Aggregation Query Rewritings Based on Clusters in Inconsistent Databases
This paper presents the rewriting method for aggregation queries based on clusters and non-aggregation queries in inconsistent databases. The expectation and the extremum are limited by range of aggregation values to propose non-join and join rewriting strategies for aggregation queries. The aggregation rewritten queries analyze potential tuples of clusters and grouping attributes to filter clusters and calculate the expectation and the extremum of original grouping attributes. The experiment presents a performance study using the data and queries of the TPC-H decision support benchmark, and analyzes some effects of relative factors such as the cluster cardinality and database size. Although the experiment results show that rewritten queries are longer than original queries for run time, the run time may be accepted and the method is effective.