Presentation is loading. Please wait.

Presentation is loading. Please wait.

Week 2: Directed Reading Relational Database Design Nick Rossiter

Similar presentations


Presentation on theme: "Week 2: Directed Reading Relational Database Design Nick Rossiter"— Presentation transcript:

1 Week 2: Directed Reading Relational Database Design Nick Rossiter
Database Modelling Week 2: Directed Reading Relational Database Design Nick Rossiter April 6, 2017

2 Learning Objectives To consider atomic data in relations
To consider data types in a relation To consider missing data & NULLs in relations To consider Integrity Constraints To consider the principles of Candidate Keys To consider Candidate Keys in SQL April 6, 2017

3 The Information Principle
A relation contains only data values, i.e. facts. Each attribute-in-a-tuple contains just a single data value. In particular there are no pointers or OIDs. Pointers point to variables because they reference the storage location of the variable) and thus are different in nature to data values. The reason for this principle is to keep relations simple. Following work by EF Codd (1970) April 6, 2017

4 Efficiency and Human Productivity
Handling of relations is a simple abstraction: of what is going on at the physical level of a computer queries that used to take many hours to write for earlier types of DB can be written in a few minutes in a relational language. It would be foolish to throw away this productivity Use computer power to increase human productivity. April 6, 2017

5 Use of Pointers Pointers are often advocated as a means to make DBs more efficient. But their place is in the implementation of the relational model that the user uses, not in the model itself where it complicates things. It is important to distinguish between the relational model and its implementation. Object-based DBMS provide pointers at the logical level. April 6, 2017

6 Atomic Data Since it is now known that an atom consists of component parts – a nucleus of protons and neutrons with electrons orbiting round it - perhaps atom is no longer the best word to describe this concept. However until the 20th century, an atom was regarded as the smallest, indivisible particle of matter possible The tradition of using atom/atomic to describe this concept has remained. April 6, 2017

7 Definition of Atomic Value
Definition: An atomic value is a single, indivisible value, not a composite value or a collection of values. The data in one attribute of one tuple must be atomic. April 6, 2017

8 Example of Atomic Data Example: In this EMPLOYEE relation there
is only one value in each attribute-in-a-tuple. April 6, 2017

9 Atomicity Requirement
Maintains the inherent simplicity of relations, and is of great practical benefit. Occasionally it is not obvious whether a value is atomic or not. For example, is a date atomic? On the one hand, it represents a particular day in the calendar, and thus should be atomic. On the other hand, it has 3 components, day-of-the-month, month and year. Another example is a person’s full name should this be atomic ? or split into its component parts, (set of) forename(s) and surname? April 6, 2017

10 Designer’s choice The DB designer must decide
based on what precisely the data means in the context of the database and how it will be used. Typically a date will be regarded as atomic, through a date type predefined in the database standard SQL.   Names are more diverse and are usually handled through definitions to suit the application. April 6, 2017

11 Non-Atomic Data Example: A “relation” containing non-atomic data.
April 6, 2017

12 Multiple Atomic Values
The attributes ‘Component’ and ‘’Quantity’ clearly contain multiple atomic values. Although not shown in the above example, it is possible that some tuples could contain single values of ‘Component’ and ‘Quantity’. Traditional prohibition against repeating values has weakened in the last few years. allowing relations and other “container types” such as arrays, records, etc to be stored as the single atomic value in an attribute. April 6, 2017

13 Data Types Definition: A data type has a set of permissible values.
Each attribute value must be drawn from the set of permissible values of the data type specified for that attribute. More than one attribute in a relation may draw its values from the same data type. April 6, 2017

14 Example of Type Assignment
Every attribute must have a data type, just as every variable in a program must have a type. April 6, 2017

15 Example of Using Data Types
April 6, 2017

16 Comments on Example All the attribute values in the top tuple are drawn from their respective data types Would not be acceptable otherwise. Only 1 out of 4 values in the bottom tuple are drawn from their respective data types; so that tuple cannot be stored in the relation. If even one attribute has a value that is not drawn from its type’s set of permissible values that tuple cannot be in the relation. April 6, 2017

17 Data Types -- Operators
Definition: A Data Type has a set of permissible operators. Examples :  Number : +, -, /, x, <, > apply to all possible numbers Text : length( ), sub( ), concat( ) apply to all possible texts April 6, 2017

18 Data Type Implementation
A data type needs logical representations for its values and operators. These are what the user uses. They become part of the logical model. A data type needs physical representations for its values and executable code for each of its operators. These form the implementation of the logical model.  We need Strong Typing. Object classes as described in traditional object-oriented programming meet precisely these criteria. Thus object classes are data types. April 6, 2017

19 Built-in Data Types Commonly needed data types are Built-In, i.e. provided with the DBMS. Examples: Number, Text, (and usually Date ). Text appears as char, varchar in SQL Also have data types for multimedia (blob, clob in SQL) Can also add new data types (later in module) April 6, 2017

20 Underlying/Specific Data Types
When specifying an attribute‘s type, there are typically 2 stages : Specify the general kind of data required, e.g. numbers, text, dates. This is the Underlying Type. Specify that subset of it that the attribute values must be limited to, e.g. only the integer numbers ,000. This is the Specific Type. It uses the same operators as the underlying type. April 6, 2017

21 Example of Specific Type
Note that data types have sets of values that are permitted to be used. Specific Type allows a subset of those in Underlying Type April 6, 2017

22 Ways to Define a Mathematical Set
Set enumeration the values in the set are individually specified; useful for comparatively small sets of values. Set comprehension a constraint or rule applied to any potential member of the set to see if it is in fact a member of the set Both these methods can be used to constrain the underlying type to get the specific type. April 6, 2017

23 CHECK constraint Some underlying types have parameters
which can be used to constrain them to the specific type. SQL has a Check constraint option, allows the enumeration of the specific type within the underlying type and more ad hoc constraints on the underlying type April 6, 2017

24 SQL Data Types SQL data types are often based on their physical storage. April 6, 2017

25 Explanation of Types The “2” in Varchar2(x) indicates that it is Oracle’s second version of the variable length text type. It has nothing to do with the number of characters in the text. It is the standard Oracle variable length text type now. The text type is often known as the character string type. SQL attributes/columns are assigned their types when the relation/table is created with the Create Table statement. The SQL Create Table statement is the statement used to specify all aspects of a table. the Alter Table statement can be used to add, delete and modify any aspect of a table already created with a Create Table. April 6, 2017

26 SQL : Example The SQL Create Table statement creates a table type with the required columns of specified names and specific types (which will use the operators of the underlying types), and creates the table variable EMPLOYEE of that type. April 6, 2017

27 Missing Data In the real world, data is not always available to put in the DB. Reasons for this include the value being : unknown  not available  not applicable  not yet known  undefined  to be announced  does not exist  not supplied, etc  One paper recorded 42 different reasons! April 6, 2017

28 Solutions to Missing Data
Use a special value to represent missing data. Example: ‘N/A’, ‘T.B.A.’ It gives the reason why the data is missing. The special value must have the same type as the data that is missing, so it can be stored with the data that is known. So cannot use ‘N/A’ in numeric field April 6, 2017

29 Use of NULL Null requires special support from the DBMS. SQL DBMSs provide this support. But which reason does it represent ? In reality, no-one yet has come up with a good way of handling missing data that is generally accepted . These options are the main ones used in practice, but there is considerable controversy about them. April 6, 2017

30 NULL terminology We might say :
“The attribute ‘Sal’ in a tuple has a null value.” This is wrong ! Null is the absence of a value, so it can’t be a value. “The attribute ‘Sal’ in a tuple contains a null.” This is better, but not very precise. “The attribute ‘Sal’ in a tuple is null.” This is accurately stated. ‘Sal’ is null does not mean that there is no such value or that the salary is £0. April 6, 2017

31 2-Valued Logic Normal Boolean logic only has the truth values true and false. The result (or value) of any comparison will be true or false. Thus, the Boolean logic operators AND, OR and NOT can be used to combine comparisons, forming an expression. Example:- ( X = 3 AND Y < X ) OR NOT ( Y > 0 )  The value of this expression will be true or false, and can be derived if the values of X and Y are known. April 6, 2017

32 Truth Table The rules which the logic operators apply to their operands to yield a Boolean result are represented by truth tables In the tables, T and F stand for true and false respectively. The 3 operators yield commonsense results. AND yields false unless both its operands are true, OR yields true unless both operands are false, and NOT reverses the truth value of its operand. April 6, 2017

33 3-valued Logic With NULL, results of queries can be maybe.
For example, for X = Y, if both NULL, result is unclear. We still want to use logical expressions. Therefore AND, OR and NOT must be extended to cope with maybe. This logic offends Gödel’s theorem on decidability. April 6, 2017

34 3-valued Logic Truth Tables
In the tables, M stands for maybe. April 6, 2017

35 SQL : Not NULL Constraint
Sometimes we want to prevent a column from ever holding NULLs. To achieve this in SQL, add a “Not NULL” constraint to the definition of the column. April 6, 2017

36 Advantages of NOT NULL Because 3-valued logic is more complex than 2-valued it sometimes gives unexpected results It is desirable to avoid having missing data if at all possible. It would be better to stick to 2-valued logic.  Thus we often specify a “not NULL” constraint for a column to ensure that it always contains a data value in every row. April 6, 2017

37 Integrity Constraints
Definition: An Integrity Constraint is a constraint on the values that a given DB relation is permitted to hold. April 6, 2017

38 Purpose To try to ensure that the relations in the DB only hold data that is true, accurate and up-to-date. A constraint is a validation check that the DBMS automatically applies when a relation’s value is altered. The requirement that a data type be assigned to every attribute is itself an integrity constraint. However, more integrity constraints are possible. April 6, 2017

39 Applying Constraints in SQL
In SQL, integrity constraints are usually applied when the relation is created using the Create Table statement. But can also be enforced in the Alter Table statement April 6, 2017

40 Categories of Integrity Constraints
Attribute type constraints: already considered. Candidate Key constraints: these apply to an individual relation.  Referential Integrity constraints: these correlate two relations. Ad hoc constraints: these apply to one or more relations.  This is not the only possible categorisation of integrity constraints but it is a convenient and practical one. April 6, 2017

41 Candidate Keys There are no duplicate tuples in a relation, because it is a set of tuples. So every tuple must be unique. Often, indeed typically, the values of only one attribute, or a small number of attributes, in a relation are sufficient to make each tuple in it unique. Whether it requires one attribute, several attributes, or all the attributes in a relation to make each tuple unique, that set of 1 or more attribute(s) is called a Candidate Key. April 6, 2017

42 Candidate Keys for ID The candidate key attribute(s) can also be considered as uniquely identifying each tuple in the relation. A relation may contain two or more candidate keys. Often a candidate key consists of just one attribute. For example passport number. Nevertheless it is quite normal for a candidate key to consist of 2 or more attributes For example student number + module number in marks Occasionally in an extreme case all of a relation’s attributes form the candidate key. If there is only one key, it is still called the Candidate Key. April 6, 2017

43 Properties of a Candidate Key
Uniqueness: No two distinct tuples may contain the same key value. Irreducibility: No attribute can be removed from the set forming the key, and the remaining attributes still possess the uniqueness property. Underlining attribute(s) is a common way of specifying a candidate key. April 6, 2017

44 Benefits of these two Properties
Candidate keys provide (the only) guaranteed way to find a particular tuple. Checks on the uniqueness of tuples can be limited to the candidate key attribute(s), giving greater efficiency. April 6, 2017

45 Candidate Keys: Example (1)
April 6, 2017

46 Rationale for Candidate Keys
Relation EMPLOYEE : Employee names are not guaranteed to be unique, Many employees may be on the same salary. So none of the attributes apart from ‘ENo’, either on their own or taken in combination, is sufficient to form a candidate key for EMPLOYEE. Relation CAR : A car’s registration number is guaranteed to be unique, and so can be a candidate key. As ‘Owner’ is an employee number which the company will ensure is unique, that can also be a candidate key April 6, 2017

47 Candidate Keys : Example (2)
Re-consider CAR. Let us change the assumptions. The company now has a “share and park” scheme whereby a group of employees can share a car to work; a group may use several of the members’ cars. Now neither ‘RegNo’ or ‘ENo’ on its own is sufficient to identify a tuple in CAR. However, both together will identify any tuple. Therefore, they jointly become the only candidate key. April 6, 2017

48 2-attribute candidate key
The ‘ENo’ attribute need not represent the owner of the car in question; s/he need not even own a car. We simply need to know which cars each employee may come to work in, or alternatively which employees may be allowed to come to work in each car. It is essential to be able to distinguish: two 1-attribute candidate keys and one 2-attribute candidate key. April 6, 2017

49 Candidate Keys in SQL SQL has Primary and Alternate Keys.
If there is only one candidate key, it becomes the primary key; there are no alternate keys. If there is more than one candidate key, choose one as the primary key; the rest become the alternate keys. April 6, 2017

50 Making the choice Any candidate key can become the primary key.
So choose one that makes the most practical sense. Usually the shortest - easiest for the user, most efficient for the computer. While SQL defines a Primary Key using the phrase Primary Key, it defines an Alternate Key using the word Unique!  SQL does not make specifying at least one candidate key mandatory ! April 6, 2017

51 Define a Primary Key So bags can occur. To insist on a set
Therefore ensure every SQL table has at least a primary key. April 6, 2017

52 SQL Key Requirements SQL requires that a primary key never be null.
However, it will let an alternate key be null, thereby permitting duplicate null keys, a contradiction in terms. To prevent this, a “not NULL” constraint can be added to an alternate key. It is desirable to specify any other candidate keys that happen to exist as alternate keys.   April 6, 2017

53 Entity Integrity This is an additional constraint for relational DBs that allow nulls. Definition: Entity Integrity requires that no attribute in a primary key can ever be null. April 6, 2017

54 Rationale Each tuple represents an entity in the real world
Each entity must be identifiable by definition Primary keys serve as identifiers of tuples Therefore a primary key can never be partly or wholly null, to ensure that it does identify each tuple. Note entity integrity does not apply to alternate keys which can be null, either wholly or in part. April 6, 2017

55 Constraint Names Most relational DBMSs give integrity constraints a name when they store the constraint in the DB. Thus a candidate key constraint would receive a name. If the user does not supply a name when assigning the constraint, a unique default name is created for it by the DBMS. April 6, 2017

56 Use of naming Constraints
The naming of integrity constraints can be of great practical use : It helps users find out about what integrity constraints have been assigned to relations. It allows more meaningful error messages to be provided to the user if there is an attempt to break an integrity constraint. April 6, 2017

57 Constraints in Oracle Oracle allows user to provide integrity constraint names, and generate default names if the user does not provide them. Oracle default names are not very user-friendly. Therefore assign your own names to integrity constraints. Constraint names must be unique within the entire user’s DB, not just within a single relation. April 6, 2017

58 Specifying Candidate Keys in SQL
Keys (primary and alternate) can be assigned in two places : in the same sub-statement in which an attribute is assigned its type, in a separate sub-statement at the end of a Create Table statement. The first method is only possible if the SQL key consists of one attribute. The second method must be used if the key consists of two or more attributes. April 6, 2017

59 Constraint Definition
In either case, starting the assignment of an SQL key with the phrase Constraint constraint-name assigns a name to the key constraint as well In Oracle, if a primary or alternate key constraint is assigned in its own sub-statement at the end of the Create Table statement, then it is mandatory to give the constraint a name. April 6, 2017

60 Examples of SQL Keys (1) In Oracle, note that :
Create Table EMPLOYEE ( ENo Char( 2 ) Primary Key , EName Varchar2( 30 M - S 1 Check ( M In (‘S’, ‘M’, ‘W’, ‘D’ ) ), Sal Number ( Sal >999 And Sal < ) ) ; Sal < ), Primary Key( ENo ) ); These 2 versions of have a default constraint name. In Oracle, note that :  the first example is permissible  the second example would not be permissible, because no name has been assigned to the key constraint and so a default name must be given. April 6, 2017

61 Examples of SQL Keys (2) In Oracle, both examples are permissible.
April 6, 2017

62 Examples of SQL Keys (3) Note that, in any version of SQL, only the second method is permissible if a primary or alternate key consists of 2 or more attributes. April 6, 2017


Download ppt "Week 2: Directed Reading Relational Database Design Nick Rossiter"

Similar presentations


Ads by Google