A dependency is a constraint in the database and is used to show the relationship between two or more table attributes. Although database dependencies are universal, they are known to confuse both students and database specialists.
In this article, we will cover one of the popular dependencies: the Join dependency in DBMS. Fortunately, they're easier than they appear; we will start by discussing what dependencies are and why they are essential in DBMS.
Dependency in DBMS
When data from one database table uniquely identifies data from another stored in the same table, then dependencies are used to define the relationship between them. Dependencies provide basic building blocks for the normalisation of the databases.
Normalisation is used to organise the data in the databases efficiently. It decreases redundant data and removes undesired traits like Insertion, Update, and Deletion Anomalies. So, dependency in DBMS is important for the normalisation of databases. Let’s discuss some of the pros of dependency in DBMS.
Advantages of Dependency in DBMS
Some advantages of dependency in DBMS are as follows:
It enables you to store data efficiently and maintain data quality in DBMS.
Dependency in DBMS prevents data duplication, commonly known as redundant data in databases.
It enables you to spot improper database designs.
Dependency in DBMS contributes to clarifying the purposes and constraints imposed by databases.
It offers the fundamental components needed for table normalisation in DBMS.
What are Join Dependencies in DBMS?
A Join dependency in DBMS is a constraint in DBMS. A table(Suppose R) is considered a join dependency if it can be recreated by simply connecting multiple tables, each containing a subset of the R's attributes.
The 5NF(fifth normal form), or project join normal form, is based on Join dependency. We can say that a table T is in the fifth normal form if the T is already in the fourth normal form(4 NF) and T does not contain any join dependencies.
It can only be satisfied if the relevant relation joins a certain number of projections.
Let T be a relational schema and T1, T2, … TN be a lossless decomposition of T. The relation r(T) satisfies the join dependency if and only if every legal relation r(T) equals the join of its projections on T1, T2, … TN.
In other words, the relations in a Join dependency are independent of one another. It is like a generalisation of multivalued dependencies.
A join dependency is considered trivial if any relational schemas(Ti) in a join dependency are equivalent to the original relation T. For example, if the relation T3 is equal to the original relation T, then the join dependency will be trivial.
We will understand the Join dependency in DBMS by exploring various examples.
Let's consider an example of some particular types of join dependencies that can be used to identify data dependencies in hierarchical data structures.
The above data is hierarchical information from the college database. As shown in the database, the departments and students of those departments depend on the college, not the college's infrastructure. A college has multiple departments, so functional dependencies are insufficient to express the dependency between the college and the department. We will use the multivalued dependency in this case.
Here,
College ->-> Infrastructure or College ->-> Department are multivalued dependencies.
Using first-order hierarchical decomposition, we could more naturally describe the data dependencies contained in hierarchical data structures. In DBMS, decomposition involves dividing a relation into several relations in order to transform it into the correct normal form. It aids in eliminating redundant data, discrepancies, and various anomalies.
As we know that the Join dependency is the generalisation of the multivalued dependency.
So, using a lossless join, we can generalise and store the college database in the following manner:
The relations, as mentioned above, are not 5NF since they are joined dependent. In other words, our original relation table Ninja is identical to a join relation of the three tables mentioned before.
Example 3
Given a library model that keeps the records of books in table Book = (book_number, book_name, author_name, category).
One can deduce the following relationships:
The book number determines the book's name.
The author's name depends on the book number.
The category depends on the book number.
The following join dependency exists because the relationships are independent: *((book-number, book-name), (book-number, author-name), (book-number, category)).
However, if every book has a separate category, there may be a join-dependency like *((book-number, book-name), (book-number, author-name), (book-number, category), (book-name, category)), although *((book-number, book-name, category), (book-number, book-name)) would also be acceptable. This makes it clear that normalising a database strategy requires more than simply a join dependency.
Join Dependencies and Fifth Normal Form (5NF)
Let us some important points regarding join dependency:
It refers to a situation where a table can be reconstructed by joining multiple smaller tables together using certain attributes as keys
It deals with the way data is divided and stored in tables to minimize redundancy and anomalies
The aim of it is to eliminate redundancy and anomalies related to the decomposition of data into smaller tables
It is primarily concerned with how tables can be combined (joined) to retrieve the original data without loss or duplication
It helps in reducing data redundancy and maintaining data integrity
Achieving a complete join dependency can lead to complex and numerous joins, which may affect query performance
Let us some important points regarding the Fifth Normal Form (5NF):
It is a level of normalization that deals with the elimination of join dependencies between attributes in a table
It addresses the removal of complex join dependencies and ensures that each attribute is functionally dependent on the entire primary key
The aim of it is to further eliminate join dependencies beyond the third and fourth normal forms
It ensures that a table's attributes are as independent as possible, preventing cases where an attribute depends on a combination of other attributes
It enhances data integrity by minimizing dependencies and promoting a more modular and independent structure
Achieving 5NF might require the creation of additional tables, which can lead to more complex schema designs
When is a Join Dependency trivial?
A join dependency is considered trivial when it can be satisfied by the individual tables' primary keys without requiring additional attributes or tables. In other words, a trivial join dependency can be deduced directly from the keys of the involved tables, and no extra relationships or combinations are needed. This means that the relationship between the tables is straightforward and can be determined solely based on their primary key attributes.
Trivial join dependencies are simple and do not involve complex interactions or dependencies between tables, making them easier to manage and understand in a database system.
Characteristics of Join Dependency in DBMS?
The main characteristics of join dependency are as follows:
Table Relationships: It indicates how tables are interrelated based on common attributes. It defines how data from separate tables can be combined to reconstruct a specific table.
Data Consistency: It contributes to maintaining data consistency and integrity by avoiding redundancy and duplication of information. This helps prevent anomalies during data retrieval and modification.
Query Optimization: While it enhances data integrity, it can also impact query complexity. More complex join dependencies might lead to intricate query structures, affecting query performance and execution time.
Database Structure: It influences the design of the database schema. Tables need to be organized in a way that allows for meaningful joins and relationships to achieve the desired data representation and retrieval efficiency.
Normalization: It is closely related to normalization, a process aimed at structuring databases to minimize data redundancy and maintain data integrity. Ensuring proper normalization helps in managing join dependencies effectively.
Data Retrieval: While it aids in combining data from multiple tables, it can also impact how data is retrieved. Query optimization techniques are often employed to ensure efficient data retrieval despite complex join dependencies.
Frequently Asked Questions
What is the difference between join dependency and 5NF?
Join dependency and Fifth Normal Form (5NF) are concepts in database normalization. Join dependency combines tables to prevent anomalies, while 5NF removes complex dependencies within one table. Join dependency enhances data integrity through structured tables, while 5NF promotes attribute independence. Both contribute to normalized databases, with join dependency affecting queries and 5NF enhancing attributes.
What is decomposition in DBMS?
In DBMS, decomposition involves dividing a relation into several relations in order to transform it into the correct normal form. It aids in eliminating redundant data, discrepancies, and various anomalies.
How many types of decomposition is there in DBMS?
There are two types of decomposition in DBMS. The lossy and lossless decompositions. Lossy decomposition occurs when a relation gets split up into several other relational schemas in a way that makes it difficult to retrieve the original relation. Lossless decomposition preserves all information from the original relationship.
What is normalisation in DBMS?
Normalisation is used to organise the data in the databases efficiently. It decreases redundant data and removes undesired traits like Insertion, Update, and Deletion Anomalies. Dependencies in DBMS are important for the normalisation of databases.
Conclusion
In this article, we explored Join dependency in DBMS. Join dependency is the generalisation of multivalued dependency and is helpful for table normalisation.
We hope this article helps you. You can visit more articles related to Join and dependencies.
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