earticle

영어

Range-aggregate queries are popular in many applications in data warehouse environments with large business relational databases. To evaluate these efficiently, several studies on data cubes (such as the aggregate cubetree) have been carried out. In the well-known aggregate cubetree, each entry in every node stores the aggregate values of its corresponding subtree. Therefore, range-aggregate queries can be processed without visiting the child subtree whose nodes are all fully included in the query range. However, the aggregate cubetree does not consider range queries using partial dimensions and range queries without aggregation operations. Concretely, 1) a great deal of information that is irrelevant to the queries also has to be read from the disk for partial-dimensional range queries, and 2) while it improves the performance of range queries with aggregate operations, it degrades the performance of range queries without aggregate operations. As part of our research on this problem, previously we proposed an index structure, called the Aggregate-tree (denoted as Ag-tree), which does away with the above-mentioned weaknesses of the aggregate cubetree. Additionally in this paper, we make the Ag-tree more complete by sorting the entries in each of the nodes. The final index structure proposed in this study is called an Ag+-tree.