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)

---

🧾 ✅ MongoDB Document Modeling – Solution

---

🔹 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 }
  ]
}

---

🔹 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 */ });

---

🔹 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.

---

📝 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.

---

🧠 Summary

You’ve now:

• Designed realistic NoSQL documents

• Learned how to embed nested data

• Queried and filtered embedded arrays

---

← Previous Next →