Research On MOLAP Model And Key Algorithms

In order to support analysis of decisions, people have proposed the concept of data-warehouse. The data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection. Its main purpose is to support analysis of decisions. On line analysis processing (OLAP) is the most important application on the data warehouses. According to the difference of the forms of data organizations, there are two kinds of OLAP servers: ROLAP (relational OLAP) that is founded on the relational database and MOLAP (multi-dimensional OLAP), which is on the basis of multi-dimensional arrays. MOLAP supports multi-views and has high query performance that is attributed to its particular multi-dimensional data structure and aggregate data, which is pre-computed abundantly.This thesis explores the technology of the aggregate data of MOLAP and mainly concentrates on how to find out the optimal sequence of the multi-way array aggregation, how to store the data effectively and how to index and query the data. On the basis of our systematic research on the latest theory, the thesis makes several innovations and achievements, which will be illustrated in detail as follows.1. In this thesis, according to the defects of the sequence of the multi-way aggregation, we propose a new method to find out the optimal order, which can improve the rate of pre-computation.2. The dimensional information, which is stored in traditional way, would lead to the problem of the bad expansibility and difficulties with data update. We propose a kind of storage structure of dimensional data, which well solve this problem.3. Aggregate data are usually stored by multi-arrays, which lead to the lost of the dimension information and data hierarchy semantic information. The thesis proposes a kind of storage structure of Multi-dimensional data based on hierarchy, which well solve this problem.