To meet the needs for storing and quick retrieving mass unstructured temporal information

it proposed using the distributed and unstructured database HBase

which was on the Hadoop platform

to store temporal data. Then

it built the temporal data storage model with the store unit as the temporal set

and designed a Multi level indexed Distributed Hash Table (tDHT) algorithm to realize the retrieval for the temporal attribute value of temporal column quickly and efficiently. By mapping from temporal attribute value to the two-dimensional space

the conversion from temporal data to space object was achieved

the temporal data area was divided by using the processing method for spatial data

Multi level temporal data sub-areas were generated

and the Multi level indexed DHT directory was constructed

which was stored by HBase

using the methodology of DHT. The experiment results show that the index strategy can achieve a good performance

and it can be used to accelerate temporal data retrieval in the HBase table to a certain extent.