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M2P Fintech
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I applied via Approached by Company and was interviewed in Jul 2024. There were 3 interview rounds.
Normal DSA round from hacker rank
DSA round from hacker rank or leetcode
I applied via Recruitment Consulltant and was interviewed in Jun 2024. There was 1 interview round.
I was interviewed with m2p virtually. One of the worst interview experience yet. Interviewer was inexperience. He remembered one solution for the problem and not ready to accept any other solution which is better
Question: Given root node and two other node of binary tree. Find the distance between them
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I applied via Referral and was interviewed in Jul 2024. There were 2 interview rounds.
It was about DS Algo and Java garbage collection,multithreading
Rate limiter is a system that controls the rate of traffic sent or received by a network interface.
Implement a token bucket algorithm to track and limit the rate of requests
Use a sliding window algorithm to track the number of requests within a specific time frame
Consider using a distributed rate limiter for scalability and fault tolerance
I applied via Referral and was interviewed in Jun 2024. There was 1 interview round.
Asked to do coding for RDBMS using any programing language
Design an ad-click aggregation service for tracking and analyzing ad clicks.
Use a distributed system to handle high volume of ad click data
Implement real-time processing for immediate insights on ad performance
Utilize a database to store aggregated ad click data for reporting and analysis
Design a high-performance in-memory cache system for storing and retrieving data efficiently.
Use a hash table or a key-value store to store data in memory
Implement caching strategies like LRU (Least Recently Used) or LFU (Least Frequently Used) to manage cache eviction
Consider using a distributed cache for scalability and fault tolerance
Optimize cache size and expiration policies based on the application's data access
I applied via Referral and was interviewed in Mar 2024. There was 1 interview round.
In-memory SQL databases store data in memory for faster access and processing.
In-memory databases keep all data in RAM for quicker retrieval compared to disk-based databases.
Examples include SQLite in-memory database and Redis.
They are commonly used for caching, real-time analytics, and temporary data storage.
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Software Development Engineer II
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Software Development Engineer
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Software Development Engineer 1
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