Abstract: A method includes determining, using a processor, a set of aggregate queries to be executed on a data stream, the set of aggregate queries comprising queries that perform respective sets of aggregation operations on respective sets of attribute values over respective time intervals. The method also includes generating, using the processor, at least one intermediate aggregate query for a subset of the set of aggregate queries, the at least one intermediate aggregate query combining a subset of aggregation operations for the subset of aggregate queries and a subset of attribute values. The method further includes executing, using the processor, the at least one intermediate aggregate query to generate pre-aggregated data from the data stream for the subset of aggregate queries and executing, using the processor, the subset of aggregate queries subsequent to executing the at least one intermediate aggregate query on the pre-aggregated data.

Abstract: Improved techniques are disclosed for processing data stream queries wherein a data stream is obtained, a set of aggregate queries to be executed on the data stream is obtained, and a query plan for executing the set of aggregate queries on the data stream is generated. In a first method, the generated query plan includes generating at least one intermediate aggregate query, wherein the intermediate aggregate query combines a subset of aggregate queries from the set of aggregate queries so as to pre-aggregate data from the data stream prior to execution of the subset of aggregate queries such that the generated query plan is optimized for computational expense based on a given cost model. In a second method, the generated query plan includes identifying similar filters in two or more aggregate queries of the set of aggregate queries and combining the similar filters into a single filter such that the single filter is usable to pre-filter data input to the two or more aggregate queries.

Abstract: A method includes determining, using a processor, a set of aggregate queries to be executed on a data stream, the set of aggregate queries comprising queries that perform respective sets of aggregation operations on respective sets of attribute values over respective time intervals. The method also includes generating, using the processor, at least one intermediate aggregate query for a subset of the set of aggregate queries, the at least one intermediate aggregate query combining a subset of aggregation operations for the subset of aggregate queries and a subset of attribute values. The method further includes executing, using the processor, the at least one intermediate aggregate query to generate pre-aggregated data from the data stream for the subset of aggregate queries and executing, using the processor, the subset of aggregate queries subsequent to executing the at least one intermediate aggregate query on the pre-aggregated data.

Abstract: Improved techniques are disclosed for processing data stream queries wherein a data stream is obtained, a set of aggregate queries to be executed on the data stream is obtained, and a query plan for executing the set of aggregate queries on the data stream is generated. In a first method, the generated query plan includes generating at least one intermediate aggregate query, wherein the intermediate aggregate query combines a subset of aggregate queries from the set of aggregate queries so as to pre-aggregate data from the data stream prior to execution of the subset of aggregate queries such that the generated query plan is optimized for computational expense based on a given cost model. In a second method, the generated query plan includes identifying similar filters in two or more aggregate queries of the set of aggregate queries and combining the similar filters into a single filter such that the single filter is usable to pre-filter data input to the two or more aggregate queries.