DatabaseManagementSystems/Practical/Practical Exam/MongoDB/M2 - Crud operations.md

# M2 - Crud Operations

**Problem Statement:**
Design and Develop MongoDB Queries using CRUD operations:
Create Employee collection by considering following Fields:
i. Name: Embedded Doc (FName, LName)
ii. Company Name: String
iii. Salary: Number
iv. Designation: String
v. Age: Number
vi. Expertise: Array
vii. DOB: String or Date
viii. Email id: String
ix. Contact: String
x. Address: Array of Embedded Doc (PAddr, LAddr)
Insert at least 5 documents in collection by considering above
attribute and execute following queries:
1. Final name of Employee where age is less than 30 and salary more
than 50000.
2. Creates a new document if no document in the employee collection
contains
{Designation: "Tester", Company_name: "TCS", Age: 25}
3. Selects all documents in the collection where the field age has
a value less than 30 or the value of the salary field is greater
than 40000.
4. Find documents where Designation is not equal to "Developer".
5. Find _id, Designation, Address and Name from all documents where
Company_name is "Infosys".
6. Display only FName and LName of all Employees

---

## Creating database & collection:

```json
use empDB
db.createCollection("Employee")

```

## Inserting data:

```json
db.Employee.insertMany([
{
  Name: {FName: "Ayush", LName: "Kalaskar"},
  Company: "TCS",
  Salary: 45000,
  Designation: "Programmer",
  Age: 24,
  Expertise: ['Docker', 'Linux', 'Networking', 'Politics'],
  DOB: new Date("1998-03-12"),
  Email: "ayush.k@tcs.com",
  contact: 9972410427,
  address: [{PAddr: "Kokan, Maharashtra"}, {LAddr: "Lohegaon, Pune"}]
},
{
  Name: {FName: "Mehul", LName: "Patil"},
  Company: "MEPA",
  Salary: 55000,
  Designation: "Tester",
  Age: 20,
  Expertise: ['HTML', 'CSS', 'Javascript', 'Teaching'],
  DOB: new Date("1964-06-22"),
  Email: "mehul.p@mepa.com",
  contact: 9972410426,
  address: [{PAddr: "NDB, Maharashtra"}, {LAddr: "Camp, Pune"}]
},
{
  Name: {FName: "Himanshu", LName: "Patil"},
  Company: "Infosys",
  Salary: 85000,
  Designation: "Developer",
  Age: 67,
  Expertise: ['Mongodb', 'Mysql', 'Cassandra', 'Farming'],
  DOB: new Date("1957-04-28"),
  Email: "himanshu.p@infosys.com",
  contact: 9972410425,
  address: [{PAddr: "NDB, Maharashtra"}, {LAddr: "Camp, Pune"}]
}
])

```

## Queries

1. Final name of Employee where age is less than 30 and salary more than 50000.
```json
db.Employee.find(
  {
    Age: { $lt: 30 },
    Salary: { $gt: 50000 }
  }
)

```

2. Creates a new document if no document in the employee collection contains `{Designation: "Tester", Company_name: "TCS", Age: 25}`
```json
db.Employee.updateOne(
  {Designation: "Tester", Company: "TCS", Age: 25},
  { $setOnInsert:
    {
      Name: {FName: "Karan", LName: "Salvi"},
      Salary: 35000,
      Expertise: ['Blockchain', 'C++', 'Python', 'Fishing'],
      DOB: new Date("1999-11-01"),
      Email: "karan.s@tcs.com",
      Contact: 9972410424,
      Address: [{PAddr: "Kolhapur, Maharashtra"}, {LAddr: "Viman Nagar, Pune"}]
    }
  },
  { upsert: true }
)

```

3. Selects all documents in the collection where the field age has a value less than 30 or the value of the salary field is greater than 40000.
```json
db.Employee.find(
  {
    Age: { $lt: 30 },
    Salary: { $gt: 40000 }
  }
)

```

4. Find documents where Designation is not equal to "Developer".
```json
db.Employee.find(
  {
    Designation: { $ne: "Developer" }
  }
)

```

5. Find _id, Designation, Address and Name from all documents where Company_name is "Infosys".
```json
db.Employee.find(
  { Company: "Infosys" },
  { _id: 1, Designation: 1, Address: 1, Name: 1 }
)

```

6. Display only FName and LName of all Employees.
```json
db.Employee.find(
  {},
  {"Name.FName": 1, "Name.LName": 1}
)

```

---