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Feature #5: Top Brokers

Explore how to implement a functionality that automatically finds the top k most active brokers based on their trade frequency. Learn to use a HashMap for counting occurrences and a min-heap to efficiently track the top performers, understanding both time and space complexity.

Description

The company is doing performance evaluations. Each broker’s increments will be decided based on their level of activity throughout the last quarter. Each broker is assigned a unique ID that can be used to track their progress. Currently, this information is managed using an array. Every time a broker completes a trade, their ID is inserted into this array. Now, the company wants to promote its top k brokers. We have to implement a functionality that will automatically output the top k performers at the end of a quarter.

We’ll be provided with a array of integers representing the brokers’ IDs. Our task is to determine the top k most active brokers based on the number of times their ID occurs in the array.

Solution

We need to find the top k IDs based on each number’s frequency count. In this problem, we first need to know the frequency of each number; we can do this using a, HashMap. Once we have the frequency map, the best data structure to keep track of the top k frequencies is heap. We’ll iterate through the frequency map and insert each element into our heap. If for an element, i, the size of our heap is k + 1, we do two things:

  1. Take out the lowest frequency ...