Big data refers to the enormous heterogeneous being produced at a brisk pace by large number of diverse generating sources. Since traditional processing technologies are unable process big efficiently, is processed using newer distributed storage and frameworks. view materialization technique queries efficiently on these It generates valuable information, which can be used take timely decisions...

View materialization is a well-known optimization technique of relational database systems. In this work we present a similar, yet more powerful optimization concept for object-oriented data models: function materialization. Exploiting the object-oriented paradigm|namely classi cation, object identity , and encapsulation|facilitates a rather easy incorporation of function materialization into (...

For a company with many databases in different data models, it is necessary to consolidate them into one data model interchangeable and present data in one data model concurrently to users. The benefit is to let user stick to his/her own data model to access database in another data model. This paper presents a semantic metadata to preserve database constraints for data materialization to suppo...

Deening a view over a semistructured database introduces many new problems. In this paper we propose a view speciication language and consider the problem of answering queries posed over views. The two main approaches, query rewriting and view materialization, are outlined with focus on the diicult problems caused by the semistructured nature of the data.

View materialization has been shown to ameliorate the scalability problem of data-intensiveweb servers. However, unlike data warehouses which are off-line during updates, most web servers maintain their back-end databases online and perform updates concurrently with user accesses. In such environments, the selection of views to materialize must be performed online; both performance and data fre...

De ning a view over a semistructured database introduces many new problems. In this paper we propose a view speci cation language and consider the problem of answering queries posed over views. The two main approaches, query rewriting and view materialization, are outlined with focus on the di cult problems caused by the semistructured nature of the data.

Abstract In this paper, we present extensions to the MultiView object-oriented database view system that improve its ability to integrate electronic computer-aided design (ECAD) tools. Using an object-preserving algebra as the view definition language, the MultiView system supports data transformations to suit the needs of individual tools. However, an object-preserving algebra alone is not pow...

Since a data warehouse deals with huge amounts of data and complex analytical queries, online processing and answering to users’ queries in data warehouses can be a serious challenge. Materialized views are used to speed up query processing rather than direct access to the database in on-line analytical processing. Since the large number and high volume of views prevents all of the views from b...

Database systems have been driving dynamic websites since the early 1990s; nowadays, even seemingly static websites employ a database back-end for personalization and advertising purposes. In order to keep up with the high demand fuelled by the rapid growth of the Internet, a number of caching and materialization techniques have been proposed for web databases over the years. The main goal of t...

We introduce an approach to view materialization which is based on relational reformulation. In this context, we present a method for automatically discovering views of the stored relations that are not already deened yet present valuable opportunities for materialization. The proposed reformu-lation algorithm works oo-line and consists of two stages. At the rst stage, Datalog rules relevant to...