Research On Bitmap Index In Data Warehouse

Nowadays, data warehouse and OLAP technique have been widely used in various business enterprises. How to improve the inquiry efficiency in data warehouse environment is one of the core problems of current studies of data warehouse. Making use of the index technology is one of the important methods to improve query performance. Compared with B-tree index, bitmap index changes comparison, connection and integration into logic operations, which can reduce the operating time a lot in order to promote the performance greatly.In this thesis, we make a comparison of the existing bitmap encoding schemes. As for evaluating the membership query, this thesis presents the procedure of evaluating the membership query for all kinds of encoding schemes. Using Multi-Components index to evaluate the membership query ,there is a problem that scan the same bitmap more than once. In order to avoid this problem ,this thesis propose an efficient algorithm for membership query based on multi-component index.Bitmap index available is usually established in a certain single level, without considering the semantics characteristic that dimension attributes have the layers, this thesis presents a method to code for dimension members based on Ecoding Bitmap Index .Using the dimension layer code and the Query,we can get the retrieval Boolean function, then find the wanted tuples on the dimension layer code or its substring of every tuples in the fact table. So we convert a large number of multi-table connections in OLAP query into scope query in fact table, so as to reduce and simplify the multi-table connections between case table and dimension table significantly. Thereby,increasing the efficiency of the OLAP queries.