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中文摘要：
为解决传统行存储结构导致OLAP聚集计算效率低下的问题，设计了基于维存储的OLAP数据存取技术．首先，将OLAP事实表中的维属性集和度量属性集定义为2个列族，每张维表的所有属性定义为1个列族．对维表进行二进制编码，生成维层次编码，从而保持了维的层次语义特性．以（维层次编码，度量值）对形式按列组织数据，消除查询时维表与事实表的复杂连接操作运算．然后，采用自底向上方法构建B＋树，对维层次编码进行索引，加快了数据读取效率．通过增删事实表和维层次编码一度量表中相应的列，实现维和度量的增加和删除．性能分析结果表明，这种OLAP数据存取技术具有良好的可扩展性，能高效地管理和存取OLAP海量多维数据，有效支持上层OLAP聚集计算．
英文摘要：
To improve the efficiency of OLAP（ online analytical processing） aggregation in tradition- al row-stores, a dimension-stores based OLAP data access technology is designed. First, the dimen- sion attributes and measure attributes of the OLAP fact table are defined as two column families, and all attributes in a dimension table are defined as one column family. Dimension tables are encoded by using binary digit to generate dimension hierarchy codes, and thus the hierarchy semantics of dimen- sion is maintained. The data are organized as （dimension hierarchy code, measure value） to elimi- nate the complex join operations between dimension tables and fact table in query. Then, a B ＋ tree index is bottom-up built to index the dimension hierarchy codes, which accelerates the data access efficiency. Adding and deleting the corresponding columns in fact table and dimension hierarchy code-measure tables can realize the addition and deletion of dimensions and measures. The performance analysis results show that this OLAP data access technology has good expandability. It can effi- ciently manage and access massive OLAP multidimensional data, and effectively supports the upper OLAP aggregation.
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