of a first cursor based and a second cursor based on a first application of the query on the first data set and a second cursor based on a second application of the query on the second data set. A third cursor based on a combination of a result set returned by the first cursor and second cursor is then generated in response to the query.

Abstract: An approach is provided for providing operations for manipulation of distributed computations. A computations closure management infrastructure determines to receive a request for specifying one or more operations to perform on one or more computation spaces, wherein the one or more computation spaces represent one or more computational processes as one or more graphs within the respective one or more computation spaces. The computation closures management infrastructure determines to retrieve the one or more computation spaces, the one or more graphs within the one or more computation spaces, one or more subgraphs of the one or more graphs, or a combination thereof.

Abstract: An approach is provided for dynamic modification of inference rules and deduction engines in an information base. Authorized agents are allowed to insert, delete or modify inference rules and deduction engines dynamically by signing their input using an authorized signature. Additionally, the functionalities of dynamic modification of inference rules and deduction engines can be provided through a direct application programming interface (API).

Abstract: A device for generating semantic folder annotations is provided. The device includes a semantic folder editor which enables a user to create attribute-value pairs corresponding to a semantic folder(s). The device is capable of downloading ontolog(ies) and associated data from an ontology server which may be utilized to determine relationships between the attribute-value pairs created by the user. The device includes an annotations generator which specifies the semantic folder descriptions of the semantic folders based on attribute-value relationships determined by the ontolog(ies). The device is capable of allowing a user to insert an object(s) into a semantic folder(s) and the annotations generator assigns all attribute-value pairs corresponding to the semantic folder to the object(s). The annotations assigned to object(s) may be stored in a semantic triple store. The device further includes a search engine which may be employed by a user to search semantic folders to locate an object(s).