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Collect Reviews: The system should fetch movie reviews from various sources, such as IMDb, Rotten Tomatoes, Metacritic, and others.
Aggregate Reviews: Combine reviews for each movie and present them in a unified format, highlighting individual reviews and generating an average rating.
Search and Filter Movies: Users should be able to search movies by title, genre, release year, and other attributes. They should also be able to filter reviews by source, rating, or reviewer.
User Registration and Profile: Allow users to register, create profiles, and save favorite movies for future reference.
User Review Submission: Registered users should be able to submit their own reviews and ratings.
User Ratings and Feedback: Users should be able to upvote or downvote other users' reviews.
Movie Metadata: Display metadata such as movie title, synopsis, release date, genre, and director along with reviews.
Scalability: The system should support a growing number of users and handle a large number of concurrent requests. Plan for 10x scaling over the next few years.
High Availability: The system should be available 99.9% of the time.
Performance: Average response times should be less than 200ms under normal loads.
Data Consistency: Consistency is critical when aggregating data from multiple sources. Data should be consistent and up-to-date.
Security: User data and API keys for external sources should be securely stored and encrypted.
Rate Limiting: Implement rate limiting to prevent misuse or abuse of the system and APIs.
User Base: Initial user base is approximately 1 million users, growing to 10 million over the next few years.
Request Traffic:
Data Sources: We will aggregate reviews from 10 different sources, and each movie has about 20 reviews on average.
Movies in Database: Approximately 50,000 movies in our database, each having metadata and multiple reviews.
Assuming the average response size is 50KB:
We will be making use of following API's:
This include user registration, user login and user profile.
Search Movies
Endpoint: /api/v1/movies/search
Method: GET
Query Params: title, genre, year
Response:
[
{
"movie_id": "1",
"title": "Inception",
"year": "2010",
"genre": "Sci-Fi",
"rating": 4.8
},
{
"movie_id": "2",
"title": "The Matrix",
"year": "1999",
"genre": "Action",
"rating": 4.7
}
]
Get Movie Details
Endpoint: /api/v1/movies/{movie_id}
Method: GET
Response:
{
"movie_id": "1",
"title": "Inception",
"year": "2010",
"genre": "Sci-Fi",
"rating": 4.8,
"reviews": [
{
"review_id": "rev123",
"reviewer": "Rotten Tomatoes",
"rating": 5,
"content": "A visually stunning masterpiece..."
},
{
"review_id": "rev124",
"reviewer": "IMDb",
"rating": 4.5,
"content": "Christopher Nolan does it again!"
}
]
}
Submit Review
Endpoint: /api/v1/movies/{movie_id}/reviews
Method: POST
Request Body:
{
"user_id": "12345",
"rating": 4.5,
"content": "Great movie with complex plot."
}
Response:
{
"review_id": "rev125",
"message": "Review submitted successfully."
}
The Movie Reviews Aggregator System requires a structured database schema to handle user information, movie metadata, reviews, and interactions with external sources. The design should consider scalability, data integrity, and efficient querying for optimal performance.
User Service.Movie Service.Review Management Service.Review Aggregator Service periodically fetches reviews from external sources.Review Database.Movie Service for users querying movie details.Review Management Service.Review Database and updates the overall rating for the movie.Notification Service sends alerts when new reviews are added to a user's favorite movie.API Gateway.Review Management Service, which stores the review data in the Review Database.Review Management Service communicates with the Movie Service to update the movie's overall rating.Movie Service recalculates the average rating and updates the Movie Database.API Gateway.Fetching Reviews:
Data Normalization and Deduplication:
Review Storage and Rating Update:
Review Database.Movie Database to reflect the latest review data.Error Handling and Retries:
Scalability:
FOR each movie IN movie_list:
FOR each source IN review_sources:
reviews = fetch_reviews(movie, source)
normalized_reviews = normalize_reviews(reviews)
deduplicated_reviews = deduplicate_reviews(normalized_reviews)
store_reviews(deduplicated_reviews)
update_movie_rating(movie)
Review Aggregator Service crashes or becomes unresponsive due to unhandled exceptions or resource exhaustion.Movie Service and Review Management Service) due to eventual consistency issues or failed updates.