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Recently several important relational database tasks such as index selection, histogram tuning, approximate query processing, and statistics selection have recognized the importance of leveraging workloads. Often these tasks are presented with large workloads, i.e., a set of SQL DML statements, as input. A key factor affecting the scalability of such tasks is the size of the workload. In this paper, we present the novel problem of workload compression which helps improve the scalability of suchdoi:10.1145/564691.564747 dblp:conf/sigmod/ChaudhuriGN02 fatcat:54enognxdzcornt53cg3y2nh2q