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MongoDB Database Configuration

Overview​

The Movie List Application uses MongoDB as its primary database to store movie information and user reviews. MongoDB is a NoSQL document database that stores data in flexible, JSON-like documents called BSON (Binary JSON).

Database Setup​

Container Configuration​

The MongoDB database runs in a Docker container named mongo-local using the official MongoDB image:

mongo-local:
  image: mongo:latest
  container_name: mongo-local
  ports:
    - "27017:27017"
  volumes:
    - ./mongo-init:/docker-entrypoint-initdb.d

Key Configuration Details:

  • Image: mongo:latest - Uses the most recent stable MongoDB version
  • Port: 27017 (MongoDB's default port) is exposed to the host
  • Initialization: The mongo-init folder is mounted to /docker-entrypoint-initdb.d

Automatic Database Initialization​

MongoDB automatically executes any scripts placed in /docker-entrypoint-initdb.d when the container starts for the first time. This project uses this feature to populate the database with initial movie data.

Database Structure​

Database Name​

  • Database: movie-api-db
  • Collection: movies (stores all movie documents)

Connection Configuration​

The Spring Boot application connects to MongoDB using different configurations based on the environment:

Local Development (application-local.properties)​

spring.data.mongodb.host=mongo-local
spring.data.mongodb.port=27017
spring.data.mongodb.database=movie-api-db

Explanation:

  • host=mongo-local: Connects to the Docker container named "mongo-local"
  • port=27017: Uses MongoDB's standard port
  • database=movie-api-db: Specifies the database name

Production (application-prod.properties)​

# Commented out - would use MongoDB Atlas or other cloud service
# spring.data.mongodb.uri=mongodb+srv://user:password@cluster

Data Initialization Process​

1. Initialization Script (init-mongo.js)​

const fs = require('fs');
const path = require('path');

// Read the movie data from JSON file
const dataPath = path.join('/docker-entrypoint-initdb.d', 'data.json');
const data = JSON.parse(fs.readFileSync(dataPath, 'utf8'));

// Connect to the database
const db = connect('mongodb://localhost:27017/movie-api-db');

// Insert all movie data into the movies collection
db.movies.insertMany(data);

How it works:

  1. File Reading: Reads movie data from data.json file
  2. Database Connection: Connects to the movie-api-db database
  3. Data Insertion: Uses insertMany() to add all movies to the movies collection

2. Movie Data Structure (data.json)​

Each movie document contains the following fields:

{
  "imdbId": "tt3915174",
  "title": "Puss in Boots: The Last Wish",
  "releaseDate": "2022-12-21",
  "trailerLink": "https://www.youtube.com/watch?v=tHb7WlgyaUc",
  "genres": ["Animation", "Action", "Adventure", "Comedy", "Family"],
  "poster": "https://image.tmdb.org/t/p/w500/1NqwE6LP9IEdOZ57NCT51ftHtWT.jpg",
  "backdrops": [
    "https://image.tmdb.org/t/p/original/r9PkFnRUIthgBp2JZZzD380MWZy.jpg",
    // ... more backdrop URLs
  ]
}

Field Descriptions:

  • imdbId: Unique identifier from IMDb (Internet Movie Database)
  • title: Movie title
  • releaseDate: When the movie was released (YYYY-MM-DD format)
  • trailerLink: YouTube URL for the movie trailer
  • genres: Array of genre categories
  • poster: URL to the movie poster image
  • backdrops: Array of background image URLs for the movie

Data Persistence​

Development Mode​

By default, data is not persisted between container restarts. When you stop and restart the containers, the database is reinitialized with the original data.

Enabling Persistence​

To persist data between restarts, uncomment the volume configuration in docker-compose.yml:

volumes:
  - mongo-local-data:/data/db

This creates a named Docker volume that survives container restarts.

Database Operations​

The Spring Boot application interacts with MongoDB through:

  • Spring Data MongoDB: Provides repository pattern for database operations
  • Automatic Mapping: Converts between Java objects and MongoDB documents
  • Query Methods: Allows finding movies by various criteria (title, genre, etc.)

Benefits of This Setup​

  1. Quick Development: Database is ready with sample data immediately
  2. Consistency: Every developer gets the same initial dataset
  3. Flexibility: NoSQL structure allows easy schema changes
  4. Scalability: MongoDB can handle large amounts of movie and review data
  5. Docker Integration: Database runs consistently across different environments