Research of Temporal Information Index Strategy Based on HBase

In view of the demand of massive unstructured data storage and fast retrieval, in this study, it puts forward a distributed and unstructured database HBase under the Hadoop platform to store massive temporal data, and to build a temporal data storage model with the store unit as the temporal set. Designing a multi-level distributed hash table indexing algorithm (t-DHT), so that realized retrieval the temporal attribute values of the temporal column family efficiently and rapidly. By mapping temporal attribute value to two-dimensional space, the transformation of temporal data to spatial object is realized. Dividing the temporal data area by using the spatial data processing method generates multilevel temporal data sub domain, and designing HBase stored multilevel index table by using the distributed hash table. Experimental results show that the proposed method has higher performance and can speed up the retrieval speed of temporal information in HBase to a certain extent.