Optimizational Method of HBase Multi-dimensional Data Query Based on Hilbert Space-Filling Curve

Abstract

HBase distributed database technology has been widely used in missive data processing. The problem of the efficiency of multi-dimensional data query which is caused by its single primary key indexing becomes more apparent. This paper proposed and implemented a multi-dimensional query method based on Hilbert space-filling curve. Using the Hilbert space filling curve to make the multi-dimensional data space to be one-dimensional lossless compression, on the basis of mapping the query conditions to the multi-dimensional space, and then using the subspace match to generate Hilbert segment, thereby convert into a single dimension query. Finally, the experiments prove that this method can query the keyword of multi-dimensional space more efficiently with the massive data and has a good load balancing performance. And this method can be more effective to avoid the issue of the server cluster hotspot.