Data and Its Structure Data is actually stored as bits, but it is difficult to The Relational Data Model work with data at this level. It is convenient to view data at different levels of abstraction. Chapter 3 Schema: Description of data at some abstraction level. Each level has its own schema. We will be concerned with three schemas: physical, conceptual, and external. 1 2 Physical Data Level Conceptual Data Level Physical schema describes details of how data is Hides details. stored: tracks, cylinders, indices etc. In the relational model, the conceptual schema presents Early applications worked at this level data as a set of tables. explicitly dealt with details. DBMS maps from conceptual to physical schema automatically. Problem: Routines were hard-coded to deal with Physical schema can be changed without changing physical representation. application: Changes to data structure difficult to make. DBMS would change mapping from conceptual to Application code becomes complex since it must deal physical transparently with details. This property is referred to as physical data independence Rapid implementation of new features impossible. 3 4 External Data Level Conceptual Data Level (con t) In the relational model, the external schema also presents data as a set of relations. Conceptual view An external schema specifies a view of the data of data Application in terms of the conceptual level. It is tailored to the needs of a particular category of users. Portions of stored data should not be seen by some users. Students should not see their files in full. Physical view of data Faculty should not see billing data. DBMS Information that can be derived from stored data might be viewed as if it were stored. GPA not stored, but calculated when needed. 5 6 1 External Data Level (con t) Levels of Abstraction Application is written in terms of an external schema. billing A view is computed when accessed (not stored). payroll records Different external schemas can be provided to different View 1 View 2 View 3 External categories of users. schemas Translation from external to conceptual done automatically by DBMS at run time. Conceptual schema Conceptual schema can be changed without changing application: Physical schema Mapping from external to conceptual must be changed. Referred to as conceptual data independence. 7 8 Data Model Schema: description of data at some level Relational Model (e.g., tables, attributes, constraints, domains) A particular way of structuring data (using Model: tools and language for describing: relations) Conceptual and external schema Simple Data definition language (DDL) Mathematically based Integrity constraints, domains (DDL) Expressions ( queries) can be analyzed by DBMS Operations on data Queries are transformed to equivalent expressions Data manipulation language (DML) automatically (query optimization) Directives that influence the physical schema Optimizers have limits (=> programmer needs to know (affects performance, not semantics) how queries are evaluated and optimized) Storage definition language (SDL) 9 10 Relation Instance Relation Instance (Example) Relation is a set of tuples Tuple ordering immaterial Id Name Address Status No duplicates Cardinality of relation = number of tuples 11111111 John 123 Main freshman All tuples in a relation have the same structure; constructed from the same set of attributes 12345678 Mary 456 Cedar sophmore Attributes are named (ordering is immaterial) Value of an attribute is drawn from the attribute s domain 44433322 Art 77 So. 3rd senior There is also a special value null (value unknown or undefined), which belongs to no domain 87654321 Pat 88 No. 4th sophmore Arity of relation = number of attributes Student 11 12 2 Relation Schema Relational Database Relation name Finite set of relations Attribute names & domains Each relation consists of a schema and an Integrity constraints like instance The values of a particular attribute in all tuples Database schema = set of relation schemas are unique constraints among relations (inter-relational The values of a particular attribute in all tuples constraints) are greater than 0 Database instance = set of (corresponding) Default values relation instances 13 14 Database Schema (Example) Integrity Constraints Student (Id: INT, Name: STRING, Address: STRING, Part of schema Status: STRING) Restriction on state (or of sequence of states) of Professor (Id: INT, Name: STRING, DeptId: DEPTS) data base Course (DeptId: DEPTS, CrsName: STRING, Enforced by DBMS CrsCode: COURSES) Intra-relational - involve only one relation Transcript (CrsCode: COURSES, StudId: INT, Part of relation schema e.g., all Ids are unique Grade: GRADES, Semester: SEMESTERS) Inter-relational - involve several relations Department(DeptId: DEPTS, Name: STRING) Part of relation schema or database schema 15 16 Constraint Checking Kinds of Integrity Constraints Automatically checked by DBMS Static restricts legal states of database Protects database from errors Syntactic (structural) Enforces enterprise rules e.g., all values in a column must be unique Semantic (involve meaning of attributes) e.g., cannot register for more than 18 credits Dynamic limitation on sequences of database states e.g., cannot raise salary by more than 5% 17 18 3 Key Constraint A key constraint is a sequence of attributes Key Constraint (cont d) A1, ,An (n=1 possible) of a relation schema, S, with the following property: Superkey - set of attributes containing key A relation instance s of S satisfies the key constraint iff at most one row in s can contain a particular set of (Id, Name) is a superkey of Student values, a1, ,an, for the attributes A1, ,An Every relation has a key Minimality: no subset of A1, ,An is a key constraint Key Relation can have several keys: Set of attributes mentioned in a key constraint primary key: Id in Student (can t be null) e.g., Id in Student, candidate key: (Name, Address) in Student e.g., (StudId, CrsCode, Semester) in Transcript It is minimal: no subset of a key is a key (Id, Name) is not a key of Student 19 20 Foreign Key Constraint Foreign Key Constraint Referential integrity: Item named in one relation must refer to tuples that describe that item in another (Example) Transcript (CrsCode) references Course(CrsCode ) Professor(DeptId) references Department(DeptId) A2 Attribute A1 is a foreign key of R1 referring to attribute A2 in R2, A1 v3 v1 v5 if whenever there is a value v of A1, there is a tuple of R2 in which A has value v, and A is a key of R2 v2 v1 2 2 v3 v6 This is a special case of referential integrity: A must be a candidate key 2 v4 v2 of R2 (e.g., CrsCode is a key of Course in the above) R2 Course null v7 If no row exists in R2 => violation of referential integrity v3 v4 Not all rows of R2 need to be referenced: relationship is not symmetric R1 R2 (e.g., some course might not be taught) Foreign key Value of a foreign key might not be specified (DeptId column of some Candidate key professor might be null) 21 22 Foreign Key (cont d) Foreign Key (cont d) Foreign key might consist of several columns Names of the attrs A1 and A2 need not be the same. (CrsCode, Semester) of Transcript references With tables: (CrsCode, Semester) of Teaching Teaching(CrsCode: COURSES, Sem: SEMESTERS, ProfId: INT) Professor(Id: INT, Name: STRING, DeptId: DEPTS) R1(A1, An) references R2(B1, Bn) ProfId attribute of Teaching references Id attribute of Professor Ai and Bi must have same domains (although not R1 and R2 need not be distinct. necessarily the same names) Employee(Id:INT, MgrId:INT, .) B1, ,Bn must be a candidate key of R2 Employee(MgrId) references Employee(Id) Every manager is also an employee and hence has a unique row in Employee 23 24 4 Inclusion Dependency SQL Referential integrity constraint that is not a foreign key constraint Language for describing database schema Teaching(CrsCode, Semester) references and operations on tables Transcript(CrsCode, Semester) Data Definition Language (DDL): (no empty classes allowed) sublanguage of SQL for describing schema Target attributes do not form a candidate key in Transcript (StudId missing) No simple enforcement mechanism for inclusion dependencies in SQL (requires assertions -- later) 25 26 Table Declaration Tables Student ( Id: , SQL entity that corresponds to a relation Name: (20), Address: (50), An element of the database schema Status: 10) SQL-92 is currently the most supported ) standard but is now superseded by Id Name Address Status SQL:1999 and SQL:2003 101222333 John 10 Cedar St Freshman Database vendors generally deviate from 234567890 Mary 22 Main St Sophomore the standard, but eventually converge 27 Student 28 Primary/Candidate Keys Null Course ( Problem: Not all information might be known when CrsCode (6), row is inserted (e.g., Grade might be missing from CrsName (20), Transcript) DeptId (4), A column might not be applicable for a particular Descr (100), row (e.g., MaidenName if row describes a male) (CrsCode), Solution: Use place holder null DeptId, CrsName) -- candidate key Not a value of any domain (although called null value) ) Indicates the absence of a value Not allowed in certain situations Comments start with 2 dashes Primary keys and columns constrained by 29 30 5 Default Value Semantic Constraints in SQL -Value to be assigned if attribute value in a row Primary key and foreign key are examples is not specified of structural constraints Semantic constraints Student ( Express the logic of the application at hand: Id , e.g., number of registered students maximum Name , enrollment