Optimizing entity join queries when data transmission cost dominates

Heterogeneities exist in a multidatabase environment. For example, a real world entity may be differently represented in relations of different databases. In particular, keys of these relations may be incompatible. In this paper, we consider processing entity join queries when data transmission cost...

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Bibliographic Details
Published inData & knowledge engineering Vol. 22; no. 3; pp. 283 - 308
Main Authors Tsai, Pauray S.M., Chen, Arbee L.P.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.05.1997
Subjects
Entity join
Extended semijoin
Inconsistent data
Local processing
Multidatabase
Query optimization
Query transformation
Selectivity
Inconsistent data
Multidatabase
Entity join
Local processing
Extended semijoin
Selectivity
Query transformation
Query optimization
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Summary:Heterogeneities exist in a multidatabase environment. For example, a real world entity may be differently represented in relations of different databases. In particular, keys of these relations may be incompatible. In this paper, we consider processing entity join queries when data transmission cost dominates. An entity join operation ‘integrates’ tuples representing the same entities from different relations in which inconsistent data may exist. A natural way to process the entity join is to transmit both relations to a site, resolve the possible conflicts between corresponding attributes and process the join, which is very costly. In this paper, an approach is proposed to correctly transform a global query into local subqueries to preprocess entity join queries in multiple sites with an attempt to lower the cost of data transmission. Besides, an extension of the traditional semijoin, named extended semijoin, is proposed to further reduce the cost of data transmission for entity join query processing.
ISSN:0169-023X
1872-6933
DOI:10.1016/S0169-023X(96)00052-3