Abstract
We are currently in a big data era and raditional data management tools tends to be insufficient for massive multidimensional data processing and retrieval. In order to provide scalable multidimensional query processing capability to users, researchers have provided several techniques, e.g., MD-HBase. To help researchers have good understanding on current multidimensional indexing techniques and their design of new multidimensional indexing approach, we conduct extensive experimental study to learn the intrinsic characteristics of MD-HBase techniques. The insights we get from our extensive evaluation not only verified previous experiment results in the original publications of MD-HBase, but also analyzed some features which haven't been clearly analyzed in their original paper. Our results show that it is possible to build a multidimensional cloud indexing system that is both elastically scalable and efficient.
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