In this paper we present a new family of Intensional RDBs (IRDBs) which extends the traditional RDBs with the Big Data and flexible and 'Open schema' features, able to preserve the user-defined relational database schemas and all preexisting user's applications containing the SQL statements for a deployment of such a relational data. The standard RDB data is parsed into an internal vector key/value relation, so that we obtain a column representation of data used in Big Data applications, covering the key/value and column-based Big Data applications as well, into a unifying RDB framework. We define a query rewriting algorithm, based on the GAV Data Integration methods, so that each user-defined SQL query is rewritten into a SQL query over this vector relation, and hence the user-defined standard RDB schema is maintained as an empty global schema for the RDB schema modeling of data and as the SQL interface to stored vector relation. Such an IRDB architecture is adequate for the massive migrations from the existing slow RDBMSs into this new family of fast IRDBMSs by offering a Big Data and new flexible schema features as well.
翻译:在本文中,我们展示了一个新的强化 RDB (IRDBs) 组合,它将传统的 RDB 与大数据、灵活和“开放方程” 功能相扩展,将传统的 RDB 与大数据、灵活和“开放方程” 功能相扩展,能够保存用户定义的关系数据库系统图案以及包含SQL 报表的先前所有用户应用程序,用于部署这种关系数据的 SQL 。标准 RDB 数据被分割成一个内部矢量键/价值关系,以便我们获得大数据应用程序中所使用的数据的一列表示,涵盖关键/价值和基于列的大数据应用程序,并形成一个统一的 RDB 框架。我们根据GAV 数据整合方法定义了查询重写算法,这样,每个用户定义的 SQL 查询将重新写成关于此矢量数据的 SQL 查询,因此,用户定义的标准 RDB Schema 被维持为用于 RDB 数据模型建模的空全球系统图案和存储矢量关系S 的 SQL 接口。这种IRDBBB 结构足以用于从现有的慢点RDBMS 和新家庭功能提供快速数据的软化数据。