mongo db in ubuntu

 

 Step 1: Update System

sudo apt update
sudo apt upgrade -y

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Step 2: Install Required Packages

sudo apt install -y curl gnupg

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 Step 3: Import MongoDB Public GPG Key

curl -fsSL https://pgp.mongodb.com/server-7.0.asc | \
sudo gpg -o /usr/share/keyrings/mongodb-server-7.0.gpg \
--dearmor

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 Step 4: Add MongoDB Repository

 For Ubuntu 22.04 (Jammy)

echo "deb [ arch=amd64 signed-by=/usr/share/keyrings/mongodb-server-7.0.gpg ] https://repo.mongodb.org/apt/ubuntu jammy/mongodb-org/7.0 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-7.0.list

👉 For Ubuntu 20.04 (Focal)

echo "deb [ arch=amd64 signed-by=/usr/share/keyrings/mongodb-server-7.0.gpg ] https://repo.mongodb.org/apt/ubuntu focal/mongodb-org/7.0 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-7.0.list

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 Step 5: Update Package List Again

sudo apt update

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 Step 6: Install MongoDB

sudo apt install -y mongodb-org

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 Step 7: Start MongoDB Service

sudo systemctl start mongod

Enable auto-start on boot:

sudo systemctl enable mongod

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 Step 8: Check MongoDB Status

sudo systemctl status mongod

You should see:

Active: active (running)

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 Step 9: Verify MongoDB Shell

mongosh

If successful, you'll see:

Current Mongosh Log ID:
Using MongoDB:

Exit shell:

exit

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 Check Installed Version

mongod --version

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 Quick Test

Inside mongosh:

show dbs
use testdb
db.users.insertOne({name: "Raghavendra", role: "Data Engineer"})
db.users.find()

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If you tell me your Ubuntu version (lsb_release -a), I can give exact commands customized for your setup.

Implement Functions: Count – Sort – Limit – Skip – Aggregate using MongoDB

Here’s a clear practical implementation of:

• ✅ count

• ✅ sort

• ✅ limit

• ✅ skip

• ✅ aggregate

using MongoDB (via mongosh).

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🔹 Step 1: Create Sample Collection

Open Mongo shell:

mongosh

Create database and collection:

use companyDB

db.employees.insertMany([
  { name: "Ravi", department: "IT", salary: 60000, age: 28 },
  { name: "Anita", department: "HR", salary: 45000, age: 32 },
  { name: "Kiran", department: "IT", salary: 75000, age: 30 },
  { name: "Meena", department: "Finance", salary: 50000, age: 29 },
  { name: "Arjun", department: "IT", salary: 80000, age: 35 },
  { name: "Divya", department: "HR", salary: 47000, age: 27 }
])

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 Count Documents

➤ Count All Documents

db.employees.countDocuments()

➤ Count with Condition

db.employees.countDocuments({ department: "IT" })

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 Sort Documents

➤ Sort by Salary (Ascending)

db.employees.find().sort({ salary: 1 })

➤ Sort by Salary (Descending)

db.employees.find().sort({ salary: -1 })

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 Limit Documents

Return first 3 records:

db.employees.find().limit(3)

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 Skip Documents

Skip first 2 records:

db.employees.find().skip(2)

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 Combine Sort + Limit + Skip (Pagination Example)

Example: Page 2 (3 records per page)

db.employees.find()
.sort({ salary: -1 })
.skip(3)
.limit(3)

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 Aggregate (Advanced Operations)

Aggregation uses pipeline stages.

---

🔹 A. Group by Department & Count Employees

db.employees.aggregate([
  { $group: { _id: "$department", totalEmployees: { $sum: 1 } } }
])

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🔹 B. Average Salary per Department

db.employees.aggregate([
  {
    $group: {
      _id: "$department",
      avgSalary: { $avg: "$salary" }
    }
  }
])

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🔹 C. Highest Salary per Department

db.employees.aggregate([
  {
    $group: {
      _id: "$department",
      maxSalary: { $max: "$salary" }
    }
  }
])

---

🔹 D. Filter + Group + Sort (Real Interview Example)

👉 IT employees average salary sorted descending

db.employees.aggregate([
  { $match: { department: "IT" } },
  {
    $group: {
      _id: "$department",
      avgSalary: { $avg: "$salary" }
    }
  },
  { $sort: { avgSalary: -1 } }
])

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 Real-Time Scenario (Top 2 Highest Paid Employees)

db.employees.find()
.sort({ salary: -1 })
.limit(2)