OLAP is a set of database exploratory techniques to efficiently retrieve multiple sets of aggregations from a large dataset. Generally, these techniques have either involved the use of an external OLAP server or required the dataset to be exported to a specialized OLAP tool for more efficient processing. In this work, we show that OLAP techniques can be performed within a modern DBMS without external servers or the exporting of datasets, using standard SQL queries and UDFs. The main challenge of such approach is that SQL and UDFs are not as flexible as the C language to explore the OLAP lattice and therefore it is more difficult to develop optimizations. We compare three different ways of performing OLAP exploration: plain SQL queries, a UDF implementing a lattice structure, and a UDF programming the star cube structure. We demonstrate how such methods can be used to efficiently explore typical OLAP datasets.
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