Diamond dicing

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摘要

In OLAP, analysts often select an interesting sample of the data. For example, an analyst might focus on products bringing revenues of at least $100,000, or on shops having sales greater than $400,000. However, current systems do not allow the application of both of these thresholds simultaneously, selecting products and shops satisfying both thresholds. For such purposes, we introduce the diamond cube operator, filling a gap among existing data warehouse operations.Because of the interaction between dimensions the computation of diamond cubes is challenging. We compare and test various algorithms on large data sets of more than 100 million facts. We find that while it is possible to implement diamonds in SQL, it is inefficient. Indeed, our custom implementation can be a hundred times faster than popular database engines (including a row-store and a column-store).

论文关键词:OLAP,Information retrieval,Multidimensional queries

论文评审过程:Received 16 June 2010, Revised 31 December 2012, Accepted 7 January 2013, Available online 18 January 2013.

论文官网地址:https://doi.org/10.1016/j.datak.2013.01.001