SQL Interview Questions (0-5 Year Experience)!!
Are you preparing for a SQL interview?
Here are some essential SQL concepts to review:
πππ¬π’π πππ ππ¨π§πππ©ππ¬:
1. What is SQL, and why is it important in data analytics?
2. Explain the difference between
3. What is the difference between
4. How do you use
5. Write a query to find duplicate records in a table.
6. How do you retrieve unique values from a table using SQL?
7. Explain the use of aggregate functions like
8. What is the purpose of a
ππ§πππ«π¦πππ’πππ πππ:
1. Write a query to find the second-highest salary from an employee table.
2. What are subqueries and how do you use them?
3. What is a Common Table Expression (CTE)? Give an example of when to use it.
4. Explain window functions like
5. How do you combine results of two queries using
6. What are indexes in SQL, and how do they improve query performance?
7. Write a query to calculate the total sales for each month using
πππ―ππ§πππ πππ:
1. How do you optimize a slow-running SQL query?
2. What are views in SQL, and when would you use them?
3. What is the difference between a stored procedure and a function in SQL?
4. Explain the difference between
5. What are windowing functions, and how are they used in analytics?
6. How do you use
7. How do you handle NULL values in SQL, and what functions help with that (e.g.,
Here you can find essential SQL Interview Resourcesπ
https://t.iss.one/mysqldata
Like this post if you need more πβ€οΈ
Hope it helps :)
Are you preparing for a SQL interview?
Here are some essential SQL concepts to review:
πππ¬π’π πππ ππ¨π§πππ©ππ¬:
1. What is SQL, and why is it important in data analytics?
2. Explain the difference between
INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN. 3. What is the difference between
WHERE and HAVING clauses? 4. How do you use
GROUP BY and HAVING in a query? 5. Write a query to find duplicate records in a table.
6. How do you retrieve unique values from a table using SQL?
7. Explain the use of aggregate functions like
COUNT(), SUM(), AVG(), MIN(), and MAX(). 8. What is the purpose of a
DISTINCT keyword in SQL? ππ§πππ«π¦πππ’πππ πππ:
1. Write a query to find the second-highest salary from an employee table.
2. What are subqueries and how do you use them?
3. What is a Common Table Expression (CTE)? Give an example of when to use it.
4. Explain window functions like
ROW_NUMBER(), RANK(), and DENSE_RANK(). 5. How do you combine results of two queries using
UNION and UNION ALL? 6. What are indexes in SQL, and how do they improve query performance?
7. Write a query to calculate the total sales for each month using
GROUP BY. πππ―ππ§πππ πππ:
1. How do you optimize a slow-running SQL query?
2. What are views in SQL, and when would you use them?
3. What is the difference between a stored procedure and a function in SQL?
4. Explain the difference between
TRUNCATE, DELETE, and DROP commands. 5. What are windowing functions, and how are they used in analytics?
6. How do you use
PARTITION BY and ORDER BY in window functions? 7. How do you handle NULL values in SQL, and what functions help with that (e.g.,
COALESCE, ISNULL)?Here you can find essential SQL Interview Resourcesπ
https://t.iss.one/mysqldata
Like this post if you need more πβ€οΈ
Hope it helps :)
β€2
Tips for solving leetcode codings interview problems
If input array is sorted then
- Binary search
- Two pointers
If asked for all permutations/subsets then
- Backtracking
If given a tree then
- DFS
- BFS
If given a graph then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
If input array is sorted then
- Binary search
- Two pointers
If asked for all permutations/subsets then
- Backtracking
If given a tree then
- DFS
- BFS
If given a graph then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
β€2π2
Tips for solving leetcode codings interview problems
If input array is sorted then
- Binary search
- Two pointers
If asked for all permutations/subsets then
- Backtracking
If given a tree then
- DFS
- BFS
If given a graph then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
If input array is sorted then
- Binary search
- Two pointers
If asked for all permutations/subsets then
- Backtracking
If given a tree then
- DFS
- BFS
If given a graph then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
β€4
The Only SQL You Actually Need For Your First Job (Data Analytics)
The Learning Trap: What Most Beginners Fall Into
When starting out, it's common to feel like you need to master every possible SQL concept. You binge YouTube videos, tutorials, and courses, yet still feel lost in interviews or when given a real dataset.
Common traps:
- Complex subqueries
- Advanced CTEs
- Recursive queries
- 100+ tutorials watched
- 0 practical experience
Reality Check: What You'll Actually Use 75% of the Time
Most data analytics roles (especially entry-level) require clarity, speed, and confidence with core SQL operations. Hereβs what covers most daily work:
1. SELECT, FROM, WHERE β The Foundation
SELECT name, age
FROM employees
WHERE department = 'Finance';
This is how almost every query begins. Whether exploring a dataset or building a dashboard, these are always in use.
2. JOINs β Combining Data From Multiple Tables
SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;
Youβll often join tables like employee data with department, customer orders with payments, etc.
3. GROUP BY β Summarizing Data
SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;
Used to get summaries by categories like sales per region or users by plan.
4. ORDER BY β Sorting Results
SELECT name, salary
FROM employees
ORDER BY salary DESC;
Helps sort output for dashboards or reports.
5. Aggregations β Simple But Powerful
Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()
SELECT AVG(salary)
FROM employees
WHERE department = 'IT';
Gives quick insights like average deal size or total revenue.
6. ROW_NUMBER() β Adding Row Logic
SELECT *
FROM (
SELECT *, ROW_NUMBER() OVER(PARTITION BY customer_id ORDER BY order_date DESC) as rn
FROM orders
) sub
WHERE rn = 1;
Used for deduplication, rankings, or selecting the latest record per group.
Credits: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
React β€οΈ for more
The Learning Trap: What Most Beginners Fall Into
When starting out, it's common to feel like you need to master every possible SQL concept. You binge YouTube videos, tutorials, and courses, yet still feel lost in interviews or when given a real dataset.
Common traps:
- Complex subqueries
- Advanced CTEs
- Recursive queries
- 100+ tutorials watched
- 0 practical experience
Reality Check: What You'll Actually Use 75% of the Time
Most data analytics roles (especially entry-level) require clarity, speed, and confidence with core SQL operations. Hereβs what covers most daily work:
1. SELECT, FROM, WHERE β The Foundation
SELECT name, age
FROM employees
WHERE department = 'Finance';
This is how almost every query begins. Whether exploring a dataset or building a dashboard, these are always in use.
2. JOINs β Combining Data From Multiple Tables
SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;
Youβll often join tables like employee data with department, customer orders with payments, etc.
3. GROUP BY β Summarizing Data
SELECT department, COUNT(*) AS employee_count
FROM employees
GROUP BY department;
Used to get summaries by categories like sales per region or users by plan.
4. ORDER BY β Sorting Results
SELECT name, salary
FROM employees
ORDER BY salary DESC;
Helps sort output for dashboards or reports.
5. Aggregations β Simple But Powerful
Common functions: COUNT(), SUM(), AVG(), MIN(), MAX()
SELECT AVG(salary)
FROM employees
WHERE department = 'IT';
Gives quick insights like average deal size or total revenue.
6. ROW_NUMBER() β Adding Row Logic
SELECT *
FROM (
SELECT *, ROW_NUMBER() OVER(PARTITION BY customer_id ORDER BY order_date DESC) as rn
FROM orders
) sub
WHERE rn = 1;
Used for deduplication, rankings, or selecting the latest record per group.
Credits: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02
React β€οΈ for more
β€5π1
Don't overwhelm to learn JavaScript, JavaScript is only this much
1.Variables
β’ var
β’ let
β’ const
2. Data Types
β’ number
β’ string
β’ boolean
β’ null
β’ undefined
β’ symbol
3.Declaring variables
β’ var
β’ let
β’ const
4.Expressions
Primary expressions
β’ this
β’ Literals
β’ []
β’ {}
β’ function
β’ class
β’ function*
β’ async function
β’ async function*
β’ /ab+c/i
β’ string
β’ ( )
Left-hand-side expressions
β’ Property accessors
β’ ?.
β’ new
β’ new .target
β’ import.iss.oneta
β’ super
β’ import()
5.operators
β’ Arithmetic Operators: +, -, *, /, %
β’ Comparison Operators: ==, ===, !=, !==, <, >, <=, >=
β’ Logical Operators: &&, ||, !
6.Control Structures
β’ if
β’ else if
β’ else
β’ switch
β’ case
β’ default
7.Iterations/Loop
β’ do...while
β’ for
β’ for...in
β’ for...of
β’ for await...of
β’ while
8.Functions
β’ Arrow Functions
β’ Default parameters
β’ Rest parameters
β’ arguments
β’ Method definitions
β’ getter
β’ setter
9.Objects and Arrays
β’ Object Literal: { key: value }
β’ Array Literal: [element1, element2, ...]
β’ Object Methods and Properties
β’ Array Methods: push(), pop(), shift(), unshift(),
splice(), slice(), forEach(), map(), filter()
10.Classes and Prototypes
β’ Class Declaration
β’ Constructor Functions
β’ Prototypal Inheritance
β’ extends keyword
β’ super keyword
β’ Private class features
β’ Public class fields
β’ static
β’ Static initialization blocks
11.Error Handling
β’ try,
β’ catch,
β’ finally (exception handling)
ADVANCED CONCEPTS
12.Closures
β’ Lexical Scope
β’ Function Scope
β’ Closure Use Cases
13.Asynchronous JavaScript
β’ Callback Functions
β’ Promises
β’ async/await Syntax
β’ Fetch API
β’ XMLHttpRequest
14.Modules
β’ import and export Statements (ES6 Modules)
β’ CommonJS Modules (require, module.exports)
15.Event Handling
β’ Event Listeners
β’ Event Object
β’ Bubbling and Capturing
16.DOM Manipulation
β’ Selecting DOM Elements
β’ Modifying Element Properties
β’ Creating and Appending Elements
17.Regular Expressions
β’ Pattern Matching
β’ RegExp Methods: test(), exec(), match(), replace()
18.Browser APIs
β’ localStorage and sessionStorage
β’ navigator Object
β’ Geolocation API
β’ Canvas API
19.Web APIs
β’ setTimeout(), setInterval()
β’ XMLHttpRequest
β’ Fetch API
β’ WebSockets
20.Functional Programming
β’ Higher-Order Functions
β’ map(), reduce(), filter()
β’ Pure Functions and Immutability
21.Promises and Asynchronous Patterns
β’ Promise Chaining
β’ Error Handling with Promises
β’ Async/Await
22.ES6+ Features
β’ Template Literals
β’ Destructuring Assignment
β’ Rest and Spread Operators
β’ Arrow Functions
β’ Classes and Inheritance
β’ Default Parameters
β’ let, const Block Scoping
23.Browser Object Model (BOM)
β’ window Object
β’ history Object
β’ location Object
β’ navigator Object
24.Node.js Specific Concepts
β’ require()
β’ Node.js Modules (module.exports)
β’ File System Module (fs)
β’ npm (Node Package Manager)
25.Testing Frameworks
β’ Jasmine
β’ Mocha
β’ Jest
1.Variables
β’ var
β’ let
β’ const
2. Data Types
β’ number
β’ string
β’ boolean
β’ null
β’ undefined
β’ symbol
3.Declaring variables
β’ var
β’ let
β’ const
4.Expressions
Primary expressions
β’ this
β’ Literals
β’ []
β’ {}
β’ function
β’ class
β’ function*
β’ async function
β’ async function*
β’ /ab+c/i
β’ string
β’ ( )
Left-hand-side expressions
β’ Property accessors
β’ ?.
β’ new
β’ new .target
β’ import.iss.oneta
β’ super
β’ import()
5.operators
β’ Arithmetic Operators: +, -, *, /, %
β’ Comparison Operators: ==, ===, !=, !==, <, >, <=, >=
β’ Logical Operators: &&, ||, !
6.Control Structures
β’ if
β’ else if
β’ else
β’ switch
β’ case
β’ default
7.Iterations/Loop
β’ do...while
β’ for
β’ for...in
β’ for...of
β’ for await...of
β’ while
8.Functions
β’ Arrow Functions
β’ Default parameters
β’ Rest parameters
β’ arguments
β’ Method definitions
β’ getter
β’ setter
9.Objects and Arrays
β’ Object Literal: { key: value }
β’ Array Literal: [element1, element2, ...]
β’ Object Methods and Properties
β’ Array Methods: push(), pop(), shift(), unshift(),
splice(), slice(), forEach(), map(), filter()
10.Classes and Prototypes
β’ Class Declaration
β’ Constructor Functions
β’ Prototypal Inheritance
β’ extends keyword
β’ super keyword
β’ Private class features
β’ Public class fields
β’ static
β’ Static initialization blocks
11.Error Handling
β’ try,
β’ catch,
β’ finally (exception handling)
ADVANCED CONCEPTS
12.Closures
β’ Lexical Scope
β’ Function Scope
β’ Closure Use Cases
13.Asynchronous JavaScript
β’ Callback Functions
β’ Promises
β’ async/await Syntax
β’ Fetch API
β’ XMLHttpRequest
14.Modules
β’ import and export Statements (ES6 Modules)
β’ CommonJS Modules (require, module.exports)
15.Event Handling
β’ Event Listeners
β’ Event Object
β’ Bubbling and Capturing
16.DOM Manipulation
β’ Selecting DOM Elements
β’ Modifying Element Properties
β’ Creating and Appending Elements
17.Regular Expressions
β’ Pattern Matching
β’ RegExp Methods: test(), exec(), match(), replace()
18.Browser APIs
β’ localStorage and sessionStorage
β’ navigator Object
β’ Geolocation API
β’ Canvas API
19.Web APIs
β’ setTimeout(), setInterval()
β’ XMLHttpRequest
β’ Fetch API
β’ WebSockets
20.Functional Programming
β’ Higher-Order Functions
β’ map(), reduce(), filter()
β’ Pure Functions and Immutability
21.Promises and Asynchronous Patterns
β’ Promise Chaining
β’ Error Handling with Promises
β’ Async/Await
22.ES6+ Features
β’ Template Literals
β’ Destructuring Assignment
β’ Rest and Spread Operators
β’ Arrow Functions
β’ Classes and Inheritance
β’ Default Parameters
β’ let, const Block Scoping
23.Browser Object Model (BOM)
β’ window Object
β’ history Object
β’ location Object
β’ navigator Object
24.Node.js Specific Concepts
β’ require()
β’ Node.js Modules (module.exports)
β’ File System Module (fs)
β’ npm (Node Package Manager)
25.Testing Frameworks
β’ Jasmine
β’ Mocha
β’ Jest
β€5π1
Skills to become a successful web developerπ―π¨π»βπ»
1. HTML/CSS Basics ππ¨
Master the building blocks of the web.
2. JavaScript π»β‘
Add interactivity and dynamic content to your sites.
3. Responsive Design π±π
Ensure your sites look great on all devices!
4. Version Control (Git) π οΈπ
Track changes and collaborate with ease.
5. Frameworks (React, Angular, etc) ππ οΈ
Speed up development with powerful tools.
6. Backend Languages (Node.js, Python, etc)ππ»
Handle server-side logic and databases.
7. APIs ππ‘
Connect and integrate with other services.
8. Problem-Solving Skills π§©π€
Tackle challenges creatively and efficiently.
9. Testing/Debugging ππ
Ensure your code runs smoothly and bug-free.
10. Soft Skills (Communication, Teamwork) π£οΈπ€
Work effectively with others and convey ideas clearly.
11. Continuous Learning πβ¨
Stay updated with the latest technologies and trends.
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING ππ
#webdev
1. HTML/CSS Basics ππ¨
Master the building blocks of the web.
2. JavaScript π»β‘
Add interactivity and dynamic content to your sites.
3. Responsive Design π±π
Ensure your sites look great on all devices!
4. Version Control (Git) π οΈπ
Track changes and collaborate with ease.
5. Frameworks (React, Angular, etc) ππ οΈ
Speed up development with powerful tools.
6. Backend Languages (Node.js, Python, etc)ππ»
Handle server-side logic and databases.
7. APIs ππ‘
Connect and integrate with other services.
8. Problem-Solving Skills π§©π€
Tackle challenges creatively and efficiently.
9. Testing/Debugging ππ
Ensure your code runs smoothly and bug-free.
10. Soft Skills (Communication, Teamwork) π£οΈπ€
Work effectively with others and convey ideas clearly.
11. Continuous Learning πβ¨
Stay updated with the latest technologies and trends.
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING ππ
#webdev
β€2
SQL CHEAT SHEETπ©βπ»
Here is a quick cheat sheet of some of the most essential SQL commands:
SELECT - Retrieves data from a database
UPDATE - Updates existing data in a database
DELETE - Removes data from a database
INSERT - Adds data to a database
CREATE - Creates an object such as a database or table
ALTER - Modifies an existing object in a database
DROP -Deletes an entire table or database
ORDER BY - Sorts the selected data in an ascending or descending order
WHERE β Condition used to filter a specific set of records from the database
GROUP BY - Groups a set of data by a common parameter
HAVING - Allows the use of aggregate functions within the query
JOIN - Joins two or more tables together to retrieve data
INDEX - Creates an index on a table, to speed up search times.
Here is a quick cheat sheet of some of the most essential SQL commands:
SELECT - Retrieves data from a database
UPDATE - Updates existing data in a database
DELETE - Removes data from a database
INSERT - Adds data to a database
CREATE - Creates an object such as a database or table
ALTER - Modifies an existing object in a database
DROP -Deletes an entire table or database
ORDER BY - Sorts the selected data in an ascending or descending order
WHERE β Condition used to filter a specific set of records from the database
GROUP BY - Groups a set of data by a common parameter
HAVING - Allows the use of aggregate functions within the query
JOIN - Joins two or more tables together to retrieve data
INDEX - Creates an index on a table, to speed up search times.
List of Top 12 Coding Channels on WhatsApp:
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11. SQL:
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12. GitHub:
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β€5
SQL Joins β
β€2
Iβve never met an awesome software developer who:
- Thought learning new frameworks was a waste.
- Avoided refactoring because βit already works.β
- Avoided debugging because it was frustrating.
- Never deleted code they once proudly wrote.
- Never pushed code that broke in production.
- Stuck to one programming language forever.
- Stopped learning after getting their first job.
- Didnβt rewrite their code later.
- Only worked on projects that felt safe.
- Refused to ask questions when stuck.
Great developers arenβt perfect.
They take risks.
They make mistakes.
They debug endlessly.
They make wrong estimates.
But during all that, They learn.
And thatβs exactly why they grow.
Keep that in mind
- Thought learning new frameworks was a waste.
- Avoided refactoring because βit already works.β
- Avoided debugging because it was frustrating.
- Never deleted code they once proudly wrote.
- Never pushed code that broke in production.
- Stuck to one programming language forever.
- Stopped learning after getting their first job.
- Didnβt rewrite their code later.
- Only worked on projects that felt safe.
- Refused to ask questions when stuck.
Great developers arenβt perfect.
They take risks.
They make mistakes.
They debug endlessly.
They make wrong estimates.
But during all that, They learn.
And thatβs exactly why they grow.
Keep that in mind
β€5π1
Theoretical Questions for Coding Interviews on Basic Data Structures
1. What is a Data Structure?
A data structure is a way of organizing and storing data so that it can be accessed and modified efficiently. Common data structures include arrays, linked lists, stacks, queues, and trees.
2. What is an Array?
An array is a collection of elements, each identified by an index. It has a fixed size and stores elements of the same type in contiguous memory locations.
3. What is a Linked List?
A linked list is a linear data structure where elements (nodes) are stored non-contiguously. Each node contains a value and a reference (or link) to the next node. Unlike arrays, linked lists can grow dynamically.
4. What is a Stack?
A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. The most recently added element is the first one to be removed. Common operations include push (add an element) and pop (remove an element).
5. What is a Queue?
A queue is a linear data structure that follows the First In, First Out (FIFO) principle. The first element added is the first one to be removed. Common operations include enqueue (add an element) and dequeue (remove an element).
6. What is a Binary Tree?
A binary tree is a hierarchical data structure where each node has at most two children, usually referred to as the left and right child. It is used for efficient searching and sorting.
7. What is the difference between an array and a linked list?
Array: Fixed size, elements stored in contiguous memory.
Linked List: Dynamic size, elements stored non-contiguously, each node points to the next.
8. What is the time complexity for accessing an element in an array vs. a linked list?
Array: O(1) for direct access by index.
Linked List: O(n) for access, as you must traverse the list from the start to find an element.
9. What is the time complexity for inserting or deleting an element in an array vs. a linked list?
Array:
Insertion/Deletion at the end: O(1).
Insertion/Deletion at the beginning or middle: O(n) because elements must be shifted.
Linked List:
Insertion/Deletion at the beginning: O(1).
Insertion/Deletion in the middle or end: O(n), as you need to traverse the list.
10. What is a HashMap (or Dictionary)?
A HashMap is a data structure that stores key-value pairs. It allows efficient lookups, insertions, and deletions using a hash function to map keys to values. Average time complexity for these operations is O(1).
Coding interview: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
1. What is a Data Structure?
A data structure is a way of organizing and storing data so that it can be accessed and modified efficiently. Common data structures include arrays, linked lists, stacks, queues, and trees.
2. What is an Array?
An array is a collection of elements, each identified by an index. It has a fixed size and stores elements of the same type in contiguous memory locations.
3. What is a Linked List?
A linked list is a linear data structure where elements (nodes) are stored non-contiguously. Each node contains a value and a reference (or link) to the next node. Unlike arrays, linked lists can grow dynamically.
4. What is a Stack?
A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. The most recently added element is the first one to be removed. Common operations include push (add an element) and pop (remove an element).
5. What is a Queue?
A queue is a linear data structure that follows the First In, First Out (FIFO) principle. The first element added is the first one to be removed. Common operations include enqueue (add an element) and dequeue (remove an element).
6. What is a Binary Tree?
A binary tree is a hierarchical data structure where each node has at most two children, usually referred to as the left and right child. It is used for efficient searching and sorting.
7. What is the difference between an array and a linked list?
Array: Fixed size, elements stored in contiguous memory.
Linked List: Dynamic size, elements stored non-contiguously, each node points to the next.
8. What is the time complexity for accessing an element in an array vs. a linked list?
Array: O(1) for direct access by index.
Linked List: O(n) for access, as you must traverse the list from the start to find an element.
9. What is the time complexity for inserting or deleting an element in an array vs. a linked list?
Array:
Insertion/Deletion at the end: O(1).
Insertion/Deletion at the beginning or middle: O(n) because elements must be shifted.
Linked List:
Insertion/Deletion at the beginning: O(1).
Insertion/Deletion in the middle or end: O(n), as you need to traverse the list.
10. What is a HashMap (or Dictionary)?
A HashMap is a data structure that stores key-value pairs. It allows efficient lookups, insertions, and deletions using a hash function to map keys to values. Average time complexity for these operations is O(1).
Coding interview: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
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π§Ώ Essential React Hooks Part 1
Each hook addresses specific performance, state management, or accessibility needs within React components, allowing for efficient and organized code structure.
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