An Efficient View Maintenance Algorithm for Data Warehousing

Data streams are continuous, rapid, time-varying, and transient streams of data and provide new opportunities for analysis of timely information. Data processing in data streams faces similar challenges as view management in data warehousing: continuous query processing is related to view maintenance in data warehousing, multi-query optimization for continuous queries is highly related to view selection in conventional relational DBMS and data warehouses. In this chapter, we give an overview of view maintenance and view selection methods, explain the fundamental issues of data stream management, and discuss how view management techniques from data warehousing are related to data stream management. We also give directions for future research in view management, data streams, and data warehousing.

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Data Warehousing Interoperability for the Extended Enterprise

Data Warehousing and Mining ◽

10.4018/978-1-59904-951-9.ch161 ◽

2008 ◽

pp. 2626-2636

Author(s):

Aristides Triantafillakis ◽

Panagiotis Kanellis ◽

Drakoulis Martakos

Keyword(s):

Data Warehouse ◽

Business Process ◽

Information Quality ◽

Data Warehousing ◽

Special Kind ◽

View Maintenance ◽

Collaborative Environments ◽

Web Based ◽

Empirical Results ◽

Materialized View

The purpose of this paper is to raise awareness and identify a number of challenges regarding the issue of data warehouse interoperation in Web-based collaborative environments. Adopting system and information quality as success variables, we argue that existing works fell short of addressing complex issues that relate to their refreshment and extent far beyond view maintenance solutions within single warehouses. Considering a solution that approaches warehouse refreshment as a business process in a federation of data warehouses, we define a special kind of materialized view that emanates from such an environment, provide a roadmap for implementing the appropriate warehousing architecture, and give some preliminary empirical results.

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Triggers, Rules and Constraints in Databases

Encyclopedia of Information Science and Technology, First Edition ◽

10.4018/978-1-59140-553-5.ch512 ◽

2005 ◽

pp. 2878-2881

Author(s):

Juan M. Ale ◽

Mauricio Minuto Espil

Keyword(s):

Web Applications ◽

Data Warehousing ◽

Integrity Constraints ◽

Data Sampling ◽

View Maintenance ◽

Server Side ◽

Materialized View ◽

Reactive Behavior ◽

Action Model ◽

Client Side

Databases are essentially large repositories of data. Since the mid-1980s up to the mid-1990s, considerable effort has been paid to incorporate reactive behavior to the data management facilities available. Reactive behavior is characterized by variants of the event–condition–action model. Applications areas include checking for integrity constraints, system alerts, materialized view maintenance (especially useful in data warehousing), replication of data for audit purposes, data sampling, workflow processing, implementation of business rules, scheduling, and many others. Practically all products offered today in the database marketplace support complex reactive behavior on the client side. Nevertheless, the reactive behavior supported by those products on the server side is poor. Recently, the topic has regained attention because of the inherent reactive nature demanded in Web applications and the necessity of migrating many of the functionalities of browsers to active Web servers (Bonifati, Braga, Campi, & Ceri, 2002).

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View Management Techniques and Their Application to Data Stream Management

Evolving Application Domains of Data Warehousing and Mining ◽

10.4018/978-1-60566-816-1.ch005 ◽

2010 ◽

pp. 83-112 ◽

Cited By ~ 2

Author(s):

Christoph Quix ◽

Xiang Li ◽

David Kensche ◽

Sandra Geisler

Keyword(s):

Data Streams ◽

Data Stream ◽

Data Warehousing ◽

Future Research ◽

View Maintenance ◽

Data Stream Management ◽

View Selection ◽

Stream Management ◽

Management Techniques ◽

View Management

Data streams are continuous, rapid, time-varying, and transient streams of data and provide new opportunities for analysis of timely information. Data processing in data streams faces similar challenges as view management in data warehousing: continuous query processing is related to view maintenance in data warehousing, multi-query optimization for continuous queries is highly related to view selection in conventional relational DBMS and data warehouses. In this chapter, we give an overview of view maintenance and view selection methods, explain the fundamental issues of data stream management, and discuss how view management techniques from data warehousing are related to data stream management. We also give directions for future research in view management, data streams, and data warehousing.

Download Full-text