Spatio-temporal indexes for events in public opinion system

With the development of various media platforms, Internet users would like to become the producer of information and the spreader of the public opinion. Meanwhile, there are mounts of information fragments of public opinion events on the Internet. And users always issue queries according to specific spatial and temporal predicates to better understand the whole process of events. This paper focuses on addressing spatio-temporal query problem in the task of “event assembling” in public opinion system, where information fragments (snippets) are stored in HBase. Many previous works tackle the problem by designing schema, i.e., designing row key and column key formation for HBase. But it can not achieve high query efficiency. In this paper, we address this problem from nature level of HBase by using an index structure of STEHIX (Spatio-TEmporal Hbase IndeX) as a built-in component for HBase. We propose the model of Event Assembling and the algorithms of range query and kNN query for it. STEHIX is adapted to the two-level architecture of HBase and suitable for HBase to process spatio-temporal queries. It is composed of index in the meta table (the first level) and region index (the second level) for indexing inner structure of HBase regions. Base on this structure, the range query and kNN query are solved by proposing algorithms, respectively. We manually collect events data from the Internet, and implement STEHIX and conduct experiments on real dataset, and the results show our design outperforms a previous work in many aspects.