DatabaseManagementSystems/Practical/Practical Exam/M1 - Crud operations.md

# M1 - 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. Select all documents where the Designation field has the value
"Programmer" and the value of the salary field is greater than
30000.
2. Creates a new document if no document in the employee collection
contains
{Designation: "Tester", Company_name: "TCS", Age: 25}
3. Increase salary of each Employee working with “Infosys" 10000.
4. Finds all employees working with "TCS" and reduce their salary
by 5000.
5. Return documents where Designation is not equal to "Tester".
6. Find all employee with Exact Match on an Array having Expertise:
['Mongodb','Mysql','Cassandra']

---

## 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: 55,
  Expertise: ['Docker', 'Linux', 'Networking', 'Politics'],
  DOB: new Date("1969-03-12"),
  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: 60,
  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. Select all documents where the Designation field has the value "Programmer" and the value of the salary field is greater than 30000.
```json
db.Employee.find(
{ Designation: "Programmer", Salary: { $gt: 30000 } }
)

```

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: 67500,
  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. Increase salary of each Employee working with “Infosys" 10000.
```json
db.Employee.updateMany(
{ Company: "Infosys" },
{ $inc: { Salary: 10000 } }
)

```

4. Finds all employees working with "TCS" and reduce their salary by 5000.
```json
db.Employee.updateMany(
{ Company: "TCS" },
{ $inc: { Salary: -5000 } }
)

```

5. Return documents where Designation is not equal to "Tester".
```json
db.Employee.find(
{ Designation: { $ne: "Tester"} }
)

```

6. Find all employee with Exact Match on an Array having Expertise: `['Mongodb','Mysql','Cassandra']`
```json
db.Employee.find(
{ Expertise: { $all: ['Mongodb', 'Mysql', 'Cassandra'] } }
)

```

---