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AI Features

Feature #2: Fetch Top Movies

Explore how to combine multiple country-specific top movie lists, each sorted by popularity, into one unified list. Understand the step-by-step merging approach, time and space complexities, and implement the solution to handle distributed search results efficiently.

Description

Now, we need to build a criterion so the top movies from multiple countries will combine into a single list of top-rated movies. In order to scale, the content search is performed in a distributed fashion. Search results for each country are produced in separate lists. Each member of a given list is ranked by popularity, with 1 being most popular and popularity decreasing as the rank number increases.

Let’s say that the following titles are represented by the provided IDs:

We’ll be given n arrays that are all sorted in ascending order of popularity rank. We have to combine these lists into a single list that will be sorted by rank in ascending order, meaning from best to worst.

Keep in mind that the ranks are unique to individual movies and a single rank can be in multiple lists.

Let’s understand this better with an illustration:

Solution

Since our task involves multiple lists, you should divide the problem into multiple tasks, starting with the problem of combining two lists at a time. Then, you should combine the result of those first two lists with the third list, and so on, until the very last one is reached.

Let’s discuss how we will ...