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Online analytical processing (OLAP) is a critical component of data warehouse. Most of today's OLAP applications work on data warehouses with a centralized structure in which a single database contains huge amounts of data. A range query is a very popular and important operation on OLAP data cube in finding trends or relations between attributes. Methods of computing range query in a centralized data warehouse environment have been well studied. But to the best of our knowledge, there is no literature to date to discuss how to deal with the range query in a PC cluster-based parallel data warehouse. We present a parallel data cube storage structure, called parallel hierarchical data cube (PHDC). The analytical results show that PHDC may achieve better load-balance and optimum speed-up for range sum queries.