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M2P Fintech
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I applied via Walk-in and was interviewed in Apr 2024. There were 2 interview rounds.
15 aptitute and 2 sql coding question
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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I was interviewed before Feb 2024.
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