Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

What undesirable dependencies are avoided when a relation is in \(2 \mathrm{NF}\) ?

Short Answer

Expert verified
Second Normal Form (2NF) helps to avoid undesirable dependencies in a database by eliminating partial dependencies. When a database is in 2NF, all non-key attributes are fully functionally dependent on the primary key, ensuring there are no attributes that depend on only part of the primary key.

Step by step solution

01

Understand Second Normal Form (2NF)

The Second Normal Form (2NF) is a level of database normalization which helps to reduce redundancy and improve data integrity. It is achieved when a database scheme meets all the rules of the First Normal Form (1NF) and there are no partial dependencies of non-key attributes on the primary key.
02

Define 'Undesirable Dependencies'

An undesirable dependency in a database is usually a partial dependency. A partial dependency occurs when a non-key attribute depends on a part, but not all, of a composite primary key. This can lead to anomalies and inconsistencies within the data stored.
03

Discuss how 2NF avoids these dependencies

When a relation is in 2NF, all non-key attributes are fully functionally dependent on the primary key. This means that there are no partial dependencies within the database relation. Therefore, by being in 2NF, a relation avoids these undesirable dependencies.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Database Normalization
Database normalization is the process of structurally designing a database to minimize duplication and avoid undesirable data manipulation scenarios. It involves dividing databases into multiple tables and defining relationships between them to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency.

Normal forms are standards that must be met to ensure database normalization. Starting with the First Normal Form (1NF), which requires the elimination of duplicate columns from the same table, database designs evolve through several normalization stages depending on their complexity. The 2NF further improves on this by addressing column dependencies throughout the tables.
Partial Dependency
Partial dependency is a concept that plays a pivotal role in database structure optimization. It occurs when attribute data depends only on a portion of a composite primary key rather than the whole key. This can result in redundancy and anomalies, particularly in the context of database operations like insertions, deletions, and updates.

For a table to be in 2NF, it must eliminate any partial dependency. This is crucial because partial dependencies can lead to data integrity issues where the same information can be represented inconsistently across the database, thus leading to potential errors in reporting and data aggregation.
Data Integrity
Data integrity is the accuracy, consistency, and reliability of data stored in a database. It is an essential aspect of database design and operation, which must be safeguarded throughout the data life cycle. By adhering to normalization practices, specifically moving to 2NF, databases can maintain data integrity. In addition, constraints like primary keys, foreign keys, and unique constraints also play vital roles. These constraints ensure that relationships between tables make sense and that data is entered correctly, preventing duplication and data integrity breaches.
Functional Dependency
Functional dependency is a cornerstone concept of database normalization. It refers to the relationship between two sets of attributes such that the value of one attribute (or group of attributes) is determined by the value of another. When an attribute can uniquely determine another attribute, the latter is said to be functionally dependent on the former.

For instance, in a simple table where every employee has a unique employee ID, the employee's name and address are functionally dependent on the employee ID since the ID will uniquely identify the other information. Ensuring that all attributes in a table are fully functionally dependent on the primary key for that table is a requirement for 2NF, thereby preventing partial dependency and related data anomalies.

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

What is meant by the completeness and soundness of Armstrong's inference rules?

, Date_sold, Salesman#, Commission\%, Discount_amt) Assume that a car may be sold by multiple salesmen, and hence \(\\{\mathr… # Consider the following relation: CAR_SALE(Car#, Date_sold, Salesman#, Commission\%, Discount_amt) Assume that a car may be sold by multiple salesmen, and hence \)\\{\mathrm{CAR} \\#,\( SALESMAN is the primary key. Additional dependencies are Date_sold \)\rightarrow\( Discount amt and Salesman# \)\rightarrow\( Commission\% Based on the given primary key, is this relation in \)1 \mathrm{NF}, 2 \mathrm{NF}\(, or \)3 \mathrm{NF}$ ? Why or why not? How would you successively normalize it completely?

Why should nulls in a relation be avoided as far as possible? Discuss the problem of spurious tuples and how we may prevent it.

, Odate, Cust#, Total_amount) ORDER- ITEM(O#, I#, Qty_order… # Consider the following relations for an order-processing application database at \(\mathrm{ABC},\) Inc. ORDER (O#, Odate, Cust#, Total_amount) ORDER-ITEM(O#, I#, Qty_ordered, Total_price, Discount\%) Assume that each item has a different discount. The Total_PRICE refers to one item, OOATE is the date on which the order was placed, and the Total_AMOUNT is the amount of the order. If we apply a natural join on the relations ORDER-ITEM and ORDER in this database, what does the resulting relation schema look like? What will be its key? Show the FDs in this resulting relation. Is it in \(2 \mathrm{NF}\) ? Is it in \(3 \mathrm{NF}\) ? Why or why not? (State assumptions, if you make any.)

Prove or disprove the following inference rules for functional dependencies. A proof can be made either by a proof argument or by using inference rules IR1 through IR3. A disproof should be performed by demonstrating a relation instance that satisfies the conditions and functional dependencies in the left-hand side of the inference rule but does not satisfy the dependencies in the right-hand side. a. \(\\{W \rightarrow Y, X \rightarrow Z\\} \vDash\\{W X \rightarrow Y\\}\) b. \(\\{X \rightarrow Y\\}\) and \(Y \supseteq Z \vDash\\{X \rightarrow Z\\}\) ?. \(\\{X \rightarrow Y, X \rightarrow W, W Y \rightarrow Z\\} \vDash\\{X \rightarrow Z\\}\) d. \(\\{X Y \rightarrow Z, Y \rightarrow W\\} \vDash\\{X W \rightarrow Z\\}\) e. \(\\{X \rightarrow Z, Y \rightarrow Z\\} \vDash\\{X \rightarrow Y\\}\) f. \(\quad\\{X \rightarrow Y, X Y \rightarrow Z\\} \vDash\\{X \rightarrow Z\\}\) \(\mathrm{g} .\\{X \rightarrow Y, Z \rightarrow W\\} \vDash\\{X Z \rightarrow Y W\\}\) h. \(\\{X Y \rightarrow Z, Z \rightarrow X\\} \vDash\\{Z \rightarrow Y\\}\) ¡. \(\\{X \rightarrow Y, Y \rightarrow Z\\} \vDash\\{X \rightarrow Y Z\\}\) j. \(\quad\\{X Y \rightarrow Z, Z \rightarrow W\\} \vDash\\{X \rightarrow W\\}\)

See all solutions

Recommended explanations on Computer Science Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free