2.3 Keys, constraints, and relationships
4 min read•august 6, 2024
Keys, constraints, and relationships form the backbone of relational databases. They ensure data integrity, define connections between tables, and establish rules for data storage and manipulation. Understanding these concepts is crucial for designing efficient and accurate database structures.
This section explores different types of keys, various integrity constraints, and relationship types in relational databases. It covers how these elements work together to create a robust and reliable database system, essential for managing complex data relationships.
Key Types
Superkeys and Candidate Keys
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- uniquely identifies each tuple (row) in a relation (table)
- Consists of one or more attributes
- Multiple superkeys can exist in a relation
- is a minimal superkey
- Removing any attribute from a candidate key results in a set of attributes that is no longer a superkey
- All candidate keys are superkeys, but not all superkeys are candidate keys
- A relation can have multiple candidate keys
Primary and Foreign Keys
- is a candidate key chosen to uniquely identify tuples in a relation
- Only one primary key per relation, but it can consist of multiple attributes ()
- Cannot contain null values
- Each relation must have a primary key
- is an attribute or set of attributes in one relation that refers to the primary key of another relation
- Establishes a link between two relations
- Maintains between related relations
- Values in the foreign key must match values in the primary key of the referenced relation or be null
Integrity Constraints
Entity and Referential Integrity
- ensures that no primary key value is null
- Guarantees each tuple in a relation can be uniquely identified
- Enforced by specifying primary key attributes as NOT NULL
- Referential integrity ensures that a foreign key value must match an existing primary key value in the referenced relation or be null
- Maintains consistency between related relations
- Enforced by foreign key constraints
Domain and Check Constraints
- specifies the permissible values for an attribute
- Defines the data type (integer, string, date), format, and range of values allowed
- Ensures data consistency and accuracy
- Examples: age (integer, 0-150), email (valid email format)
- is a condition that must be satisfied by attribute values in a relation
- Allows for more complex data validation beyond domain constraints
- Specified using a Boolean expression that must evaluate to true for each tuple
- Examples: salary > 0, start_date < end_date
Relationship Types
One-to-One and One-to-Many Relationships
- exists when each tuple in one relation is related to at most one tuple in another relation
- Rarely used in practice due to limited applicability
- Example: a person can have only one passport, and a passport belongs to only one person
- exists when each tuple in one relation can be related to multiple tuples in another relation, but each tuple in the second relation is related to at most one tuple in the first relation
- Most common type of relationship in relational databases
- Example: a department can have many employees, but each employee belongs to only one department
Many-to-Many Relationships
- exists when each tuple in one relation can be related to multiple tuples in another relation, and vice versa
- Implemented using a junction table (also called a bridge table or associative entity) that contains foreign keys referencing the primary keys of the related relations
- Example: a student can enroll in many courses, and a course can have many students enrolled
- Junction table "enrollment" with foreign keys referencing "student" and "course" relations
Relationship Constraints
Cardinality and Participation Constraints
- specifies the maximum number of tuples in one relation that can be associated with a single tuple in another relation
- Common cardinalities: one-to-one (1:1), one-to-many (1:N), many-to-many (M:N)
- Determined by the nature of the relationship between entities
- specifies whether the existence of a tuple in one relation depends on its relationship with a tuple in another relation
- Total participation (existence dependency): every tuple in one relation must be associated with at least one tuple in another relation
- Example: every employee must be assigned to a department
- Partial participation: a tuple in one relation may or may not be associated with a tuple in another relation
- Example: a customer may or may not place an order
- Total participation (existence dependency): every tuple in one relation must be associated with at least one tuple in another relation
Key Terms to Review (24)
Alter table: The 'alter table' command is a SQL statement used to modify an existing database table's structure, allowing you to add, drop, or change columns and constraints. This command plays a crucial role in maintaining and evolving database schemas as application requirements change, ensuring data integrity and optimizing relationships among tables.
Candidate key: A candidate key is a minimal set of attributes that uniquely identifies a record in a relational database table. Each candidate key can be used to uniquely retrieve data, ensuring that no two rows have the same value for this key, while also being the smallest possible set of attributes needed for that uniqueness. Understanding candidate keys is crucial as they directly relate to functional dependencies, normalization processes, and the establishment of relationships between tables.
Cardinality Constraint: A cardinality constraint defines the numerical relationships between entities in a database, indicating how many instances of one entity can or must be associated with instances of another entity. It is crucial for understanding how data is structured and related within a database, affecting both the integrity of the data and the way queries are constructed.
Check constraint: A check constraint is a rule applied to a column in a database table that restricts the values that can be inserted or updated in that column based on a specific condition. It ensures data integrity by enforcing certain criteria, like a range of values or specific formats, which helps maintain the quality and accuracy of the data stored in a relational database. Check constraints play a significant role in defining how data relates to itself and other tables, providing a structured approach to maintaining valid data throughout its lifecycle.
Composite key: A composite key is a combination of two or more columns in a database table that can uniquely identify a row in that table. This type of key is essential when a single column is not sufficient to guarantee uniqueness, often resulting from a many-to-many relationship where multiple attributes are needed to form a unique identifier. Composite keys play a critical role in maintaining data integrity and establishing relationships between tables.
Create table: The 'create table' statement is a SQL command used to define a new table in a database, including its structure and the data types of its columns. This command lays the foundation for how data will be organized, accessed, and manipulated within the database. It also allows the specification of keys, constraints, and relationships between different tables, which are crucial for maintaining data integrity and establishing connections between data points.
Crow's Foot Notation: Crow's foot notation is a graphical representation used in Entity-Relationship (ER) modeling to illustrate the relationships between entities in a database. This notation uses symbols that resemble a crow's foot to indicate the cardinality of relationships, such as one-to-one, one-to-many, or many-to-many. Understanding this notation is essential for developing clear ER diagrams, translating them into relational schemas, and identifying keys and constraints within database structures.
Domain constraint: A domain constraint is a rule that specifies the permissible values that a certain attribute in a database can take. This ensures data integrity by restricting the type of data entered into the database, such as setting limits on the range of values, data types, or formats. By enforcing domain constraints, databases can prevent invalid or inconsistent data entries, which is crucial for maintaining accurate and reliable information.
Entity Integrity: Entity integrity is a fundamental principle in relational database design that ensures each entity, or row, in a table is uniquely identifiable and has a primary key that is not null. This principle maintains the uniqueness and validity of each record, establishing a clear framework for data retrieval and management, which is vital for maintaining accurate and consistent databases.
Entity-relationship model: The entity-relationship model is a conceptual framework used to describe the structure of a database by defining entities, attributes, and the relationships between them. This model is crucial for database design and provides a visual representation that helps in understanding how data is organized and how different data points are interconnected, influencing various aspects such as the evolution of database systems and the establishment of keys and constraints.
First normal form (1NF): First normal form (1NF) is a property of a relational database table that ensures the data is stored in a way that each column contains atomic values, and each entry in a column is of the same kind. This means that there are no repeating groups or arrays within a single column, allowing for clearer relationships and easier data manipulation. Achieving 1NF is a critical step in the normalization process and helps establish a solid foundation for further normalization, such as second and third normal forms.
Foreign key: A foreign key is a field (or a collection of fields) in one table that uniquely identifies a row of another table, creating a link between the two tables. This concept is crucial for establishing relationships in relational databases, ensuring data integrity and enforcing referential constraints between related tables.
Functional Dependency: Functional dependency is a relationship between attributes in a database, where one attribute uniquely determines another. This concept is crucial for understanding how data is organized and structured within a database, influencing the design of schemas and the normalization process to eliminate redundancy and ensure data integrity.
Many-to-many relationship: A many-to-many relationship is a type of association between two entities where multiple records in one entity can be associated with multiple records in another entity. This relationship often requires a third table, called a junction or associative table, to properly map the connections between the two entities. Understanding this concept is crucial for effectively designing databases that accurately represent complex relationships and ensure data integrity.
Not Null Constraint: A not null constraint is a rule in database management systems that ensures a column cannot have a null value, which means it must always contain a valid entry. This constraint is critical for maintaining data integrity, as it prevents incomplete records and ensures that essential fields are populated. It connects to various database features, including how relationships and constraints are mapped, how constraints are defined, and how data is manipulated through inserting, updating, or deleting.
One-to-many relationship: A one-to-many relationship is a type of association between two entities where a single instance of one entity can be related to multiple instances of another entity. This concept is crucial in organizing data effectively, allowing for the creation of structured databases where one record can link to many others, facilitating efficient data retrieval and management.
One-to-One Relationship: A one-to-one relationship in databases occurs when a single record in one table is linked to a single record in another table. This type of relationship ensures that each entity is unique, allowing for clear and organized data representation. It is crucial for maintaining data integrity and is often enforced through primary and foreign keys, ensuring that the associations between tables reflect the real-world relationships they represent.
Participation Constraint: A participation constraint defines the minimum number of instances of one entity that must be associated with instances of another entity in a relationship. This concept helps to enforce data integrity by ensuring that certain relationships are mandatory or optional, which directly affects how data is modeled and structured in databases. Understanding participation constraints is crucial for effectively mapping relationships, as they play a significant role in defining how entities interact within the system and influence the enforcement of keys and other constraints.
Primary Key: A primary key is a unique identifier for each record in a database table, ensuring that no two rows can have the same key value. It plays a crucial role in maintaining the integrity of data by preventing duplicate entries and enabling efficient data retrieval.
Referential Integrity: Referential integrity is a database concept that ensures relationships between tables remain consistent and valid. It requires that any foreign key value in one table must either match an existing primary key value in another table or be null, thereby preventing orphaned records and maintaining the accuracy of data across related tables.
Superkey: A superkey is a set of one or more attributes that, when taken collectively, can uniquely identify a record in a relational database. It is an essential concept as it ensures that each entry in a table can be uniquely distinguished from all others, which is critical for maintaining data integrity and establishing relationships between tables.
Third Normal Form (3NF): Third Normal Form (3NF) is a database normalization condition that ensures all non-key attributes are functionally dependent only on the primary key and not on any other non-key attributes. This helps eliminate transitive dependencies, where a non-key attribute depends on another non-key attribute, thus reducing data redundancy and improving data integrity in relational databases.
Transitive dependency: Transitive dependency occurs when a non-key attribute depends on another non-key attribute, which in turn depends on a key attribute. This relationship can lead to redundancy and anomalies in data management. Understanding transitive dependencies is essential for structuring databases effectively, especially when establishing functional dependencies and ensuring that the database adheres to normal forms.
Unique Constraint: A unique constraint is a database rule that ensures all values in a specific column or a set of columns are distinct across all rows in a table. This is crucial for maintaining data integrity and helps prevent duplicate entries, which can lead to inconsistencies and errors within the database system.