DE Shaw Interview, Hyderabad | Lead
Summary
I had a screening round with DE Shaw for a Lead role in Hyderabad, which involved a HackerRank code pair. The interview covered Java fundamentals, including differences between HashMap and ConcurrentHashMap, memory management, retry mechanisms, and exception handling. It also delved into DSA topics like LRU cache and distributed cache.
Full Experience
Screening Round - hackerrank code pair. Questions
Java Fundamentals
- HashMap vs Concurrent Hashmap
- How to handle memory out of bounds in java
- Retry mechanism via api call.
- Exception handling in java
- Questions on existing project
DSA
LRU cache, Distributed cache
Interview Questions (6)
HashMap vs ConcurrentHashMap Differences
Discuss the key differences between Java's HashMap and ConcurrentHashMap. Elaborate on their thread-safety, performance characteristics, internal working, and suitable use cases for each.
Handling Memory Out of Bounds in Java
Explain common causes of OutOfMemoryError in Java applications and describe effective strategies and best practices to diagnose, prevent, and handle such memory-related issues.
Implementing Retry Mechanism for API Calls
Describe how to design and implement a robust retry mechanism for unreliable API calls. Consider factors such as exponential backoff, maximum number of retries, circuit breakers, and handling transient vs. permanent failures.
Exception Handling in Java
Discuss the principles and best practices for exception handling in Java. Cover topics like checked vs. unchecked exceptions, the try-catch-finally block, custom exceptions, and when to use specific exception handling patterns.
Design LRU Cache
Design and implement a Least Recently Used (LRU) cache. The cache should support get and put operations. The get operation retrieves the value of the key if the key exists, otherwise returns -1. The put operation inserts or updates the value if the key is not already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting a new item.
Design Distributed Cache
Design a distributed cache system. Explain how you would handle data consistency, scalability, fault tolerance, cache invalidation strategies, and typical deployment considerations in a large-scale distributed environment.