Q#1: Query processing in DBMS refers to:
(A) Translating and executing queries efficiently
(B) Creating tables
(C) Encrypting data
(D) Backup operations
Answer: (A) Translating and executing queries efficiently
Q#2: The main goal of query processing is to:
(A) Minimize response time and resource usage
(B) Normalize tables
(C) Encrypt database
(D) Store backups
Answer: (A) Minimize response time and resource usage
Q#3: Query processing involves:
(A) Parsing, optimization, and execution
(B) Only execution
(C) Only parsing
(D) Only normalization
Answer: (A) Parsing, optimization, and execution
Q#4: Query parsing checks for:
(A) Syntax and semantics of the query
(B) Only syntax
(C) Only semantics
(D) Storage requirements
Answer: (A) Syntax and semantics of the query
Q#5: Query optimization aims to:
(A) Find the most efficient execution plan
(B) Encrypt queries
(C) Normalize tables
(D) Backup database
Answer: (A) Find the most efficient execution plan
Q#6: Logical query plan represents:
(A) Sequence of relational algebra operations
(B) Physical storage structure
(C) Backup plan
(D) Encryption plan
Answer: (A) Sequence of relational algebra operations
Q#7: Physical query plan specifies:
(A) Access methods and join algorithms to execute query
(B) Only table names
(C) Only index names
(D) Backup methods
Answer: (A) Access methods and join algorithms to execute query
Q#8: Heuristic query optimization uses:
(A) Rule-based transformations
(B) Cost estimation
(C) Random selection
(D) Backup methods
Answer: (A) Rule-based transformations
Q#9: Cost-based query optimization considers:
(A) CPU, I/O, and memory cost
(B) Syntax only
(C) Semantics only
(D) Backup frequency
Answer: (A) CPU, I/O, and memory cost
Q#10: Join operation can be executed using:
(A) Nested-loop join
(B) Sort-merge join
(C) Hash join
(D) All of the above
Answer: (D) All of the above
Q#11: Nested-loop join is efficient when:
(A) One table is small
(B) Both tables are huge
(C) Tables are sorted
(D) Only one row exists
Answer: (A) One table is small
Q#12: Sort-merge join requires:
(A) Both tables to be sorted on join attribute
(B) No sorting
(C) Only indexes
(D) Hash function
Answer: (A) Both tables to be sorted on join attribute
Q#13: Hash join is efficient when:
(A) Tables fit into memory or hash buckets
(B) Tables are very small
(C) Tables are already sorted
(D) Only one table exists
Answer: (A) Tables fit into memory or hash buckets
Q#14: Query execution plan (QEP) is:
(A) Detailed procedure chosen by optimizer to execute query
(B) Backup plan
(C) Encryption method
(D) Table structure
Answer: (A) Detailed procedure chosen by optimizer to execute query
Q#15: Selection operation can be optimized using:
(A) Indexes
(B) Sorting
(C) Hashing
(D) All of the above
Answer: (A) Indexes
Q#16: Projection operation can be optimized using:
(A) Eliminating duplicate elimination early
(B) Index only
(C) Hash only
(D) Sorting only
Answer: (A) Eliminating duplicate elimination early
Q#17: Query decomposition divides:
(A) Complex queries into simpler sub-queries
(B) Tables into columns
(C) Backup into partitions
(D) Indexes into sub-indexes
Answer: (A) Complex queries into simpler sub-queries
Q#18: Pipelining in query execution:
(A) Streams intermediate results to next operation
(B) Stores all results in disk first
(C) Encrypts query
(D) Deletes temporary tables
Answer: (A) Streams intermediate results to next operation
Q#19: Materialized views can help:
(A) Speed up query execution
(B) Encrypt queries
(C) Normalize tables
(D) Backup database
Answer: (A) Speed up query execution
Q#20: Statistics on tables (like cardinality) help in:
(A) Cost-based query optimization
(B) Syntax checking
(C) Backup planning
(D) Encryption
Answer: (A) Cost-based query optimization
Q#21: Query execution order can affect:
(A) Performance and resource usage
(B) Syntax
(C) Backup frequency
(D) Data storage format
Answer: (A) Performance and resource usage
Q#22: Access paths include:
(A) Full table scan, index scan, index-only scan
(B) Backup paths
(C) Encryption paths
(D) Normalization paths
Answer: (A) Full table scan, index scan, index-only scan
Q#23: Full table scan is used when:
(A) No suitable index exists
(B) Index exists
(C) Table is empty
(D) Table is encrypted
Answer: (A) No suitable index exists
Q#24: Index-only scan is possible when:
(A) All needed columns are in the index
(B) Only primary key exists
(C) Table is empty
(D) Table is unsorted
Answer: (A) All needed columns are in the index
Q#25: Join order in query affects:
(A) Execution cost significantly
(B) Syntax only
(C) Backup strategy
(D) Encryption
Answer: (A) Execution cost significantly
Q#26: Nested sub-queries can be optimized by:
(A) Transforming into joins
(B) Ignoring them
(C) Encrypting queries
(D) Backing up table
Answer: (A) Transforming into joins
Q#27: Query rewriting includes:
(A) Transforming queries for better performance
(B) Changing table structure
(C) Encrypting queries
(D) Backup operations
Answer: (A) Transforming queries for better performance
Q#28: Cardinality estimation helps in:
(A) Predicting number of rows in intermediate results
(B) Encrypting database
(C) Normalization
(D) Backup scheduling
Answer: (A) Predicting number of rows in intermediate results
Q#29: Cost estimation in query processing considers:
(A) CPU, I/O, and memory usage
(B) Syntax only
(C) Backup time only
(D) Encryption overhead only
Answer: (A) CPU, I/O, and memory usage
Q#30: Main goal of query processing is:
(A) Efficient execution of queries with minimal resources
(B) Encrypt database
(C) Normalize tables
(D) Backup tables
Answer: (A) Efficient execution of queries with minimal resources