🎯 💡 Extra Challenge: Using References Between Documents

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Here's an Extra Challenge designed to build on the original MongoDB modeling task. This one introduces referencing between collections, helping learners understand when to use references instead of embedding — a key design concept in NoSQL databases like MongoDB.

📌 Scenario

Instead of embedding full course details in each student document (which can lead to duplication), you'll now reference courses using course_id.

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🔹 Step 1: Modify the Student Document

Update your students collection to reference enrolled courses like this:

{
  "student_id": 102,
  "name": "Ravi Kumar",
  "class": "10B",
  "date_of_birth": "2008-07-20T00:00:00Z",
  "contact_info": {
    "phone": "9876504321",
    "email": "ravi.kumar@example.com"
  },
  "course_ids": [301, 302],  // References to course documents
  "marks": [
    { "subject": "Math", "score": 91 },
    { "subject": "Science", "score": 86 }
  ]
}

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🔹 Step 2: Sample Courses (Already Inserted)

{
  "course_id": 301,
  "title": "Mathematics",
  "teacher_name": "Mr. Arjun Mehta",
  "schedule": ["Mon", "Wed", "Fri"]
}

{
  "course_id": 302,
  "title": "Science",
  "teacher_name": "Ms. Reema Das",
  "schedule": ["Tue", "Thu"]
}

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🔍 Challenge Task

1. Store course references in the students collection using course_ids

2. Write a MongoDB query to retrieve a student’s name and the full details of the courses they are enrolled in

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🧠 Hint for the Query

You’ll need to:

• Use findOne() or aggregate() to get the student

• Extract the course_ids

• Use $lookup or multiple find() queries to fetch related course details from the courses collection

🔧 This mimics a one-to-many relationship without embedding full course documents.

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🧠 Why This Matters

• Demonstrates when and why referencing is better than embedding

• Teaches the concept of manual joins in NoSQL

• Prepares learners for more advanced aggregation and relationship modeling in MongoDB

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•  solution using $lookup (MongoDB aggregation): coming next

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Solution MongoDB document Modelling Assignment

 Here's the complete solution to your MongoDB document modeling assignment, including:

• ✅ Sample documents for students and courses collections

• ✅ Correct JSON structure

• ✅ MongoDB queries for the bonus task

• ✅ Notes on best practices (embed vs reference)

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🧾 ✅ MongoDB Document Modeling – Solution

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🔹 1. Sample Document for students Collection

{
  "student_id": 101,
  "name": "Aisha Khan",
  "class": "10A",
  "date_of_birth": "2008-05-10T00:00:00Z",
  "contact_info": {
    "phone": "9876543210",
    "email": "aisha.khan@example.com"
  },
  "marks": [
    { "subject": "Math", "score": 85 },
    { "subject": "Science", "score": 90 },
    { "subject": "English", "score": 88 }
  ]
}

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🔹 2. Sample Document for courses Collection

{
  "course_id": 301,
  "title": "Mathematics",
  "teacher_name": "Mr. Arjun Mehta",
  "schedule": ["Mon", "Wed", "Fri"]
}

You can insert these into MongoDB using:

db.students.insertOne({ /* student document above */ });
db.courses.insertOne({ /* course document above */ });

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🔹 3. MongoDB Query – Bonus Task

Q: Find all students who scored above 80 in Math and display only their name and Math score.

✅ MongoDB Query:

db.students.find(
  { "marks": { $elemMatch: { "subject": "Math", "score": { $gt: 80 } } } },
  {
    "name": 1,
    "marks": {
      $filter: {
        input: "$marks",
        as: "mark",
        cond: { $and: [ { $eq: ["$$mark.subject", "Math"] } ] }
      }
    }
  }
);

🧠 Explanation:

• $elemMatch filters students with at least one "Math" score > 80.

• $filter inside the projection limits returned marks to only the Math subject.

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📝 Notes & Best Practices

• Embedding marks inside the student document is useful when the marks are tightly coupled with the student (1:1 ownership).

• Use referencing (e.g. linking course_id) when many students share the same course and you need cross-document querying or analytics.

• Store date_of_birth in ISO 8601 format for date operations.

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🧠 Summary

You’ve now:

• Designed realistic NoSQL documents

• Learned how to embed nested data

• Queried and filtered embedded arrays

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Next: Extra Practice Challenge

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