Interaction-aware prediction of business intelligence workload completion times

While planning the execution of report-generation workloads, database administrators often need to know how long different query workloads will take to run. Database systems run mixes of multiple queries of different types concurrently. Hence, estimating the completion time of a query workload requires reasoning about query mixes and inter-query interactions in the mixes; rather than considering queries or query types in isolation. This paper presents a novel approach for estimating workload completion time based on experiment-driven modeling and simulation of the impact of inter-query interactions. A preliminary evaluation of this approach with TPC-H queries on IBM DB2 shows how our approach can consistently predict workload completion times with good accuracy.