Direction: Answer question based on the problem statement given below:
Identify primary key of table R with functional dependency set F
A
In database design, identifying the primary key is crucial for ensuring data integrity and structure. A primary key uniquely identifies each record in a table. It is a special type of candidate key selected to uniquely identify all tuples in a relation.
A candidate key is a minimal superkey. A superkey is a set of one or more attributes that, taken together, allow us to uniquely identify a tuple in the relation. Minimal means that no proper subset of the superkey is also a superkey.
Functional dependencies describe the relationships between attributes. An FD X → Y means that the value of attribute set X uniquely determines the value of attribute set Y. In our case, the given functional dependencies are:
The universal relation is $R(A, B, C, D, E)$. We need to find a primary key from the given options.
To find a primary key, we can calculate the closure of attribute sets. The closure of an attribute set X, denoted as $X^+$, is the set of all attributes that are functionally dependent on X. If $X^+$ contains all attributes of the relation R, then X is a superkey. To be a primary key, X must also be minimal (no proper subset of X is a superkey).
Let's calculate the closure for the attributes/sets of attributes from the options and also check if any single attribute could be a superkey.
We want to find $A^+$.
So, $A^+ = \{A, B, C, D, E\}$. Since $A^+$ contains all attributes of R, {$A$} is a superkey.
Is {$A$} minimal? The only proper subset of {$A$} is the empty set {}. The closure of the empty set is always empty. So, {$A$} is minimal. Therefore, {$A$} is a primary key.
Since we found that A is a primary key, any option containing A along with other attributes (like AD, AB) cannot be a *minimal* superkey, and therefore cannot be a primary key.
Let's verify the other options:
We want to find $(BC)^+$.
So, $(BC)^+ = \{B, C, D, E\}$. This does not contain attribute $A$. Thus, {$BC$} is not a superkey, and therefore not a primary key.
We want to find $(AD)^+$.
So, $(AD)^+ = \{A, B, C, D, E\}$. {$AD$} is a superkey. However, we already found that $A$ alone is a superkey ($A^+ = \{A, B, C, D, E\}$). Since $A$ is a proper subset of $AD$, $AD$ is not a minimal superkey, and thus not a primary key.
We want to find $(AB)^+$.
So, $(AB)^+ = \{A, B, C, D, E\}$. {$AB$} is a superkey. However, we already found that $A$ alone is a superkey ($A^+ = \{A, B, C, D, E\}$). Since $A$ is a proper subset of $AB$, $AB$ is not a minimal superkey, and thus not a primary key.
Based on the closure calculations, only {$A$} is a minimal superkey that determines all attributes of the relation R. Therefore, the primary key is A.
| Attribute Set | Closure | Is it a Superkey? | Is it Minimal? | Is it a Primary Key? |
|---|---|---|---|---|
| A | $\{A, B, C, D, E\}$ | Yes | Yes | Yes |
| BC | $\{B, C, D, E\}$ | No | N/A | No |
| AD | $\{A, B, C, D, E\}$ | Yes | No (A is a superkey) | No |
| AB | $\{A, B, C, D, E\}$ | Yes | No (A is a superkey) | No |
Thus, the primary key of relation R is A.
| Concept | Definition | Purpose |
|---|---|---|
| Attribute | A column in a table representing a property of the entity. | Stores specific pieces of data (e.g., Name, Age). |
| Relation (Table) | A set of tuples (rows) describing an entity, with attributes (columns). | Organizes data logically. |
| Functional Dependency (X → Y) | X determines Y; if two tuples have the same value for X, they must have the same value for Y. | Defines constraints and relationships between attributes. |
| Superkey | A set of attributes that uniquely identifies every tuple in a relation. | Ensures uniqueness of records. |
| Candidate Key | A minimal superkey (no proper subset is a superkey). | Potential choices for the primary key. |
| Primary Key | A chosen candidate key used to uniquely identify tuples. | The main identifier for records in a table, used for relationships and indexing. |
In some cases, there might be multiple candidate keys. To find all candidate keys, one systematic approach involves:
An alternative method involves finding the 'essential' attributes - those attributes that do not appear on the right-hand side (RHS) of any functional dependency. These attributes must be part of *every* candidate key. In our FDs: {A → BC, D → E, BC → D, A → D}, the attributes on the RHS are B, C, D, E. The only attribute not on the RHS is A. This suggests A must be part of any candidate key. Since $A^+$ already covers all attributes, A is the only candidate key.
Let R (ABCDEFGH) be a relation schema and F be the set of dependencies F = {A → B, ABCD → E, EF → G, EF → H and ACDF →EG}. The minimal cover of a set of functional dependencies is
In a database, a rule is defined as (P1 and P2) or P3? R1 (0.8) and R2 (0.3), where P1, P2, P3 are premises and R1. R2 are conclusions of rules with certainty factors (CF) 0.8 and 0.3 respectively. If any running program has produced P1, P2, P3 with CF as 0.5, 0.8. 0.2 respectively, find the CF of results on the basis of premises.
Minimal cover F’ of functional dependency set F is
Assume that given table R is decomposed in two tables
R 1(A, B, C) with functional dependency set f 1= {A → B, A → C} and R 2(A, D, E) with FD set F 2= {A → D, D → E}
Which of the following option is true w.r.t. given decomposition?Identify the redundant functional dependency in F