A Novel Aggregation Algorithm for Online Analytical Processing Queries Evaluation Based on Dimension Hierarchical Encoding

The OLAP （online analytical processing） queries are ad hoc complex aggregation queries on the massive data set These queries include multi table join and aggregation operation in their SQL clauses As a result, how to reduce multi table join, compress the key word and effectively aggregate the query data becomes the key issue for ROLAP（relational OLAP）query evaluation To solve this problem, a novel pre grouping aggregation algorithm DHEPGA（pre grouping aggregation based on the dimension hierarchical encoding） is proposed in this paper By using the small dimension hierarchical encoding and its hierarchical prefix path, DHEPGA can rapidly retrieve the matching dimension hierarchical encoding and evaluate the set of query ranges for each dimension As a result, this algorithm can greatly reduce the disk I/Os and highly improve the efficiency of OLAP queries The analytical and experimental results show that the DHEPGA algorithm proposed is more efficient than other existing ones