The DC-Tree: A fully dynamic index structure for data warehouses

In a data warehouse, updates are typically collected and performed periodically in a batch mode, e.g., over night. This standard approach of bulk incremental updates to data warehouses has some drawbacks. First, the average runtime for a single update is small but the total runtime for the whole batch of updates may become rather large. Second, the contents of the data warehouse is not always up to date. In this paper, we introduce the DC-tree, a fully dynamic index structure for data warehouses modeled as a data cube. This new index structure is designed for applications where the above drawbacks of the bulk update approach are critical. The DC-tree is a hierarchical index structure - similar to the X-tree - exploiting the concept hierarchies typically defined for the dimensions of a data cube. We conducted an extensive experimental performance evaluation using the TPC-D benchmark data. Our results demonstrate that the DC-tree yields a significant speed-up compared to the Xtree and the sequential search when processing general range queries on a data cube.