The chunk-locality index: An efficient query method for climate datasets
Geoscientists have a constant need to query into large-scale multidimensional array-based datasets. The most efficient way to accelerate queries is indexing. We focus on the climate datasets and propose a novel and efficient indexing method called the chunk-locality index. The main idea of this method is to take advantage of the spatial-temporal data similarity in climate datasets. We evaluate the performance of chunk-locality index in various chunk sizes with two practical climate datasets, and compare the performance results with the bitmap index. The comparison results show that the chunk-locality index presents better performance than the bitmap index not only in improving the efficiency of data queries but also in the index building time and the index size. 2012 IEEE.