Bases de Datos Tema 2: Modelo Relacional y Diseño de U-tad

Grado en Ingeniería del Software

Doble Grado en Matemática Computacional e Ingeniería del Software Doble Grado en Física Computacional e Ingeniería de Software U-Tad Bases de Datos Tema 2 Rafael Socas Gutiérrez Amador Maho Etohá Enero 2024 :00000 05 ABCDE OK OK OK OK -- OK 2 3 4 5 9 8 8 04 0 03 02- 181 8 18:1 08 07 - 05 1811 8 8 01U-Tad

Introducción a las Bases de Datos

1. Introducción a las Bases de Datos
2. Modelo Relacional y Algebra Relacional
3. El Lenguaje SQL y SQL Avanzado
4. Acceso a MySQL, Almacenamiento e Indexado
5. Administración de Bases de Datos en MySQL
6. Aspectos Avanzados sobre BBDD Relacionales e Introducción a las BBDD No Relacionales: MongoDB

2 R10 m loan taxed on The tax returns INa what portion of its inc or (8) af any ( Hunter Eye Gear wibuti ns received by th income not d por (7) ved by the trust w rece if it had ney paid ou beneficiaries a been received by the trust, but rathe. d to as the 'conaunt pipe' principle. Under this principle the purposes, a. ved interest income, the beneficiary receives the distribution as *i TAX PROVISIONS x purpose This is a trus scotte recei I was trust is faced subject to the provisions of section 258 and section ? of the facesse The Mex In such a case wstamentary trust prines referessere a will trust such a trust is created in terms of the w dt of & dusouned preems anderson is not anve at any time during the trust's existroce the income falle to be turadi in the Bandin of tvr the trust or the beneficiaries. Sofiaties are taxes on the income it distributes. SECTION 258 - INCOME OF TRUSTS . . Desarrollo de la asignatura - . ---- ------ --- . D B B - Beneficiary. T = Trust. - Donor "A discretionary trust is one in which the some portion of the income of the income of the trust vests in the be the trust to the beneficiaries. not to a trust is s hether it i. s beneficiaries (i.e. it is their ome. is said to have a vested rip He incor rusts are set out in a wa easy for the to cale- son's hands. trust is usuany In the case Trustee wwvalo: the beneficiaries are unless section 7(3), (4), (2 Faitces (unless sections 7(5) Egy the court held that where fax year, it was treated The tax returns issued for trus cits income ust be taxed in which Ach makes it MR GREEN - FOUNDER trust rece X.J INCO want to distinguish between two different types of trust. enses). The R1,5m m ree possible categories et a block of flats (market value R10m) to the trus wwefit of his three children, Ned, Fred and Nelly ematically as follows: ---- - ge of large an the au te the hands of the person who put the ted ats of large amounts of ugh the use of a trust for ance provisions which are No ---- No Yes Yes ich the trustees have the poy In such a case the beneficiary is is formed by a living person, which means that such founder could be liable for tax on the trust. Once the founder has died it is obviously no longer possible to tas the foundlive. st and beneficiaries will be the only taxpayers subject to tas Trust Fund - ----U-Tad

Modelo Relacional y Álgebra Relacional

Índice U-Tad

1. Reglas de Codd
2. Estructura Modelo Relacional
3. Esquemas y Atributos del Modelo Relacional
4. Claves: Primarias vs. Foráneas
5. Fases de Diseño BBDD
6. Normalización
7. Operaciones de Álgebra Relacional

Reglas de Codd

Modelo Relacional: Las 12 Reglas de Edgar Codd (1/4)

U -Tad (1923 -2003) Edgar Frank Codd ¿Qué es y qué no es una base de datos relacional ?: Reglas de Codd Al principio de las bases de datos relacionales, como en todo mercado nuevo, no había una definición clara de lo que era y de lo que no era una base de datos relacional. Tuvo que llegar Edgar Codd con una serie de artículos para establecer una serie de reglas "las Reglas de Codd" para determinar si un base de datos de podía llamar relacional. Desarrolladas en los 70's por Edgar Frank Codd de IBM, son reglas que un verdadero sistema relacional debería tener. El documento principal de Codd es "A Relational Model of Data for Large Shared Data Banks", y en resumen las 12 reglas de Codd (que son 13) se pueden describir como sigue: Fuente: https://sites.google.com/a/ies-azarquiel.es/biografia0813/home/edgar-codd Fuente: http://dbadixit.com/reglas-codd-las-bases-datos-relacionales/ 51. Reglas de Codd -Tad Information Retrieval P. BAXENDALE, Editor A Relational Model of Data for Large Shared Data Banks E. F. CODD IBM Research Laboratory, San Jose, California Future users of large data banks must be protected from having to know how the data is organized in the machine (the Internal representation). A prompting service which supplles such information is not a satisfactory solution, Activities of users at terminals and most application programs should remain unaffected when the internal representation of data is changed and even when some aspects of the external representation are changed. Changes in data representation will often be needed as a result of changes in query, update, and report traffic and natural growth in the types of stored information. Existing noninferential, formatted data systems provide users with tree-structured files or slightly more general network models of the data. In Section 1, inadequacies of these models are discussed. A model based on n-ary relations, a normal form for data base relations, and the concept of a universal data sublanguage are introduced. In Section 2, certain opera- tions on relations (other than logical inference) are discussed and applied to the problems of redundancy and consistency in the user's model. KEY WORDS AND PHRASES: data bank, data base, data structure, data organization, hierarchies of dote, networks of data, relation, derivebility, redundancy, consistency, composition, join, retrieval language, predicate calculus, security, data integrity CR CATEGORES: 3.70, 3.73, 3.75, 4.20, 4.22, 4.29 1. Relational Model and Normal Form 1.1. INTRODUCTION This paper is concerned with the application of ele- mentary relation theory to systems which provide sharod access to large banks of formatted data. Except for a paper by Childs [1], the principal application of relations to data systems has been to deductive question-answering systems. Levein and Maron [2] provide numerous references to work in this area. In contrast, the problems treated here are those of data independence -the independence of application prognuns and terminal activities from growth in data types and changes in data representation-and certain kinda of data inconsistency which are expected to become troublesome even in nondeductive systems, Volume 13 / Number 6 / June, 1970 The relational view (or model) of data described in Section 1 appears to be superior in several respects to the graph or network model [3, 4] presently in vogue for non- inferential systems. It provides a means of describing data with its natural structure only-that is, without superim- posing any additional structure for machine representation purposes. Accordingly, it provides a basis for a high level data language which will yield maximal independence be- tween programs on the one hand and machine representa- tion and organization of data on the other. A further advantage of the relational view is that it forms a sound basis for treating derivability, redundancy, and consistency of relations-these are discussed in Section 2. The network model, on the other hand, has spawned a number of confusions, not the least of which is mistaking the derivation of connections for the derivation of rela- tions (see remarks in Section 2 on the "connection trap"). Finally, the relational view permits a clearer evaluation of the scope and logical limitations of present formatted data systems, and also the relative merits (from a logical standpoint) of competing representations of data within a single system. Examples of this clearer perspective are cited in various parts of this paper. Implementations of systems to support the relational model are not discussed. 1.2. DATA DEPENDENCIES IN PRESENT SYSTEMS The provision of data description tables in recently de- veloped information systems represents a major advance toward the goal of data independence [5, 6, 7]. Such tables facilitate changing certain characteristics of the data repre- sentation stored in a data bank. However, the variety of data representation characteristics which can be changed without logically impairing some application programs is still quite limited. Further, the model of data with which users interact is still cluttered with representational prop- ertien, particularly in regard to the representation of col- lections of data (as opposed to individual items). Three of the principal kinds of data dependencies which still need to be removed are: ordering dependence, indexing depend- ence, and access path dependence. In some systems these dependencies are not clearly separable from one another. 1.2.1. Ordering Dependence. Elements of data in a data bank may be stored in a variety of ways, some involv- ing no concern for ordering, some permitting each element to participate in one ordering only, others permitting cach element to participate in several orderings. Let us consider those existing systems which either require or permit data clements to be stored in at least one total ordering which is closely associated with the hardware-determined ordering of addresses. For example, the records of a file concerning parts might be stored in ascending order by part serial number. Such systems normally permit application pro- grams to assume that the order of presentation of records from such a file is identical to (or is a subordering of) the Communications of the ACM 377

• Regla 0: El sistema debe ser relacional, tanto la base de datos y administrador de sistema; es decir, un sistema de base de datos relacional debe utilizar sus facilidades relacionales (exclusivamente) para manejar la base de datos. Todo en una base de datos está guardado en un sistema relacional y cualquier elemento (usuario, tabla, índice, etc.) se guarda dentro de la misma base de datos.
• Regla 1. Regla de la información. Toda la información en la base de datos es representada unidireccionalmente, por valores en posiciones de las columnas dentro de filas de tablas. Toda la información en una base de datos relacional se representa explícitamente como valores en tablas. No hay información que no esté en tablas.
• Regla 2. Del acceso garantizado. Todos los datos deben ser accesibles sin ambigüedad. Cada valor individual en la base de datos debe ser direccionable especificando el nombre de la tabla, la columna que lo contiene y la llave primaria. Eso significa que todo dato puede ser ubicado teniendo el nombre de la tabla, el nombre del campo y el registro del que se trate.

Fuente: https://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf Fuente: http://dbadixit.com/reglas-codd-las-bases-datos-relacionales/ 6