137 research outputs found

    From ternary relationship to relational tables: a case against common beliefs

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    The transformation from n-ary relationships to a relational database schema has never been really fully analyzed. This paper presents one of the several ternary cases ignored by the ER-to-RM literature. The case shows that the following common belief is wrong: Given a set of FDs over a table resulting in a non-3NF situation, it is always possible to obtain a fully equivalent set of 3NF tables, without adding other restrictions than candidate keys and inclusion dependencies.Postprint (published version

    A Logical Design Methodology for Relational Databases Using the Extended ER Model

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    https://deepblue.lib.umich.edu/bitstream/2027.42/154152/1/39015099114723.pd

    Issues and Guidelines in Modeling Decomposition of Minimum Participation in Entity-Relationship Diagrams

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    The entity-relationship model has long been employed for conceptual modeling of databases. Methodologies and heuristics have been developed, both for effective modeling and for translating entity-relationship models into relational models. One aspect of modeling that is often overlooked in design methodologies is the use of optional versus mandatory participation (i.e., minimum participation) on the development of relational databases. This tutorial complements existing instructional material on database design by analyzing the syntactic implications of minimum participation in binary, unary, and n-ary relationship sets and for the special case where the E-R diagram depicts a database where 3NF is not in BCNF. It then presents design modeling guidelines which demonstrate that (1) for binary 1:1 and 1:M relationship sets, the presence of optional participation sometimes means that the relationship set should be represented in the relational model by a separate relation, (2) unary relationship sets cannot have a (1,1) participation, (3) n-ary relationship sets that have a (1,1) participation can be simplified to be of lower connectivity, and (4) decomposition is not a substitute for normalization. Illustrative examples and modeling guidelines are provided

    Normalizing Relations: One-to-One Relationships

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    This paper discusses problems and confusion that can arise in normalizing certain relations, using the commonly accepted practices of identifying primary keys and defining normal forms. Specifically, normalization of relations that combines information on two different entities with a one-to-one relationship is discussed. It is shown that for such relations, using the standard normalization procedures may lead to the conclusion that a relation in Boyce-Codd normal form (BCNF) still suffers from insertion and deletion anomalies. Methods to deal with such cases are presented

    Transforming N-ary relationships to database schemas: an old and forgotten problem

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    The N-ary relationships, have been traditionally a source of confusion and still are. One important source of confusion is that the term cardinality in a relationship has several interpretations, two of them being very popular. But none of the two approaches, nor the two together, allow us to express all the possible cardinality patterns. The transformations from all the possible relationships to database schemas have never been described by the existing literature. Using the 14 ternary patterns as example, we discuss these transformations particularly the transformations from the patterns ignored in the literature.Postprint (published version

    Fundamentals and applications of order dependencies

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    Business-intelligence queries often involve SQL functions and algebraic expressions. There can be clear semantic relationships between a column's values and the values of a function over that column. A common property is monotonicity: as the column's values ascend, so do the function's values (or the other column's values). This we call an order dependency (OD). Queries can be evaluated more efficiently when the query optimizer uses order dependencies. They can be run even faster when the optimizer can also reason over known ODs to infer new ones. Order dependencies can be declared as integrity constraints, and they can be detected automatically for many types of SQL functions and algebraic expressions. We present optimization techniques using ODs for queries that involve join, order by, group by, partition by, and distinct. Essentially, ODs can further exploit interesting orders to eliminate or simplify potentially expensive sorts in the query plan. We evaluate these techniques over our prototype implementation in IBM® DB2® using the TPC-DS® benchmark schema and some customer inspired queries. Our experimental results demonstrate a significant performance gain. Dependencies have played an important role in database theory. We study the theoretical aspects of order dependencies-and unidirectional order dependencies (UODs), a proper sub-class of ODs-which describe the relationships among lexicographical orderings of sets of tuples. We investigate the inference problem for order dependencies. We establish the following: (i) a sound and complete axiomatization for UODs which is sound for ODs; (ii) a hierarchy of order dependency classes; (iii) a proof of co-NP-completeness of the inference problem for ODs and for the subclass of UODs; (iv) a proof of co-NP-completeness of the inference problem of functional dependencies (FDs) from ODs in general, but demonstrate linear time complexity for the inference of FDs from UODs; (v) a sound and complete elimination procedure for testing logical implication over ODs; and (vi) a sound and complete polynomial inference algorithm for sets of UODs over natural domains

    A SQL front-end semantic data model

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    SQLSDM is a front end semantic data model to a SQL relational database management system (RDBMS). SQLSDM provides a more semantically complete RDBMS through the implementation of a Domain and Relational Integrity scheme. SQLSDM provides integrity definition functions and a sub-system to interpret SQL commands . Integrity system tables are created through the use of SQLSDM \u27 s domain definition command and SQL \u27 s CREATE TABLE command. As SQL database update commands are interpreted, SQLSDM uses these integrity tables to enforce domain and referential integrity. SQLSDM operates virtually transparent to the user and provides for greater database consistency and semantic control. Furthermore, SQLSDM is designed and engineered to be a portable front-end that may be implemented on any SQL relational database management system

    A collective, probabilistic approach to schema mapping using diverse noisy evidence

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    We propose a probabilistic approach to the problem of schema mapping. Our approach is declarative, scalable, and extensible. It builds upon recent results in both schema mapping and probabilistic reasoning and contributes novel techniques in both fields. We introduce the problem of schema mapping selection, that is, choosing the best mapping from a space of potential mappings, given both metadata constraints and a data example. As selection has to reason holistically about the inputs and the dependencies between the chosen mappings, we define a new schema mapping optimization problem which captures interactions between mappings as well as inconsistencies and incompleteness in the input. We then introduce Collective Mapping Discovery (CMD), our solution to this problem using state-of-the-art probabilistic reasoning techniques. Our evaluation on a wide range of integration scenarios, including several real-world domains, demonstrates that CMD effectively combines data and metadata information to infer highly accurate mappings even with significant levels of noise
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