Query Processing

Question 1

is a request posed to a database
(or data system) for data retrieval,
updating, deletion, insertion, etc.

Answer 1

Query

Question 2

is the stage in a Database Management System (DBMS) where the system interprets and executes
a user’s query (usually written in SQL) to retrieve or modify data efficiently from the database

Answer 2

Query Processing

Question 3

It ensures all table names, columns, and keywords are valid.

Answer 3

Parsing and Translation

Question 4

The query is then translated into an internal form (like relational
algebra).

Answer 4

Parsing and Translation

Question 5

finds the most efficient way to execute the query.

Answer 5

Query Optimizer

Question 6

It considers multiple query plans (e.g., using indexes, join
methods, or sorting strategies).

Answer 6

Optimization

Question 7

The goal is to minimize cost, such as CPU time, disk I/O, and memory use

Answer 7

Optimization

Question 8

runs the optimized query plan

Answer 8

Execution

Question 9

It retrieves or modifies the data from the database storage

Answer 9

Execution

Question 10

Checks SQL correctness.

Answer 10

Parsing

Question 11

Chooses whether to use an index on age or scan the whole table

Answer 11

Optimization

Question 12

Retrieves matching records and returns the name field.

Answer 12

Execution

Question 13

refer to the factors a DBMS (Database Management System) uses to estimate how expensive a query plan is

Answer 13

Measures of Query Cost

Question 14

to decide the most efficient way to run a query

Answer 14

Measures of Query Cost

Question 15

Most important factor in cost estimation

Answer 15

Disk I/O Cost

Question 16

Measures how many disk accesses (reads/writes) are needed

Answer 16

Disk I/O Cost

Question 17

Measures the time spent by the processor

Answer 17

CPU Cost

Question 18

Usually smaller than disk I/O, but becomes important for in-memory
databases.

Answer 18

CPU Cost

Question 19

Measures how much RAM is used during query execution.

Answer 19

Memory Usage (Buffer Cost)

Question 20

Affects how much data can be processed in memory without writing to disk

Answer 20

Memory Usage (Buffer Cost)

Question 21

High memory use may cause paging or spilling to disk, increasing
total cost

Answer 21

Memory Usage (Buffer Cost)

Question 22

data may be stored on multiple servers.

Answer 22

Communication Cost (in Distributed Databases)

Question 23

Critical in distributed query processing and cloud databases.

Answer 23

Communication Cost (in Distributed Databases)

Question 23

The total time taken from query submission to result delivery.

Answer 23

Query Response Time

Question 24

It’s the end-user perspective measure.

Answer 24

Query Response Time

Question 25

Accessing data on disk

Answer 25

Disk I/O Cost

Question 26

Processing tuples and computations

Answer 26

CPU Cost

Question 27

Space used for intermediate results

Answer 27

Memory Cost

Question 28

Data transfer between servers

Answer 28

Communication Cost

Question 29

Total elapsed time for query result

Answer 29

Query Response Time

Question 30

is a relational algebra operation used to choose rows (tuples) from a table (relation) that satisfy a specific condition (predicate).

Answer 30

selection operation

Question 31

It’s one of the most basic and essential operations in query processing.

Answer 31

selection operation

Question 32

Combines multiple conditions using AND (∧), OR (∨), or NOT (¬)

Answer 32

Compound Selection

Question 33

Uses comparison operators like =, ≠, <, ≤, >, ≥.

Answer 33

Theta (θ) Selection

Question 34

is the step where the DBMS arranges tuples (rows) of a relation (table) in a specific order — usually ascending or descending — based on one or more attributes (columns).

Answer 34

Sorting

Question 35

It is a key operation used in many SQL queries and internal DBMS processes.

Answer 35

Sorting

Question 36

The DBMS divides the data into chunks (runs) that fit into main memory.

Answer 36

Sort Phase

Question 37

Each run is sorted in memory using an internal sorting algorithm (like quicksort).

Answer 37

Sort Phase

Question 38

The sorted runs are then written back to disk.

Answer 38

Sort Phase

Question 39

The sorted runs are merged together into larger sorted files.

Answer 39

Merge Phase

Question 40

The process continues until one fully sorted file remains.

Answer 40

Merge Phase

Question 41

is one of the most important — and often most expensive — operations in query processing.

Answer 41

join operation

Question 42

It combines tuples (rows) from two or more relations (tables) based on a related attribute between them

Answer 42

join operation

Question 43

A theta join where the condition uses equality (=) only.

Answer 43

Equi-Join

Question 44

Automatically joins tables based on common attribute names.

Answer 44

Natural Join

Question 45

Keeps all tuples from left table.

Answer 45

Left Outer Join

Question 46

Keeps all tuples from right table.

Answer 46

Right Outer Join

Question 47

Keeps all tuples from both tables, filling missing values with NULLs

Answer 47

Full Outer Join

Question 48

For every tuple in relation R, compare it with every tuple in S.

Answer 48

Nested-Loop Join

Question 49

Used when: Relations are small or one fits in memory.

Answer 49

Nested-Loop Join

Question 50

Processes one block of R at a time and compares it with all blocks of S.

Answer 50

Block Nested-Loop Join

Question 51

Used when: One relation is much smaller than the other.

Answer 51

Block Nested-Loop Join

Question 52

Used when: Join attribute in one relation is indexed.

Answer 52

Indexed Nested-Loop Join

Question 53

Both relations are sorted on the join attribute.

Answer 53

Sort-Merge Join

Question 54

Used when: Both relations are already sorted or can be sorted easily.

Answer 54

Sort-Merge Join

Question 55

divides both R and S into buckets based on the join attribute

Answer 55

Hash Join

Question 56

Used when: Join attribute is not sorted or indexed.

Answer 56

Hash Join

Question 57

refers to how the database system executes a relational algebra expression (or an SQL query) to produce the final result efficiently

Answer 57

evaluation of expression

Question 58

It’s the stage where the DBMS translates the logical query (what to do) into a physical plan (how to do it)

Answer 58

evaluation of expression

Question 59

is a combination of relational algebra operations

Answer 59

query expression

Question 60

Each operation produces an intermediate table stored temporarily

Answer 60

Materialized Evaluation

Question 61

Output of one operation is passed directly as input to the next

Answer 61

Pipelined Evaluation

Question 62

efers to the process of executing database queries directly in main memory (RAM) instead of relying primarily on slower disk-based storage

Answer 62

IN MEMORY QUERY PROCESSING

Question 63

This approach is central to modern high-performance DBMSs, especially in memory databases such as SAP HANA, Redis, and MemSQL.

Answer 63

IN MEMORY QUERY PROCESSING

Question 64

store data on disk and move it into memory buffers only when needed.

Answer 64

Traditional DBMSs

Question 65

Data is stored in main memory (RAM) instead of disk

Answer 65

Data Storage

Question 66

Usually column-oriented (columnar) rather than row-oriented for faster analytics.

Answer 66

Data Storage

Question 67

Data is periodically backed up to disk for durability

Answer 67

Data Storage

Question 68

Queries are processed entirely in memory, using CPU caches and vectorized operations

Answer 68

Query Execution

Question 69

The query engine uses algorithms optimized for memory (e.g., in memory joins, scans).

Answer 69

Query Execution

Question 70

Uses write-ahead logging (WAL) or checkpointing to ensure recovery in case of failure.

Answer 70

Transaction Management

Question 71

ACID properties are still maintained

Answer 71

Transaction Management

Question 72

SQL query is parsed and validated

Answer 72

Query Parsing

Question 73

Plan is generated and optimized

Answer 73

Query Optimization

Question 74

Operators run directly on memory data structures

Answer 74

Query Execution

Question 75

Results returned to user

Answer 75

Result Output

Question 76

Uses cost models for memory, not disk

Answer 76

Query Optimization

Question 77

Uses memory-resident indexes and vectorized execution

Answer 77

Query Execution

Question 78

Minimal delay since data is already in memory

Answer 78

Result Output

Question 79

dominant cost (since disk I/O is minimal).

Answer 79

CPU Time

Question 80

how fast data can be transferred between memory and CPU.

Answer 80

Memory Bandwidth

Question 81

how efficiently CPU cache is used.

Answer 81

Cache Utilization

Question 82

multiple queries sharing memory resource

Answer 82

Concurrency Overhead