Practical throughput estimation for parallel databases

Methods for estimating the performance of database management systems can aid the design of database systems by identifying potential performance bottlenecks or by predicting the relative performance of different designs. Performance estimation is critical in parallel database systems with distributed memory, where an effective overall performance depends on a good choice among a wide range of ways of placing data. An approach is described for the performance estimation for shared-nothing parallel database systems. This analytical system throughput estimator, called STEADY (System Throughput Estimator for Advanced Database sYstems), estimates system throughput for a given benchmark or set of queries, and can exercise different data placement schemes to determine the data layout that provides the best throughput value