Parallel algorithms for computing temporal aggregates

J.A.G. Gendrano, B.C. Huang, J.M. Rodrigue, Bongki Moon, R.T. Snodgrass
1999 Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337)  
The ability to model the temporal dimension is essential to many applications. Furthermore, the rate of increase in database size and response time requirements has outpaced advancements in processor and mass storage technology, leading to the need for parallel temporal database management systems. In this paper, we introduce a variety of parallel temporal aggregation algorithms for a sharednothing architecture based on the sequential Aggregation Tree algorithm. Via an empirical study, we found
more » ... cal study, we found that the number of processing nodes, the partitioning of the data, the placement of results, and the degree of data reduction effected by the aggregation impacted the performance of the algorithms. For distributed results placement, we discov-
doi:10.1109/icde.1999.754958 dblp:conf/icde/GendranoHRMS99 fatcat:rrpdss7sxjfqncjt2ibvelhqaa