Research of compress storage technique for C-TRDM

In this article, we introduce C-temporal relation data model (C-TRDM), and analyze data redundancy of tradition database and temporal database in existence. For the quantities of temporal database are increasing fleetly, we put forward compress storage tactics for temporal data which combine compress technology in existence in order to settle data redundancy in the course of temporal data storage and temporal data of slow acting domain and momentary acting domain are accessed by using each from independence clock method and mutual clock. We also bring forward strategy of gridding storage to resolve the problems of temporal datum rising rapidly.

1. Introduction

In the era of information, temporal database are in existence everywhere in human being's life, such as economy, finance, communication, weather…etc. Temporal Database [1](TDB) aims at managing history data. There is a great deal of redundancy in the database while new data gets into database constantly and constantly along with the passage in time. Efficiently data-storage and flexible index mechanism for temporal data must be introduced in order to ensure the time-space efficiency in dealing with a great deal temporal data. Operation of choice, projection and link are main temporal data query in actual application. Optimizing for temporal data query focuses on choice, projection and link of temporal data. Storage of temporal data is the key to solve it. It is important for us to research compress storage technique of temporal relation data model.