Clio: a semi-automatic tool for schema mapping
Clio: a semi-automatic tool for schema mapping
复制标题
Clio：用于模式映射的半自动工具
DOI：
10.1145/375663.375767
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
L. Haas
中科院分区：
文献类型：
--
作者：
Mauricio A. Hernández;Renée J. Miller;L. Haas
我们考虑现代数据密集型应用程序的集成要求，包括数据仓库、全球信息系统和电子商务。这些要求的核心在于模式映射问题，其中源（遗留）数据库必须映射到不同但固定的目标模式。模式映射的目标是发现一个查询或一组查询，以将源数据库映射到新结构。我们演示了 Clio，这是一种用于创建模式映射的新半自动化工具。 Clio 采用示例映射范例，该范例依赖于值对应关系的使用，描述如何从一组源属性值创建目标属性值。与 Clio 的典型会话从用户将源模式和目标模式加载到系统中开始。这些模式是从底层对象关系数据库或具有关联 XML 模式的 XML 文件中读取的。然后，用户可以绘制将源属性映射到目标属性的值对应关系。 Clio 的映射引擎增量地生成 SQL 查询，这些查询实现了对应关系所隐含的映射。 Clio 提供模式和数据浏览器以及其他反馈，以允许用户了解生成的映射。输入和操作值对应关系可以通过两种模式完成。在架构视图模式中，用户可以查看源架构和目标架构的表示，并通过从源中选择架构对象并将其映射到目标属性来创建值对应关系。另一种数据视图模式为映射过程提供所见即所得界面，显示源表和目标表的示例数据 [3]。用户可以在此视图中添加和删除值对应关系，并立即看到结果目标元组中反映的更改。此外，数据视图模式还可以帮助用户浏览替代映射，了解它们之间通常存在的细微差异。例如，在某些情况下，将连接从内连接更改为外连接可能会显着改变结果表。在其他情况下，由于源上的限制，相同的更改可能不会产生任何影响
We consider the integration requirements of modern data intensive applications including data warehousing, global information systems and electronic commerce. At the heart of these requirements lies the schema mapping problem in which a source (legacy) database must be mapped into a different, but xed, target schema. The goal of schema mapping is the discovery of a query or set of queries to map source databases into the new structure. We demonstrate Clio, a new semi-automated tool for creating schema mappings. Clio employs a mapping-by-example paradigm that relies on the use of value correspondences describing how a value of a target attribute can be created from a set of values of source attributes. A typical session with Clio starts with the user loading a source and a target schema into the system. These schemas are read from either an underlying Object-Relational database or from an XML le with an associated XML Schema. Users can then draw value correspondences mapping source attributes into target attributes. Clio's mapping engine incrementally produces the SQL queries that realize the mappings implied by the correspondences. Clio provides schema and data browsers and other feedback to allow users to understand the mapping produced. Entering and manipulating value correspondences can be done in two modes. In the Schema View mode, users see a representation of the source and target schema and create value correspondences by selecting schema objects from the source and mapping them to a target attribute. The alternative Data View mode o ers a WYSIWYG interface for the mapping process that displays example data for both the source and target tables [3]. Users may add and delete value correspondences from this view and immediately see the changes re ected in the resulting target tuples. Also, the Data View mode helps users navigate through alternative mappings, understanding the often subtle di erences between them. For example, in some cases, changing a join from an inner join to an outer join may dramatically change the resulting table. In other cases, the same change may have no e ect due to constraints that hold on the source