Data Placement in Parallel Database Systems

The way in which data is distributed across the processing elements of a parallel shared-nothing architecture can have a signiicant eeect on the performance of a parallel DBMS. Data placement strategies provide a mechanical approach to determining a data distribution which will provide good performance. However, there is considerable variation in the results produced by diierent strategies and no simple way of determining which strategy will provide the best results for any particular database application. This paper considers ve diierent data placement strategies and illustrates some of the problems associated with the placement of data by studying the sensitivity of the results produced by these diierent strategies to the changes in a number of environmental factors, such as the number of processing elements participating in database activities and the size of database. The study was conducted by using an analytical performance estimator for parallel database systems, in the context of a shared-nothing parallel database system using the transaction processing benchmark TPC-C. It provides some insight into the eeect which diierent types of strategies can have on the overall performance of the system.