Tabular-oriented data model and its query issues

With the rapid development of information technologies, data storage and representation of various sources, including not only the traditional structured data such as relational databases and object-oriented databases, but also those special unstructured data like Excel, CSV documents, manifest distributed and heterogeneous characteristics. Undoubtedly, all above data features high-volume, continuously-updating, low-usability, which falls into Big Data. However, the organization and management of Excel and other forms of data by using unstructured and semi-structured methods leads to a weakly-controllable, weakly-usable data structure with poor access efficiency. To solve this problem, this paper, taking Excel data source into consideration, aims to propose a new tabular-oriented relational data model and discusses Tabular querying and optimizing issues. Firstly, the formal definition of Tabular form data is given; secondly, PartiPath tree is designed to achieve structural transformation by tabular division and its relation schema as well; then its data model is presented. After that, four basic queries and their optimization by improved DICE with user interest similarity are described. Finally, the experiment was conducted and a conclusion was drawm.