MongoDB Query Practice Guide with Real Job Portal Dataset

Overview

Recently, I practiced MongoDB queries using a sample Job Portal database.

Instead of learning operators in isolation, I used a realistic Job Portal dataset to better understand how MongoDB queries work in real-world applications.

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Dataset Structure

A sample jobs collection was created with fields such as:

• title
• company
• location
• salary
• experience
• skills
• applicants
• status
• department

Example Document

{
  title: "\"Software Engineer\","
  company: "TechCorp Bangladesh",
  salary: 75000,
  skills: ["JavaScript", "Node.js", "MongoDB"]
}

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Topics Covered

1. Comparison Operators

Used for filtering documents based on value comparison.

Operators covered:

• $eq
• $ne
• $gt
• $gte
• $lt
• $lte

Example:

db.jobs.find({
  salary: { $gt: 70000 }
})

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2. Logical Operators

Combining multiple query conditions.

Operators covered:

• $and
• $or
• $not
• $nor

Example:

db.jobs.find({
  $or: [
    { location: "Dhaka" },
    { isRemote: true }
  ]
})

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3. Array Query Operators

Working with array fields such as skills.

Operators covered:

• $in
• $nin
• $all
• $size
• $elemMatch

Example:

db.jobs.find({
  skills: { $all: ["Python", "SQL"] }
})

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4. Update Operators

Updating existing documents.

Operators covered:

• $set
• $inc
• $push
• $pull

Example:

db.jobs.updateOne(
  { title: "Frontend Developer" },
  { $push: { skills: "TypeScript" } }
)

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5. Projection, Sorting & Pagination

Topics covered:

• Field selection
• Sorting
• Limiting results
• Pagination

Example:

db.jobs.find({}, { title: 1, salary: 1, _id: 0 })
  .sort({ salary: -1 })
  .limit(5)

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6. Aggregation Pipeline

Used for analytics and reporting.

Operators covered:

• $match
• $group
• $project
• $sort

Example use case:

Calculate average salary by department.

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7. Advanced Aggregation

Production-level query operations.

Operators covered:

• $lookup
• $unwind
• $facet

Useful for:

• Joining collections
• Dashboard analytics
• Multi-stage reporting

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Key Learning

MongoDB becomes significantly easier to understand when practiced using realistic datasets instead of isolated examples.

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Next Learning Goals

• MongoDB Indexing
• Mongoose ODM
• MongoDB Atlas
• Transactions

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Thanks for reading.

mongodb #backend #nodejs #database #webdev