SDE - Intern

Design and implement a data structure for Least Recently Used (LRU) cache to support the following operations:

1. get(key) - Return the value of the key if the key exists in the cache, otherwise return -1.

2. put(key, value), Insert the value in the cache if the key is not already present or update the value of the given key if the key is already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting the new item.

You will be given ‘Q’ queries. Each query will belong to one of these two types:

Type 0: for get(key) operation.
Type 1: for put(key, value) operation.

Note :

1. The cache is initialized with a capacity (the maximum number of unique keys it can hold at a time).

2. Access to an item or key is defined as a get or a put operation on the key. The least recently used key is the one with the oldest access time.

It was an SQL query which required 2 joins among 3 tables.

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The question was a theory question on Time Complexity difference b/w different sorting algorithm, and a follow up question on Quick sort vs Merge Sort.

Given 'k' sorted linked lists, each list is sorted in increasing order. You need to merge all these lists into one single sorted list. You need to return the head of the final linked list.

For example:

Input:
3
3
4 6 8
3
2 5 7 
2
1 9

Output:
1 2 4 5 6 7 8 9 

Explanation:
First list is: 4 -> 6 -> 8 -> NULL
Second list is: 2 -> 5 -> 7 -> NULL
Third list is: 1 -> 9 -> NULL
The final list would be: 1 -> 2 -> 4 -> 5 -> 6 -> 7 -> 8 -> 9 -> NULL

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I was only asked how did i know SAP, what was my thoughts on joining.