Abstract

Many queries that constrain multiple dimensions simultaneously are difficult to express and compute efficiently in both Structured Query Language (SQL) and multi-dimensional languages. We introduce the diamond cube operator, filling a gap among existing data warehouse operations. It aids decision support and analysis by facilitat-ing the execution of simultaneous multidimensional queries on data cubes. An example query from the business analysis domain follows. A company wants to close shops and terminate product lines simul-taneously. The CEO wants the maximal set of products and shops such that each shop would have sales greater than $400 000, and each prod-uct would bring revenues of at least $100 000—assuming we terminate all other shops and product lines. Diamonds are intrinsically multidimensional and because of the interaction between dimensions the computation of diamond cubes is challenging. We present diamond dicing experiments on large data sets of more than 100 million facts. Our custom Java implementation is more than one hundred times faster, on a large data set, than a popular database engine.