Parallel Query Processing

With relations growing larger and queries becoming more complex, parallel query processing is an increasingly attractive option for improving the performance of database systems. The objective of this paper is to examine the various issues encountered in parallel query processing and the techniques available for addressing these issues. The focus of the paper is on the join operation with both sort-merge join and hash joins being considered. Three types of parallelism can be exploited, namely intra-operator, inter-operator, and inter-query parallelism. In intra-operator parallelism the major issue is task creation, and the objective is to split a join operation into tasks in a manner such that the load can be spread evenly across a given number of processors. This is a challenge when the values on the join attribute are not uniformly distributed. Inter-operator parallelism can be achieved either through parallel execution of independent operations or through pipelining. In either case, the major issues are the join sequence selection, which determines the precedence relations among the operations and the pipeline structures that can be exploited, and the processor allocation for each operation. For inter-query parallelism, the issue again is processor allocation, but at the query level. Various techniques to address each of these issues have been studied in the past, albeit under diierent assumptions and generally focussing on only one of the issues. In this paper, we explore a method for obtaining inter-query parallelism based on a hierarchical approach and a uniied framework, so that the potential integration of the techniques used to address each type of parallelism can be illustrated.