Designing the movie model schema

Introduction to Data Modeling¶

Concept: Data modeling defines how data is stored and organized in a database.
Importance: Enhances data retrieval efficiency, maintains data integrity, and simplifies application maintenance.

Understanding Document-Oriented Databases¶

MongoDB Documents: Stores data in JSON-like documents (BSON format) that are flexible and schema-less.
Collections: Documents are grouped into collections, similar to tables in relational databases.

Identifying Entities and Relationships¶

Primary Entities: Movies, cast, and reviews.
Relationships: Movies have casts and reviews.

Defining the Movie Schema¶

Fields:
- Title: The name of the movie (string, required).
- Year: The release year of the movie (number, required).
- Genre: The genre of the movie (string, required).
- Director: The director of the movie (string, optional).
- Cast: An array of objects containing cast member references and their roles.
- Reviews: An array of embedded review documents.

Example Movie Document¶

{
  "_id": ObjectId("60c72b2f9b1d8b3f0c6e6a2e"),
  "title": "Inception",
  "year": 2010,
  "genre": "Sci-Fi",
  "director": "Christopher Nolan",
  "cast": [
    { "_id": ObjectId("60c72b2f9b1d8b3f0c6e6a2f"), "role": "Dom Cobb" },
    { "_id": ObjectId("60c72b2f9b1d8b3f0c6e6a30"), "role": "Arthur" }
  ],
  "reviews": [
    {
      "_id": ObjectId("60c72b2f9b1d8b3f0c6e6a31"),
      "user": "John Doe",
      "rating": 5,
      "comment": "Excellent movie!"
    },
    {
      "_id": ObjectId("60c72b2f9b1d8b3f0c6e6a32"),
      "user": "Jane Smith",
      "rating": 4,
      "comment": "Great visuals and story."
    }
  ]
}

Designing the Cast Schema¶

Fields:
- Name: The name of the cast member (string, required).
- Date of Birth: The date of birth of the cast member (date, optional).

Example Cast Document:

{
  "_id": ObjectId("60c72b2f9b1d8b3f0c6e6a2f"),
  "name": "Leonardo DiCaprio",
  "date_of_birth": ISODate("1974-11-11")
}

Embedding vs. Referencing¶

Embedding: Storing related data directly within a single document. Best for data that is often read together.
Referencing: Storing related data in separate documents and linking them via ObjectId. Best for data that is shared across multiple documents.
Choice: Using embedding for reviews to keep them closely tied to their respective movies, and references for cast members to allow for reuse and maintain normalization.

Querying with References and Embedding¶

Basic Queries:

Find Movies by Genre:
```
db.movies.find({ genre: "Sci-Fi" })
```
Find Movies by Year:
```
db.movies.find({ year: 2010 })
```

Advanced Queries:

Find Movies by Cast Member:

// Assuming the cast member's ObjectId is known
var castId = ObjectId("60c72b2f9b1d8b3f0c6e6a2f");
db.movies.find({ "cast._id": castId })

Find Movies by Reviewer:

// Assuming the reviewer's user name is known
var userName = "John Doe";
db.movies.find({ "reviews.user": userName })

Using Aggregation for Joins:

Populate Cast Information:

db.movies.aggregate([
  { $match: { title: "Inception" } },
  {
    $lookup: {
      from: "cast",
      localField: "cast._id",
      foreignField: "_id",
      as: "castDetails"
    }
  }
])

Benefits of Using References and Embedding¶

Data Normalization: Avoids data duplication by storing shared data (like cast members) separately.
Scalability: Embedding reviews within movies simplifies data retrieval and makes it easier to scale the database as related data grows.
Flexibility: Allows for more complex queries and relationships between different entities.