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K2-treaps to represent and query data warehouses into main memory

In this paper we propose the use of the compact data structure k2-treap to process data cubes of Data Warehouses (DWs) into main memory. Compact data structures are data structures that allow compacting the data without losing the capacity of querying them in their compact form. A DW is a data repository to store historical data for decision support, and consists of dimensions and facts. The former are an abstract concept that groups data with a similar meaning, they are modelled as hierarchies of levels, which contain elements. The latter are quantitative data associated to dimensions. A data cube is a typical way to retrieve facts at different levels of granularity (through navigation on dimensions hierarchies). A DW can store terabytes of data, thus the efficient processing of data cubes is key in OLAP (On-line Analytical Processing). We show that by using a compact representation of data cubes and bitmaps to represent dimensions we are able to improve the use of space in main memory, and achieve better performance for query processing.