Abstract: A method of efficiently providing estimated answers to workloads of aggregate, multi-join SQL-like queries over a number of input data-streams. The method only examines each data elements once and uses a limited amount of computer memory. The method uses join graphs and atomic sketches that are essentially pseudo-random summaries formed using random binary variables. The estimated answer is the product of all the atomic sketches for all the vertices in the query join graph. A query workload is processed efficiently by identifying and sharing atomic sketches common to distinct queries, while ensuring that the join graphs remain well formed. The method may automatically minimize either the average query error or the maximum query error over the workload.

Abstract: A method of efficiently providing estimated answers to workloads of aggregate, multi-join SQL-like queries over a number of input data-streams. The method only examines each data elements once and uses a limited amount of computer memory. The method uses join graphs and atomic sketches that are essentially pseudo-random summaries formed using random binary variables. The estimated answer is the product of all the atomic sketches for all the vertices in the query join graph. A query workload is processed efficiently by identifying and sharing atomic sketches common to distinct queries, while ensuring that the join graphs remain well formed. The method may automatically minimize either the average query error or the maximum query error over the workload.