Efficient Maintenance of Materialized Outer-Join Views

Information Systems, 2012

The VLDB Journal, 2006

Prior work on computing queries from materialized views has focused on views defined by expressions consisting of selection, projection, and inner joins, with an optional aggregation on top (SPJG views). This paper provides the first view matching algorithm for views that may also contain outer joins (SPOJG views). The algorithm relies on a normal form for SPOJ expressions and does not use bottomup syntactic matching of expressions. It handles any combination of inner and outer joins, deals correctly with SQL bag semantics and exploits not-null constraints, uniqueness constraints and foreign key constraints.

Second, the most critical issues related to maintaining the materialized view and the effective query maintenance strategy are also discussed along with comparison between all the discussed systems.

2005

In a data warehouse system, maintaining materialized views can speed up query processing. These views need to be maintained in response to updates in the base relations. This is often done for reasons of data currency, using incremental techniques rather than re-computing the view from scratch. However, when the data source changes, the views in the warehouse can become inconsistent with the base data. Thus, maintenance of materialized views in the warehouse consistent with the base relations is a challenging task. In this paper, we propose an approach to maintain a materialized view without accessing the base relations by materializing and maintaining additional relations, known as auxiliary relations. In our approach, these auxiliary relations are derived based on the functional dependencies that hold on base relations, materialized view, and the key participation of the base relations in the materialized view. This approach helps in reducing the storage space and improves the efficiency of view maintenance. We present an algorithm to derive those auxiliary relations and determine which auxiliary relations need to be materialized in order to maintain a materialized view incrementally. We also present the cost model that enables the evaluation of the total cost and benefit involved in materializing auxiliary relations.

Lecture Notes in Computer Science, 2006

In many information systems, the databases that make up the system are distributed in different modules or branch offices according to the requirements of the business enterprise. In these systems, it is often necessary to combine the information of all the organization's databases in order to perform analysis and make decisions about the global operation. This is the case of Data Warehouse Systems. From a conceptual point of view, a Data Warehouse can be considered as a set of materialized views which are defined in terms of the tables stored in one or more databases. These materialized views store historical data that must be maintained in either real time or periodically by means of batch processes. During the maintenance process the systems must perform selections, projections, joins, etc. that can affect several databases. This is a complex problem since making a join among several tables requires (at least temporarily) having the information from these tables in the same place. This requires the Data Warehouse to store auxiliary materialized views that in many cases contain duplicated information. In this article, we study this problem, and we propose a method that minimizes the duplicated information in the auxiliary materialized views and also reduces the response time of the system.

1996

A data warehouse stores materialized views over data from one or more sources in order to provide fast access to the integrated data, regardless of the availability of the data sources. Warehouse views need to be maintained in response to changes to the base data in the sources. Except for very simple views, maintaining a warehouse view requires access to data that is not available in the view itself. Hence, to maintain the view, one either has to query the data sources or store auxiliary data in the warehouse. We show that by using key and referential integrity constraints, we often can maintain a select-project-join view when there are insertions, deletions, and updates to the base relations without going to the data sources or replicating the base relations in their entirety in the warehouse. We derive a set of auxiliary views such that the warehouse view and the auxiliary views together are self-maintainable|they can be maintained without going to the data sources or replicating all base data. In addition, our technique can be applied to simplify traditional materialized view maintenance by exploiting key and referential integrity constraints.

International Journal of Computer Science & Engineering Survey, 2010

Quick response time and accuracy are important factors in the success of any database. In large databases particularly in distributed database, query response time plays an important role as timely access to information and it is the basic requirement of successful business application. A data warehouse uses multiple materialized views to efficiently process a given set of queries. The materialization of all views is not possible because of the space constraint and maintenance cost constraint. Materialized views selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key component in data warehousing. Materialized views are found useful for fast query processing. This paper gives an overview of various techniques that are implemented in past recent for selection of materialized view. The issues related to maintaining the materialized view are also discussed in this paper. Here some future aspects are also stated that might be useful for recent researchers.

2014

A data warehouse is a large data repository for the purpose of analysis and decision making in organizations. To improve the query performance and to get fast access to the data, data is stored as materialized views (MV) in the data warehouse. When data at source gets updated, the materialized views also need to be updated. In this paper, we focus on the problem of maintenance of these materialized views and address the issue of finding such auxiliary views (AV) that together with the materialized views make the data self-maintainable and take minimal space. We propose an algorithm that uses key and referential constraints which reduces the total number of tuples in auxiliary views and uses idea of information sharing between these auxiliary views to further reduce number of auxiliary views.

International Journal of Advanced Computer Science and Applications, 2011

Data in a warehouse can be perceived as a collection of materialized views that are generated as per the user requirements specified in the queries being generated against the information contained in the warehouse. User requirements and constraints frequently change over time, which may evolve data and view definitions stored in a data warehouse dynamically. The current requirements are modified and some novel and innovative requirements are added in order to deal with the latest business scenarios. In fact, data preserved in a warehouse along with these materialized views must also be updated and maintained so that they can deal with the changes in data sources as well as the requirements stated by the users. Selection and maintenance of these views is one of the vital tasks in a data warehousing environment in order to provide optimal efficiency by reducing the query response time, query processing and maintenance costs as well. Another major issue related to materialized views is that whether these views should be recomputed for every change in the definition or base relations, or they should be adapted incrementally from existing views. In this paper, we have examined several ways o performing changes in materialized views their selection and maintenance in data warehousing environments. We have also provided a comprehensive study on research works of different authors on various parameters and presented the same in a tabular manner.

IEEE Data(base) Engineering Bulletin, 1995