The Opsis project: materialized views for data warehouses and the web (original) (raw)
Related papers
A Comprehensive Analysis of Materialized Views in a Data Warehouse Environment
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.
Efficient materialization and use of views in data warehouses
ACM SIGMOD Record, 1999
Given the complexity of many queries over a Data Warehouse (DW), it is interesting to precompute and store in the DW the answer sets of some demanding operations, so called materialized views. In this paper, we present an algorithm, including its experimental evaluation, which ...
Using Relational Database Constraints to Design Materialized Views in Data Warehouses
Lecture Notes in Computer Science, 2004
Queries to data warehouses often involve hundreds of complex aggregations over large volumes of data, and so it is infeasible to compute these queries by scanning the data sources each time. Data warehouses therefore build a large number of materialized views to increase system performance. However, materialized views need to be immediately updated when its sources are changed, leading to a possible decrease in system performance. The goal of the materialized view selection problem is to select an appropriate set of views that minimize total query response time as well as the view maintenance cost. In this paper, we develop a solution for identifying the candidate view space of materialization. In particular, we present algorithms for generating a unionview and a partial-view, both of which are good candidates for materialization. The proposed candidate view space guarantees to find a polynomial bounded set of optimal views, and any selection algorithm from previous research, e.g. greedy algorithm, can be ran on the candidate view space to find the optimal materialized views.
OLAP, Data Warehousing, and Materialized Views: a Survey
1998
This report aims to give a comprehensive introduction to the subjects of Data Warehousing and OLAP. It also gives an overview of the related topic of Materialized Views. Materialized Views become important when trying to improve the performance of an OLAP system. The main intention is to describe the state of the art in these fields in order to identify research opportunities. Topics covered here are: architecture, design, querying, optimization and implementation. Relevant research papers are commented, and some commercial products reviewed, mainly to remark their differences. ROLAP and MOLAP are also analyzed and, finally, an extensive bibliography is presented in the references.
Algorithms for Materialized View Design in Data Warehousing Environment
1997
Selecting views to materialize is one of the most important decisions in designing a data warehouse. In this paper, we present a framework for analyzing the issues in selecting views to materialize so as to achieve the best combination of good query performance and low view maintenance. We first develop a heuristic algorithm which can provide a feasible solution based on individual optimal query plans. We also map the materialized view design problem as O-l integer programming problem, whose solution can guarantee an optimal solution.
Assortment of Materialized View: A Comparative Survey in Data Warehouse Environment
International Journal of Computer Applications, 2014
Data warehouse is a repository of large amount of data collected from multiple heterogeneous and distributed data sources. Data warehouse stores lots of data in the form of views, referred as materialized views which provide a base for decision support or OLAP queries. Materialized views store the result of queries which improves the query performance. One of the most important aspect in data warehousing is the selection of materialized views which minimizes the query response time and maintenance cost, given a limited storage space. In this paper, analysis of various approaches of view selection in data warehousing environment is done that have been proposed in the recent past and also provided a comprehensive study of these approaches based on various parameters such as issues addressed, query language supported, comparison to benchmark etc.
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/cluster-based-framework-for-selection-of-materialized-views-to-reduce-the-execution-time-and-storage-space https://www.ijert.org/research/cluster-based-framework-for-selection-of-materialized-views-to-reduce-the-execution-time-and-storage-space-IJERTV1IS6050.pdf Data warehouse have been developed to overcome the weakness of traditional databases. A DW is a repository of information collected from multiple, possibly very large, distributed, heterogeneous, autonomous databases and other information sources. It is a set of materialized views defined over remote source relations. It uses multiple materialized views to efficiently process a given set of queries. The DWs are dynamic entities that evolve continuously over time. As time passes, new queries need to be answered by them. Some of these queries can be answered using exclusively the materialized views. When a query is posed, it is evaluated locally, using the materialized views, without accessing the original information sources. It is highly probable that a user will issue a series of similar queries until he or she receives satisfying results. In general new views need to be added to the DW.
A Solution to View Management to Build a Data Warehouse
2009
Several techniques exist to select and materialize a proper set of data in a suitable structure that manage the queries submitted to the online analytical processing systems. These techniques are called view management techniques, which consist of three research areas: 1) view selection to materialize, 2) query processing and rewriting using the materialized views, and 3) maintaining materialized views. There are several parameters should be considered in order to find the most important algorithm for view management. As various researches have been done to propose view selection algorithms, we should select and modify the most suitable algorithm for view materialization based on the properties of the applications. In this paper, we investigate and find relevant parameters to view selection algorithms and classify them based on these parameters. We also present a system to evaluate algorithms and compare them with respect to the values of the evaluation parameters. Based on the results of these activities, we propose a roadmap that helps us choose the most efficient view selection algorithm concerning application types.
Multi-source Materialized Views Maintenance: Multi-level Views
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.
Data warehouse enhancement manipulating materialized view hierarchy
Eighth International Conference on Digital Information Management (ICDIM 2013), 2013
Materialized Views usually used in distributed databases for replication and can also be used for well-organized delivery of data to a querying process. The process of data delivery to queries can further be accelerated if materialized views hierarchy is introduced to the existing materialized view. The newly generated sub views of the existing materialized views forms a materialized views hierarchy consists of parents and newly generated sub materialized views. The newly generated sub materialized views are dependent over the existing materialized views. Besides, these newly generated views are automatically created upon the creation of the parent materialized with some restrictions. This reduces the user dependency due to creation of materialized views based on some parameters. These parameters include the number of newly generated materialized views and the type of the data a view contain. In this paper, a stable approach is suggested to create newly generated materialized views to answer user queries without consulting the parent materialized view that requires no complex calculations and joining of multiple tables.