Free Test Decomposition and Loss... – Databas...

Q1: What is decomposition in database design?

A. Breaking a relation into two or more relations B. Combining two relations into one C. Adding new attributes to a relation D. Removing attributes from a relation

Q2: What is a lossless join decomposition?

A. A decomposition where the original relation can be perfectly reconstructed B. A decomposition where some data is lost C. A decomposition with duplicate tuples D. A decomposition that removes keys

Q3: Why is lossless join important?

A. To avoid loss of information in decomposed relations B. To improve query speed C. To create indexes D. To remove redundancy

Q4: Which type of dependency is mainly addressed by decomposition?

A. Functional dependency B. Multivalued dependency C. Join dependency D. No dependency

Q5: What is a dependency preservation property?

A. All functional dependencies are preserved after decomposition B. All keys are preserved C. No data is lost D. All tuples are unique

Q6: Is it always possible to have both lossless join and dependency preservation?

A. Not always B. Always C. Never D. Only for 1NF

Q7: Which method checks if decomposition is lossless?

A. Using attribute intersection and functional dependencies B. Counting tuples C. Using indexes D. Query optimization

Q8: What is a common problem if decomposition is not lossless?

A. Loss of tuples or introduction of spurious tuples B. Faster queries C. More indexes D. Data redundancy

Q9: What does the intersection of decomposed relations represent?

A. Common attributes used for joining B. Keys only C. No attributes D. Foreign keys only

Q10: How is lossless join property formally verified?

A. If the intersection attributes functionally determine at least one of the decomposed relations B. By checking primary keys C. By counting tuples D. By query testing

Q11: What is a spurious tuple?

A. An incorrect tuple generated by joining decomposed relations B. A valid tuple C. A deleted tuple D. An indexed tuple

Q12: What is a practical reason to perform decomposition?

A. To simplify design and reduce anomalies B. To increase redundancy C. To slow down queries D. To remove keys

Q13: Which normal form is often achieved through decomposition?

A. 3NF B. 1NF C. 2NF D. BCNF

Q14: What is a common technique to preserve dependencies after decomposition?

A. Including all dependencies in at least one decomposed relation B. Dropping keys C. Adding redundant data D. Not decomposing

Q15: What happens if dependency preservation is not maintained?

A. Some constraints cannot be enforced without joining relations B. Queries become faster C. Keys are lost D. All data is lost

Q16: Which decomposition property ensures no extra tuples are created during join?

A. Lossless join B. Dependency preservation C. Normalization D. Atomicity

Q17: What is the consequence of a lossy decomposition?

A. Incorrect query results due to spurious tuples B. Faster queries C. Increased data security D. Reduced redundancy

Q18: Which is an example of a lossless join decomposition?

A. Decomposing R(A,B,C) into R1(A,B) and R2(B,C) where B → A or B → C B. Randomly splitting tables C. Dropping keys D. Removing all dependencies

Q19: Which property must hold for every lossless decomposition?

A. At least one of the relations contains a key for the original relation B. Both relations must have the same number of attributes C. Relations must have no common attributes D. Relations must be identical

Q20: What is the role of join dependency in decomposition?

A. Generalization of multivalued dependencies affecting decomposition B. A simple functional dependency C. An index type D. Foreign key constraint

Q21: What is the goal of decomposition in database design?

A. To break a relation into smaller relations to reduce redundancy B. To combine multiple tables into one C. To add redundant data D. To remove all keys

Q22: What does lossless join mean?

A. Original relation can be exactly reconstructed by joining decomposed relations B. Some data is lost after decomposition C. Decomposition causes duplicate tuples D. Decomposition removes keys

Q23: Why is lossless join decomposition important?

A. To avoid data loss and ensure integrity B. To speed up query processing C. To reduce the number of attributes D. To create indexes

Q24: Which property ensures all functional dependencies are maintained after decomposition?

A. Dependency preservation B. Lossless join C. Normalization D. Atomicity

Q25: Is it always possible to have both lossless join and dependency preservation?

A. Sometimes a trade-off is necessary B. Always possible C. Never possible D. Only for 1NF

Q26: What is a spurious tuple?

A. An incorrect tuple generated by joining decomposed relations B. A valid tuple C. A deleted tuple D. A tuple with NULL values

Q27: How is lossless join verified?

A. If intersection of decomposed relations functionally determines one of them B. By counting tuples C. By checking primary keys D. By query optimization

Q28: What does the intersection of decomposed relations represent?

A. Common attributes used for joining B. Foreign keys C. Unique keys D. No attributes

Q29: Which type of dependency is mainly addressed by decomposition?

A. Functional dependency B. Multivalued dependency C. Join dependency D. No dependency

Q30: What happens if decomposition is lossy?

A. Loss of data or creation of spurious tuples B. Faster queries C. More indexes D. No data loss

Q31: Which normal form is commonly achieved through decomposition?

A. 3NF B. 1NF C. 2NF D. BCNF

Q32: What is the role of a key in lossless join decomposition?

A. One of the decomposed relations must contain a key for the original relation B. Both relations must contain foreign keys C. Keys are removed D. Keys are duplicated

Q33: Which is a sign of lossy decomposition?

A. Spurious tuples during join B. Faster queries C. Reduced redundancy D. No foreign keys

Q34: Which condition is required for a decomposition to be dependency preserving?

A. All original dependencies can be enforced on the decomposed relations B. All keys are preserved C. No keys are removed D. Relations have equal size

Q35: What is a join dependency?

A. A constraint specifying when a relation can be reconstructed by joining decompositions B. A key constraint C. A foreign key constraint D. An index

Q36: Why might a designer sacrifice dependency preservation?

A. To achieve lossless join B. To improve query performance C. To add indexes D. To increase redundancy

Q37: Which of the following is a common test for lossless join decomposition?

A. If the common attributes form a key for at least one decomposed relation B. If both relations have same number of attributes C. If both relations contain foreign keys D. If relations have no common attributes

Q38: What is the effect of lossy decomposition on database queries?

A. Queries may return incorrect or extra tuples B. Queries become faster C. Queries return fewer tuples D. No effect

Q39: Which of these is NOT a reason to perform decomposition?

A. To increase redundancy B. To reduce anomalies C. To simplify schema D. To enforce constraints

Q40: Which property is preferred but sometimes compromised during decomposition?

A. Dependency preservation B. Lossless join C. Normalization D. Atomicity

Quiz for Decomposition and Lossless Join

Q1: What is decomposition in database design?

Q2: What is a lossless join decomposition?

Q3: Why is lossless join important?

Q4: Which type of dependency is mainly addressed by decomposition?

Q5: What is a dependency preservation property?

Q6: Is it always possible to have both lossless join and dependency preservation?

Q7: Which method checks if decomposition is lossless?

Q8: What is a common problem if decomposition is not lossless?

Q9: What does the intersection of decomposed relations represent?

Q10: How is lossless join property formally verified?

Q11: What is a spurious tuple?

Q12: What is a practical reason to perform decomposition?

Q13: Which normal form is often achieved through decomposition?

Q14: What is a common technique to preserve dependencies after decomposition?

Q15: What happens if dependency preservation is not maintained?

Q16: Which decomposition property ensures no extra tuples are created during join?

Q17: What is the consequence of a lossy decomposition?

Q18: Which is an example of a lossless join decomposition?

Q19: Which property must hold for every lossless decomposition?

Q20: What is the role of join dependency in decomposition?

Q21: What is the goal of decomposition in database design?

Q22: What does lossless join mean?

Q23: Why is lossless join decomposition important?

Q24: Which property ensures all functional dependencies are maintained after decomposition?

Q25: Is it always possible to have both lossless join and dependency preservation?

Q26: What is a spurious tuple?

Q27: How is lossless join verified?

Q28: What does the intersection of decomposed relations represent?

Q29: Which type of dependency is mainly addressed by decomposition?

Q30: What happens if decomposition is lossy?

Q31: Which normal form is commonly achieved through decomposition?

Q32: What is the role of a key in lossless join decomposition?

Q33: Which is a sign of lossy decomposition?

Q34: Which condition is required for a decomposition to be dependency preserving?

Q35: What is a join dependency?

Q36: Why might a designer sacrifice dependency preservation?

Q37: Which of the following is a common test for lossless join decomposition?

Q38: What is the effect of lossy decomposition on database queries?

Q39: Which of these is NOT a reason to perform decomposition?

Q40: Which property is preferred but sometimes compromised during decomposition?