The Relational Data Model

Transcription

1 The Relational Data Model Peter Y. Wu Dept of Computer and Information Systems Robert Morris University Introduction: The Relational Model Proposed by Codd (1970) A relational model for large shared data banks, CACM 13(6), See also Data model theoretically defined before implementation. First implementations (circa 1976): System R (IBM San Jose Research Lab) Ingres (Stonebraker, UC Berkeley) First commercial systems: Oracle (1979) Ingres (1980? Computer Associates) Postgres IBM SQL/DS (1981). State of the art in industry today. 2 (c) Peter Y. Wu - RMU. 1

2 Relational Model: introduction Why was the Relational Model successful? Simple: one main concept: Relation. Relations correspond to Tables. Tables correspond to Files of Records. Solid theoretical foundation: 1 st order predicate logic. Well defined set operations model the manipulation of data as well as schema. It supports query in a declarative manner: search plan for answer generated automatically! (Therefore, no need to be concerned about efficient evaluation; query optimization can be done separately.) 3 Relational Model: an example Composer CNo CName Born Died 1 Vivaldi Bach Mozart Prokofiev Dvorak PNo Piece PName The Four Seasons B-minor Mass Christmas Oratorio Missa Solemnis Classical Symphony Cinderella CNo (c) Peter Y. Wu - RMU. 2

3 Relational Model: an example We use tables to organize our information; a database consists of a finite number of tables. Each table in the database is called a relation, identified by a name. Each table consists of columns and rows. Each column identifies an attribute, which is the column name. Each column entry is an attribute value. Each row identifies a record, associating the corresponding entries of attribute values together. Specific entries in a table may refer to other entries, in the same table, as well as some other tables. 5 Relational Model: Terminology A relational database is a collection of tables. Each table is a relation Relation Name Attribute Name Tuple Tuple R A 1... A m V 1,1 V 1,m V n,1 V n,m Attribute Name Attribute Value Attribute Value Relation = Table Attribute = Column, Field Attribute Value = Data Value Tuple = Row, Record 6 (c) Peter Y. Wu - RMU. 3

4 Relational Model: Terminology A relational database is a collection of tables. Each table is a relation Table Name Column Row Row or Record R A 1... A m V 1,1 V 1,m V n,1 V n,m Column Data Value Data Value Relation = Table Attribute = Column, Field Attribute Value = Data Value Tuple = Row, Record 7 Relational Model: Summary Database Schema Table (columns) Record (data values) Table Record Relation (attribute names) Constraints Tuple (scalars in order) Data (domain) Data Value Attribute Value Domain is the set of all permitted data values. data type. 8 (c) Peter Y. Wu - RMU. 4

5 Relational Data Model: Key The table is a set of records. No two rows of a table should be the same! that is, no duplicate rows. (why?!) in practice, it does not seem to be so but it is actually true and implemented. (how?!) How do we guarantee that there are no duplicate rows in a table? More about the concept of Keys later 9 Relational Algebra Operations on tables (sets of records) mathematically defined operation on tables to produce a table as the result. The basis of SQL implementation. Selection pick some records Projection pick some columns More but will study SQL instead. 10 (c) Peter Y. Wu - RMU. 5

6 Selection Select[cond](R) selects tuples out of S(R), the database state of relation R, which meet the specified condition in cond, to result in a new relation. σϕ(r) where R is the relation, and ϕ is the logical statement of condition to meet. Example: A B a1 b1 σa=a1( a1 b2 )= A B a1 b1 a2 b3 a1 b2 11 Selection The selection condition is a logical statement. The statement can refer to any Attribute of the Relation R, as well as constant attribute value, in a logical and/or arithmetic expression. Examples: Select [CName= Mozart ] (Composer) Select [(Died-Born)<40] (Composer) Select [CName like M% AND Born<1800] (Composer) 12 (c) Peter Y. Wu - RMU. 6

7 Projection Project[attr-list](R) selects columns specified in the attributes list, attr-list, out of S(R), the database state of relation R, to result in a new relation. π λ (R) where R is the relation, and λ is the list of attributes identifying the columns to be selected. Example: A B C a1 b1 c1 a2 b2 c2 a3 b3 c3 π A,C ( )= A a1 a2 a3 C c1 c2 c3 13 Projection While selection picks out certain rows from a table, projection picks out certain columns. Project [B 1,B 2,,B k ] (R) results in a relation of degree k, and k degree of R. Projection does not change the attribute values, but maintains only the values for the attributes specified in the projection operation. Projection may result in a relation with less number of rows than the input relation. 14 (c) Peter Y. Wu - RMU. 7

8 Projection Since the database state S(R) is a set of records, there should be no duplicate records. Projection may result in a relation with less number of rows A B C π ( A,C )= A C (c) Peter Y. Wu - RMU. 8