Implementing data cubes via subcubes

OLAP queries are complex and time-consuming and hence the data cube materialization is a commonly used technique to reduce response time. To the best of our knowledge, most of previous OLAP cube implementation techniques apply a static view selection algorithm on the search lattice. This static method first treats each node in the lattice as an undividable unit and then picks some of them for materialization. Pre-computing some nodes without being aware of which nodes are actually accessed at run time would seriously impact both response time and available space. We propose to further partition a node in the lattice into subcubes into each of which multiple OLAP queries via a dynamic materialization algorithm can be mapped. The results of OLAP queries are generally enlarged to subcubes to take potential locality effects into consideration. Experiments show that our dynamic method retains a reasonable performance even though the available space is very limited and is practical for OLAP query processing.