Applying Grid Technologies to XML Based OLAP Cube Construction

On-Line Analytical Processing (OLAP) is a powerful method for analysing large warehouse data. Typically, the data for an OLAP database is collected from a set of data repositories such as e.g. operational databases. This data set is often huge, and it may not be known in advance what data are required and when to perform the desired data analysis tasks. Sometimes it may happen that some parts of the data are only needed occasionally. Therefore, storing all data to the OLAP database and keeping this database constantly up-to-date is not only a highly demanding task but it also may be overkill in practice. This suggests that in some applications it would be more feasible to form the OLAP cubes only when they are actually needed. However, the OLAP cube construction can be a slow process. Here, we present a system that applies Grid technologies to distribute the computation needed in the cube construction process. As the data sources may well be heterogeneous, we propose an XML language as an interim format for collecting the data. The user’s definition for a new OLAP cube often includes selecting and aggregating the data. In our system this computation is distributed to the computers that store the original data. This reduces the network traffic and speeds up the computation that is now performed in parallel. We have implemented a prototype for the system. The implementation uses software packages called Spitfire (a data base front end) and Mobile Analyzer (a Java distributed computing platform). Both of these have their background in Grid technologies.