The EVE approach: view synchronization in dynamic distributed environments

Lee, A.J.; Nica, Anisoara; Rundensteiner, Elke A.

doi:10.1109/tkde.2002.1033766

Cited by 40 publications

(28 citation statements)

References 25 publications

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“…The rules can be based upon mathematical models of the relational algebra expression and heuristics, upon cost approximates of different algorithms or techniques applied to operations or upon the semantics within the query and the relations it necessitates [4] [5]. Selecting the absolute rules to apply, when to apply them and how they are applied is the function of the query optimization engine.…”

Section: Query Flowmentioning

confidence: 99%

An Approach for Query Optimization by using Schema Object Base View

Patel¹,

Patel²

2015

IJCA

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Mining of Data is the extraction of hidden prognosticative information from large databases or set of data, is a strong new technology with great prospective to help companies focus on the most important information in their data base. Query optimization is a purpose of many relational database management systems. The query optimizer experiments to dictate the most efficient way to implement a given query by examining the possible query plans. There are different techniques is given for optimizing query using schema based and materialized views in data base namely-Query Graph, Tableaus, Optimization of Queries having Aggregates. In this paper we are using Different query optimization parameter and create an effective approach by using this approach we are reduce query execution cost, query space and more effectible for the query.The complexity of Queries severely increase the execution cost of the queries and have a critical effect on performance and productivity of decision support systems. It is required to perform expensive join and aggregation operations frequently on the databases. Now if they are not pre calculated in advanced then it leads to reduce query performance. Schema object improve query performance by pre calculating expensive join and aggregation operations on the database prior to execution and storing the results in the database. Schema object define not only relationships, but also allow you to recompute expensive joins and aggregations which lead to optimized query performance in possible ways. Schema object leads to the decrease Query processing cost and Query Maintenance cost in terms of Time factor. Schema object improve query performance by pre calculating expensive join and aggregation operations on the database prior to execution and storing the results in the database. The big advantage of a Schema object based views is extremely fast retrieval of aggregate data, since it is precomputed and stored, at the expense of insert/update/delete so that it increase query performance than the ordinary view and table. Schema object based view is also called Materialized view.

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Section: Query Flowmentioning

confidence: 99%

An Approach for Query Optimization by using Schema Object Base View

Patel¹,

Patel²

2015

IJCA

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“…It addresses both equivalent & non-equivalent view re-definitions [3]. Some of the changes that result in creation of new schema definitions are as follow [3]: EVE (Evolvable View Environment), a general framework has been developed in [4] to handle view synchronization in large distributed dynamic environments like-WWW. A view definition language, E-SQL, has also been designed along with some replacement strategies to propagate the changes in affected view components.…”

Section: Schema Changes Descriptionmentioning

confidence: 99%

A Comprehensive Analysis of Materialized Views in a Data Warehouse Environment

Thakur¹,

Gosain²

2011

IJACSA

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Abstract-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.

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“…In our approach, we do not ask users to specify a sequence of transformations. The EVE [21] investigates the view synchronization problem, which supports a limited set of changes. The work in [14] describes techniques for maintaining mapping in XML p2p databases which is different from our problem.…”

Section: Related Workmentioning

confidence: 99%

Round-Trip Engineering for Maintaining Conceptual-Relational Mappings

Song

2008

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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Abstract. Conceptual-relational mappings between conceptual models and relational schemas have been used increasingly to achieve interoperability or overcome impedance mismatch in modern data-centric applications. However, both schemas and conceptual models evolve over time to accommodate new information needs. When the conceptual model (CM) or the schema associated with a mapping evolved, the mapping needs to be updated to reflect the new semantics in the CM/schema. In this paper, we propose a round-trip engineering solution which essentially synchronizes models by keeping them consistent for maintaining conceptualrelational mappings. First, we define the consistency of a conceptualrelational mapping through "semantically compatible" instances. Next, we carefully analyze the knowledge encoded in the standard database design process and develop round-trip algorithms for maintaining the consistency of conceptual-relational mappings under evolution. Finally, we conduct a comprehensive set of experiments. The results show that our solution is efficient and provides significant benefits in comparison to the mapping reconstructing approach.

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The EVE approach: view synchronization in dynamic distributed environments

Cited by 40 publications

References 25 publications

An Approach for Query Optimization by using Schema Object Base View

An Approach for Query Optimization by using Schema Object Base View

A Comprehensive Analysis of Materialized Views in a Data Warehouse Environment

Round-Trip Engineering for Maintaining Conceptual-Relational Mappings

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