1. . Query processing in DBMS refers to:
(A) The steps involved in converting a high-level query into an efficient execution plan
(B) Compressing tables
(C) Encrypting data
(D) Deleting old records
2. . The main goal of query optimization is to:
(A) Compress tables
(B) Minimize resource usage and execution time
(C) Encrypt tables
(D) Delete old records
3. . Query evaluation plan is:
(A) A sequence of operations that produces the result of a query
(B) A backup file
(C) Compressed table
(D) Encrypted data
4. . Logical query optimization involves:
(A) Transforming a query into an equivalent but more efficient form
(B) Encrypting the query
(C) Compressing the query
(D) Deleting old data
5. . Physical query optimization involves:
(A) Selecting the best algorithm and access paths to execute the query
(B) Encrypting tables
(C) Compressing tables
(D) Deleting old records
6. . Relational algebra plays a key role in:
(A) Deleting old data
(B) Encrypting tables
(C) Compressing tables
(D) Query optimization by representing queries as algebraic expressions
7. . Cost-based query optimization selects a query plan based on:
(A) Compressed data
(B) Estimated cost in terms of I/O, CPU, and memory usage
(C) Encrypted data
(D) Backup frequency
8. . Heuristic query optimization uses:
(A) Cost estimation
(B) Rules of thumb like pushing selections/projections down
(C) Compression techniques
(D) Encryption techniques
9. . Join algorithms include:
(A) Compression join
(B) Nested-loop join, Sort-merge join, Hash join
(C) Encryption join
(D) Backup join
10. . Nested-loop join is suitable when:
(A) Data is encrypted
(B) Both relations are very large only
(C) One relation is small and indexes are available on the other relation
(D) Data is compressed
11. . Sort-merge join is efficient when:
(A) Data is encrypted
(B) Both relations are already sorted or can be sorted efficiently
(C) Data is compressed
(D) Only small relations exist
12. . Hash join is efficient when:
(A) Data is compressed
(B) Data is encrypted
(C) Relations are large and hash tables can fit in memory
(D) Only small relations exist
13. . Selection operation in query processing refers to:
(A) Choosing columns
(B) Choosing rows that satisfy a given condition
(C) Compressing tables
(D) Encrypting tables
14. . Projection operation in query processing refers to:
(A) Choosing rows
(B) Choosing specific columns from a table
(C) Compressing tables
(D) Encrypting tables
15. . Pipelining in query execution allows:
(A) Passing intermediate results directly to the next operation without storing on disk
(B) Compressing intermediate results
(C) Encrypting results
(D) Backup of intermediate results
16. . Materialized views help query optimization by:
(A) Encrypting tables
(B) Storing precomputed results for faster retrieval
(C) Compressing tables
(D) Deleting old records
17. . Access paths in query optimization include:
(A) Encryption only
(B) Compression only
(C) Table scan, index scan, and index range scan
(D) Backup paths
18. . Query rewrite techniques involve:
(A) Deleting old queries
(B) Encrypting queries
(C) Compressing queries
(D) Rewriting queries for more efficient evaluation without changing the result
19. . Cost estimation for query optimization considers:
(A) I/O operations, CPU usage, memory usage, and network costs
(B) Compression ratio
(C) Encryption overhead
(D) Backup frequency
20. . The main goal of Query Processing & Optimization is to:
(A) Encrypt data
(B) Compress tables
(C) Execute queries efficiently while minimizing resource usage
(D) Delete old records