150 lines
3.6 KiB
Markdown
150 lines
3.6 KiB
Markdown
# M1 - Crud Operations
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**Problem Statement:**
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Design and Develop MongoDB Queries using CRUD operations:
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Create Employee collection by considering following Fields:
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i. Name: Embedded Doc (FName, LName)
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ii. Company Name: String
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iii. Salary: Number
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iv. Designation: String
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v. Age: Number
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vi. Expertise: Array
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vii. DOB: String or Date
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viii. Email id: String
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ix. Contact: String
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x. Address: Array of Embedded Doc (PAddr, LAddr)
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Insert at least 5 documents in collection by considering above attribute and execute following queries:
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1. Select all documents where the Designation field has the value
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"Programmer" and the value of the salary field is greater than
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30000.
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2. Creates a new document if no document in the employee collection
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contains
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{Designation: "Tester", Company_name: "TCS", Age: 25}
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3. Increase salary of each Employee working with “Infosys" 10000.
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4. Finds all employees working with "TCS" and reduce their salary
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by 5000.
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5. Return documents where Designation is not equal to "Tester".
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6. Find all employee with Exact Match on an Array having Expertise:
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['Mongodb','Mysql','Cassandra']
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---
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## Creating database & collection:
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```json
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use empDB1
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db.createCollection("Employee")
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```
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## Inserting data:
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```json
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db.Employee.insertMany([
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{
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Name: {FName: "Ayush", LName: "Kalaskar"},
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Company: "TCS",
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Salary: 45000,
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Designation: "Programmer",
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Age: 55,
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Expertise: ['Docker', 'Linux', 'Networking', 'Politics'],
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DOB: new Date("1969-03-12"),
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Email: "ayush.k@tcs.com",
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Contact: 9972410427,
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Address: [{PAddr: "Kokan, Maharashtra"}, {LAddr: "Lohegaon, Pune"}]
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},
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{
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Name: {FName: "Mehul", LName: "Patil"},
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Company: "MEPA",
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Salary: 55000,
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Designation: "Tester",
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Age: 60,
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Expertise: ['HTML', 'CSS', 'Javascript', 'Teaching'],
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DOB: new Date("1964-06-22"),
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Email: "mehul.p@mepa.com",
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Contact: 9972410426,
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Address: [{PAddr: "NDB, Maharashtra"}, {LAddr: "Camp, Pune"}]
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},
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{
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Name: {FName: "Himanshu", LName: "Patil"},
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Company: "Infosys",
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Salary: 85000,
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Designation: "Developer",
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Age: 67,
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Expertise: ['Mongodb', 'Mysql', 'Cassandra', 'Farming'],
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DOB: new Date("1957-04-28"),
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Email: "himanshu.p@infosys.com",
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Contact: 9972410425,
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Address: [{PAddr: "NDB, Maharashtra"}, {LAddr: "Camp, Pune"}]
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}
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])
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```
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## Queries
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1. Select all documents where the Designation field has the value "Programmer" and the value of the salary field is greater than 30000.
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```json
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db.Employee.find(
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{ Designation: "Programmer", Salary: { $gt: 30000 } }
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)
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```
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2. Creates a new document if no document in the employee collection contains `{Designation: "Tester", Company_name: "TCS", Age: 25}`
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```json
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db.Employee.updateOne(
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{ Designation: "Tester", Company: "TCS", Age: 25 },
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{ $setOnInsert: {
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Name: {FName: "Karan", LName: "Salvi"},
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Salary: 67500,
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Expertise: ['Blockchain', 'C++', 'Python', 'Fishing'],
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DOB: new Date("1999-11-01"),
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Email: "karan.s@tcs.com",
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Contact: 9972410424,
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Address: [{PAddr: "Kolhapur, Maharashtra"}, {LAddr: "Viman Nagar, Pune"}]
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}
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},
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{ upsert: true }
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)
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```
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3. Increase salary of each Employee working with “Infosys" 10000.
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```json
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db.Employee.updateMany(
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{ Company: "Infosys" },
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{ $inc: { Salary: 10000 } }
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)
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```
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4. Finds all employees working with "TCS" and reduce their salary by 5000.
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```json
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db.Employee.updateMany(
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{ Company: "TCS" },
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{ $inc: { Salary: -5000 } }
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)
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```
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5. Return documents where Designation is not equal to "Tester".
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```json
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db.Employee.find(
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{ Designation: { $ne: "Tester"} }
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)
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```
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6. Find all employee with Exact Match on an Array having Expertise: `['Mongodb','Mysql','Cassandra']`
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```json
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db.Employee.find(
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{ Expertise: { $all: ['Mongodb', 'Mysql', 'Cassandra'] } }
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)
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```
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---
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