Abstract: A method for detecting patterns across multiple input data streams related to one or more applications is disclosed. The method includes receiving multiple input data streams and generating one or more dynamic data types for one or more attributes of the input data streams. In some embodiments, the method may include combining the input data streams to generate a combined input data stream based on the dynamic data types and processing a continuous query over the combined data stream to detect a pattern.

Abstract: A continuous query may be received, the continuous query being identified based at least in part on an archived view. The archived view may be created and/or identified based at least in part on a join query related to two or more archived relations associated with an application, at least one of the two or more archived relations being identified as a dimension relation. A query plan for the continuous query may be generated. A join operator in the query plan may be identified based at least in part on the dimension relation. A state of an operator corresponding to the dimension relation may be initialized. It may be identified if the state of the operator identifies an event that detects a change to the dimension relation. The continuous query may be re-started based at least in part on the event that detects the change to the dimension relation.

Abstract: A method for detecting patterns across multiple input data streams related to one or more applications is disclosed. The method includes receiving multiple input data streams and generating one or more dynamic data types for one or more attributes of the input data streams. In some embodiments, the method may include combining the input data streams to generate a combined input data stream based on the dynamic data types and processing a continuous query over the combined data stream to detect a pattern.

Abstract: A continuous query may be received, the continuous query being identified based at least in part on an archived view. The archived view may be created and/or identified based at least in part on a join query related to two or more archived relations associated with an application, at least one of the two or more archived relations being identified as a dimension relation. A query plan for the continuous query may be generated. A join operator in the query plan may be identified based at least in part on the dimension relation. A state of an operator corresponding to the dimension relation may be initialized. It may be identified if the state of the operator identifies an event that detects a change to the dimension relation. The continuous query may be re-started based at least in part on the event that detects the change to the dimension relation.