Podcast
Questions and Answers
What happens when an attribute is removed from the left-hand side of a functional dependency if it is extraneous?
What happens when an attribute is removed from the left-hand side of a functional dependency if it is extraneous?
- The set of dependencies remains equivalent. (correct)
- The dependency remains valid.
- The dependency must be augmented.
- The dependency becomes invalid.
In the process of finding a minimal cover, what step is taken after identifying that a dependency can be separated into individual dependencies?
In the process of finding a minimal cover, what step is taken after identifying that a dependency can be separated into individual dependencies?
- Check for equivalence between the original and modified sets. (correct)
- Determine if any attributes are redundant.
- Augment the dependencies on both sides.
- Eliminate redundant dependencies.
Which functional dependency set was derived from the original set E: {B → A, D → A, AB → D}?
Which functional dependency set was derived from the original set E: {B → A, D → A, AB → D}?
- {B → A, D → A, AB → D, B → D}
- {A → B, D → A, B → D}
- {B → D, D → A, A → B}
- {B → A, D → A, B → D} (correct)
What is the rule used to replace AB → D with B → D?
What is the rule used to replace AB → D with B → D?
What is a situation where a functional dependency can be considered redundant?
What is a situation where a functional dependency can be considered redundant?
Why can Y, a proper subset of X, not replace X in a dependency X → A?
Why can Y, a proper subset of X, not replace X in a dependency X → A?
What is the first step in finding a minimal cover for a set of functional dependencies?
What is the first step in finding a minimal cover for a set of functional dependencies?
What is the minimum cover of the given set E: {B → A, D → A, AB → D}?
What is the minimum cover of the given set E: {B → A, D → A, AB → D}?
What do functional dependencies (FDs) specify in relational designs?
What do functional dependencies (FDs) specify in relational designs?
Which of the following statements correctly defines the relationship represented by X → Y?
Which of the following statements correctly defines the relationship represented by X → Y?
Which example best illustrates a functional dependency?
Which example best illustrates a functional dependency?
What must be true for an attribute set X to functionally determine another attribute set Y?
What must be true for an attribute set X to functionally determine another attribute set Y?
Which condition is necessary for a set of attributes K to be a key in the schema R?
Which condition is necessary for a set of attributes K to be a key in the schema R?
How can functional dependencies be visually represented?
How can functional dependencies be visually represented?
Which inference rule states that if X determines YZ, then X determines both Y and Z?
Which inference rule states that if X determines YZ, then X determines both Y and Z?
In order to establish functional dependencies from data instances, what is required?
In order to establish functional dependencies from data instances, what is required?
What is a characteristic feature of a dense index?
What is a characteristic feature of a dense index?
What is the closure of a set F of functional dependencies?
What is the closure of a set F of functional dependencies?
What characteristic does a valid functional dependency imply about two tuples in a relation?
What characteristic does a valid functional dependency imply about two tuples in a relation?
Which of the following describes a clustering index?
Which of the following describes a clustering index?
What does the closure X+ represent with respect to a set of functional dependencies F?
What does the closure X+ represent with respect to a set of functional dependencies F?
If the set of functional dependencies includes FD1: Classid → Course#, Instr_name, Credit_hrs, Text, Publisher, Classroom, Capacity, what can be concluded?
If the set of functional dependencies includes FD1: Classid → Course#, Instr_name, Credit_hrs, Text, Publisher, Classroom, Capacity, what can be concluded?
Which inference rule applies if you have X determining Y and X determining Z, thus allowing you to conclude X determines YZ?
Which inference rule applies if you have X determining Y and X determining Z, thus allowing you to conclude X determines YZ?
Which of the following statements is true about secondary indexes?
Which of the following statements is true about secondary indexes?
What is the initial step in the algorithm to determine the closure of X under functional dependencies F?
What is the initial step in the algorithm to determine the closure of X under functional dependencies F?
Which of the following would be a feasible solution for managing overflow records in primary indexes?
Which of the following would be a feasible solution for managing overflow records in primary indexes?
In the closure determination algorithm, what denotes that the process should continue iterating?
In the closure determination algorithm, what denotes that the process should continue iterating?
What is the function of the Pseudotransitivity rule in relation to sets of functional dependencies?
What is the function of the Pseudotransitivity rule in relation to sets of functional dependencies?
What is the main purpose of a secondary index?
What is the main purpose of a secondary index?
In the context of primary indexes, what does 'P(i)' represent?
In the context of primary indexes, what does 'P(i)' represent?
What major problem is associated with primary indexes during data modifications?
What major problem is associated with primary indexes during data modifications?
What is a disadvantage of a sparse index compared to a dense index?
What is a disadvantage of a sparse index compared to a dense index?
What is the result of applying a NATURAL JOIN on EMPLOYEE_1 and EMPLOYEE_3?
What is the result of applying a NATURAL JOIN on EMPLOYEE_1 and EMPLOYEE_3?
What defines a dangling tuple in the context of the EMPLOYEE relation?
What defines a dangling tuple in the context of the EMPLOYEE relation?
Which representation avoids dangling tuples in regard to department assignments?
Which representation avoids dangling tuples in regard to department assignments?
What format do the relations EMPLOYEE_1 and EMPLOYEE_2 have regarding their attributes?
What format do the relations EMPLOYEE_1 and EMPLOYEE_2 have regarding their attributes?
How does the transformation of EMPLOYEE into EMPLOYEE_3 affect data integrity?
How does the transformation of EMPLOYEE into EMPLOYEE_3 affect data integrity?
What possible issue arises when using NULL values in the EMPLOYEE relation?
What possible issue arises when using NULL values in the EMPLOYEE relation?
What is a key characteristic of the EMPLOYEE_2 relation?
What is a key characteristic of the EMPLOYEE_2 relation?
Which employees would not appear in the result of a NATURAL JOIN between EMPLOYEE_1 and EMPLOYEE_2?
Which employees would not appear in the result of a NATURAL JOIN between EMPLOYEE_1 and EMPLOYEE_2?
Study Notes
Functional dependencies
- Functional dependencies (FDs) are used to measure how good a relational database design is.
- FDs are constraints derived from the real-world interrelationship between attributes.
- A set of attributes (X) functionally determines another set of attributes (Y) if the value of X determines a unique value for Y.
- Example of an FD constraint: SSN determines employee name (SSN → ENAME).
Defining FDs
- X → Y holds if whenever two tuples have the same value for X, they must have the same value for Y.
- The constraint of X → Y applies to every relation instance.
Examples of FD Constraints
- SSN → ENAME: Social Security number determines employee name.
- PNUMBER → {PNAME, PLOCATION}: Project number determines project name and location.
- {SSN, PNUMBER} → HOURS: Employee SSN and project number determine hours per week worked on the project.
- If K is a key of R, then K functionally determines all attributes in R.
Inference Rules for FDs
- Decomposition: If X → YZ, then X → Y and X → Z.
- Union: If X → Y and X → Z, then X → YZ.
- Pseudotransitivity: If X → Y and WY → Z, then WX → Z.
Closure
- The closure of a set F of FDs (F+) is the set of all FDs inferred from F.
- The closure of a set of attributes X with respect to F (X+) is the set of all attributes that are functionally determined by X.
Minimal Sets of FDs
- A set of FDs is minimal if no FD can be removed or replaced with a simpler one without changing the meaning of the set.
- Algorithm 15.2 finds a minimal cover F for a set of FDs E.
- There are several steps to finding a minimal cover including replacing dependencies, removing redundant attributes, and removing redundant dependencies.
Problems with Null Values and Dangling Tuples
- There can be problems with null values in a database, especially when joining tables together.
- Dangling tuples can occur when a tuple in one table does not have a matching tuple in another table, resulting in incomplete results.
Primary Indexes
- Ordered file with two fields: primary key and pointer to a disk block.
- One index entry for each block in the data file.
- Indexes can be dense or sparse:
- Dense index: index entry for every search key value in the data file.
- Sparse index: entries for only some search values.
Clustering Indexes
- File records are physically ordered on a nonkey field.
- Ordered file with two fields: clustering field and disk block pointer.
Secondary Indexes
- Provide secondary means of accessing a data file.
- Ordered file with two fields: indexing field and block pointer/record pointer.
- Usually need more storage space and longer search time than primary indexes.
- Improve search time for arbitrary records.
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Description
This quiz explores the concept of functional dependencies in relational database design. Learn how attributes interrelate and the significance of FDs in ensuring data integrity. Test your understanding with real-world examples and constraints.
