Processing temporal aggregates over networked workstations

TSQL2 is a query language designed for temporal databases. In TSQL2, the GROUP BY clause has a temporal grouping property. In temporal grouping, the time line of each attribute value is partitioned into several sections, and aggregate functions are computed for each time partition. This paper describes two parallel algorithms, data partition and group partition, which compute temporal aggregates over a network of workstations. In the group partition scheme, each workstation maintains the entire aggregate tree for some attribute values selected by the GROUP BY clause. Thus, some workstations may be overloaded while others are idle for most of the time. In the data partition scheme, all the workstations participate in constructing the aggregate trees in the first phase of the scheme. Thus the load is evenly distributed across the workstations in the system in the first phase of the scheme. However, before the second phase starts, workstations must exchange the aggregate trees generated at the first phase. A simulator has been used to test the performance of the two algorithms. The results show that the performance of algorithm group partition is slightly better than data partition