Online, Non-blocking Relational Schema Changes

2006 ◽  
pp. 405-422 ◽  
Author(s):  
Jørgen Løland ◽  
Svein-Olaf Hvasshovd
Keyword(s):  
Relational Schema

Schema Evolution in Multiversion Data Warehouses

2021 ◽  
Vol 17 (4) ◽  
pp. 1-28
Author(s):  
Waqas Ahmed ◽  
Esteban Zimányi ◽  
Alejandro A. Vaisman ◽  
Robert Wrembel
Keyword(s):  
Efficient Solution ◽  
Business Processes ◽  
Online Analytical Processing ◽  
User Requirements ◽  
Schema Evolution ◽  
Data Warehouses ◽  
Relational Schema ◽  
External Sources ◽  
Analytical Processing

Data warehouses (DWs) evolve in both their content and schema due to changes of user requirements, business processes, or external sources to name a few. Although multiple approaches using temporal and/or multiversion DWs have been proposed to handle these changes, an efficient solution for this problem is still lacking. The authors' approach is to separate concerns and use temporal DWs to deal with content changes, and multiversion DWs to deal with schema changes. To address the former, previously, they have proposed a temporal multidimensional (MD) model. In this paper, they propose a multiversion MD model for schema evolution to tackle the latter problem. The two models complement each other and allow managing both content and schema evolution. In this paper, the semantics of schema modification operators (SMOs) to derive various schema versions are given. It is also shown how online analytical processing (OLAP) operations like roll-up work on the model. Finally, the mapping from the multiversion MD model to a relational schema is given along with OLAP operations in standard SQL.

A method of expressing associated semanteme of entities

2021 ◽  
Author(s):  
Wei Lijun ◽  
Pan Yang ◽  
Wang Hao ◽  
Wang Xianchao ◽  
Zhang Yan
Keyword(s):  
Linked Data ◽  
Relational Databases ◽  
Relational Schema ◽  
Formal Expression ◽  
The Rich ◽  
Relationship Of

To make up for the defects of semanteme expression about linked data, this paper proposes a semanteme expressing method of associated entities based on relationship diagram so as to realize the machine expression and recognition of associated semanteme in relational databases. Starting with the structure and relationship of relational schema, this paper analyzes the rich semanteme of associated entities and presents the semanteme parsing method based on the traversal path as well as its formal expression; the analysis of instance database is also carried out. Studies show that this method can comprehensively parse and express the associated semanteme of entities. This work has reference significance for the research of intelligent semanteme synthesis and for semanteme-oriented intelligent query.

Mapping Class Diagrams to Relational Schemas

2011 ◽  
pp. 103-123
Author(s):  
Peretz Shoval
Keyword(s):  
Mapping Class ◽  
Class Diagram ◽  
Relational Schema ◽  
Relational Schemas ◽  
Mapping Rules ◽  
Mapping Process ◽  
Class Diagrams

This chapter first explains the need to map a class diagram to a relational schema. Then, most of the chapter is dedicated to presenting and demonstrating the mapping rules based on which a relational schema (made of normalized relations) is created. The mapping process is demonstrated with several comprehensive examples.

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