Top 3 Most Booked Hotel Categories

Problem Context

You are building a hotel analytics dashboard for a travel platform. The platform receives a continuous stream of booking events, and your task is to determine the top 3 most frequently booked hotel categories from the event log.

Each booking event is a string representing a hotel category (e.g., "Luxury", "Budget", "Resort"). You must process all events and return the three categories with the highest booking counts in descending order of frequency. If two categories have the same count, they should be ordered alphabetically (ascending).

Input / Output Format

Input: A list of strings bookings where each string is a hotel category name.

Output: A list of up to 3 strings representing the top booked categories, ordered by frequency (descending). Ties broken alphabetically.

Examples

Example 1

Input: ["Luxury", "Budget", "Luxury", "Resort", "Budget", "Luxury"] Output: ["Luxury", "Budget", "Resort"]

Explanation:

• Luxury → 3 bookings
• Budget → 2 bookings
• Resort → 1 booking

Top 3 by frequency: Luxury, Budget, Resort.

Example 2

Input: ["Budget", "Resort", "Spa", "Budget", "Resort", "Spa"] Output: ["Budget", "Resort", "Spa"]

Explanation:

• All three categories have 2 bookings each (a tie).
• Sorted alphabetically among ties: Budget, Resort, Spa.

Example 3

Input: ["Boutique"] Output: ["Boutique"]

Explanation: Only one unique category exists. Return a list with just that one entry.

Approach Hints

1. Frequency Counting: Use a HashMap<String, Integer> to count occurrences of each category as you process the stream.
2. Custom Sorting: Convert the map entries to a list and sort using a custom comparator:
   • Primary sort: frequency descending
   • Secondary sort (tie-breaking): category name ascending (alphabetical)
3. Top-K Selection: After sorting, take the first min(3, list.size()) elements.
4. Alternative (advanced): Use a PriorityQueue (min-heap of size 3) for an O(N log 3) = O(N) streaming approach, especially useful for very large inputs.