Abstract: Methods and systems for computing a risk metric on a network of processing nodes are disclosed. The method includes receiving a plurality of events at a plurality of processing nodes. The method further includes at a first processing node, processing on a first event and a known instance of a second event to determine whether the first event matches the known instance of the second event. The method further includes in response to determining that the first event does not match the known instance of the second event, terminating the processing without generating an output, and generating a first output event having a resulting probability computed based on a confidence value of the first event and a first probabilistic value of a first missing event, or in response to determining that the first event matches the known instance of the second event, generating the first output event having the resulting probability computed based on the confidence value of the first event.

Abstract: Methods and systems for computing a risk metric on a network of processing nodes are disclosed. The method includes receiving a plurality of events at a plurality of processing nodes. The method further includes at a first processing node, processing on a first event and a known instance of a second event to determine whether the first event matches the known instance of the second event. The method further includes in response to determining that the first event does not match the known instance of the second event, terminating the processing without generating an output, and generating a first output event having a resulting probability computed based on a confidence value of the first event and a first probabilistic value of a first missing event, or in response to determining that the first event matches the known instance of the second event, generating the first output event having the resulting probability computed based on the confidence value of the first event.

Abstract: Disclosed herein are system, method, and computer program product embodiments for utilizing an intrusive data hash table to support processing transactions. An embodiment operates by receiving a transaction comprising a plurality of operations. Responsive to the receiving, the transaction is verified by verifying the validity of the plurality of operations. Responsive to verifying the transaction, the transaction is applied to the intrusive hash table.

Abstract: Disclosed herein are system, method, and computer program product embodiments for utilizing an intrusive data hash table to support processing transactions. An embodiment operates by receiving a transaction comprising a plurality of operations. Responsive to the receiving, the transaction is verified by verifying the validity of the plurality of operations. Responsive to verifying the transaction, the transaction is applied to the intrusive hash table.

Abstract: A query inserter receives data elements having individual priority types for placement in a queue, and utilizes the priority types of the received data elements to determine placement in the queue relative to an initial location established when a first data element is placed in an empty queue in order to manage the queue with a combination of first-in first-out and last-in first-out queue functionality.

Abstract: A query inserter receives data elements having individual priority types for placement in a queue, and utilizes the priority types of the received data elements to determine placement in the queue relative to an initial location established when a first data element is placed in an empty queue in order to manage the queue with a combination of first-in first-out and last-in first-out queue functionality.