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LRU Cache is a data structure that stores the most recently used items and discards the least recently used items.
Use a hash table to store key-value pairs
Use a doubly linked list to keep track of the order of items
When an item is accessed, move it to the front of the list
When the cache is full, remove the least recently used item from the back of the list
Lookup and insertion should be O(1) time complexity
Implement 2 stacks in an array
Divide the array into two halves
Use top1 and top2 to keep track of top elements of stacks
Push and pop elements from respective halves
Check for overflow and underflow conditions
I applied via Campus Placement and was interviewed in Aug 2022. There were 3 interview rounds.
Questions from trees and linkedin
Reverse a linked list using multiple approaches.
Iterative approach: Use three pointers to reverse the links between nodes.
Recursive approach: Recursively reverse the rest of the list and adjust the links.
Stack approach: Push all the nodes onto a stack and then pop them to create the reversed list.
I applied via Campus Placement and was interviewed before Feb 2023. There were 4 interview rounds.
The test consisted of 4 DSA questions (1 easy, 2 medium, 1 hard) that had to be completed in 2 hours. They were standard questions from Leetcode and the test was similar to Leetcode's weekly coding contest.
Find subarray in an array with sum 0
Iterate through the array and keep track of the running sum
Store the running sum in a hashmap and check if the same sum has been seen before
If the sum is 0 or if the running sum is already in the hashmap, a subarray with sum 0 exists
Database design for a blogging website
Create tables for users, blog posts, comments, and categories
Use primary and foreign keys to establish relationships between tables
Include fields such as title, content, author, date, and tags
Implement indexing for faster retrieval of data
Consider implementing a caching mechanism for improved performance
To balance the load of requests on a single server, one can implement load balancing techniques.
Implementing a load balancer to distribute incoming requests evenly across multiple servers
Using round-robin algorithm to route requests to different servers in a sequential manner
Utilizing server health checks to monitor the performance of each server and adjust the load distribution accordingly
Design a database for a college
Create tables for students, courses, professors, departments, and grades
Establish relationships between tables using foreign keys
Include attributes such as student ID, course ID, professor ID, department ID, and grade
Consider normalization to reduce redundancy and improve data integrity
Pseudo code to validate password
Create a function that takes a password as input
Check if the password meets the required criteria (e.g. length, special characters)
Return true if the password is valid, false otherwise
I applied via Campus Placement and was interviewed before May 2023. There were 3 interview rounds.
5 questions of medium difficulty level covering topics like queue, dynamic programming, binary search, greedy.
I applied via Campus Placement
90 mins, easy, Data structures and algorithm basics
Remove duplicates from array of strings in place
Use a HashSet to keep track of unique elements
Iterate through the array and remove duplicates by checking if element is already in the HashSet
Update the array in place by shifting elements to fill in the removed duplicates
Caching is the process of storing data in a temporary location to reduce access time and improve performance.
Caching helps reduce the load on servers by serving frequently accessed data quickly
It can improve performance by reducing the time needed to retrieve data from the original source
Examples include browser caching, CDN caching, and database caching
2 hours coding round, only 1 person out of 90 cleared
posted on 14 May 2022
I applied via Naukri.com and was interviewed before May 2021. There was 1 interview round.
I applied via LinkedIn and was interviewed before Nov 2022. There were 4 interview rounds.
I applied via Naukri.com and was interviewed in Jan 2022. There were 3 interview rounds.
Group by clause is used to group data based on a specific column in a table.
Used with aggregate functions like SUM, COUNT, AVG, etc.
Helps in analyzing data by grouping it based on a common attribute.
Can be used with multiple columns to create nested groups.
Example: GROUP BY department in a table of employees to get the total salary for each department.
CountA, CountB, Countif are functions used in Google Sheets to count cells based on certain criteria.
CountA counts the number of cells in a range that are not empty.
CountB counts the number of cells in a range that are not blank.
Countif counts the number of cells in a range that meet a certain condition.
Countif can be used with operators like >, <, =, and functions like AND, OR.
Countif can also be used with wildcards l
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