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607730bcfb
@ -14,7 +14,8 @@ 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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Insert at least 5 documents in collection by considering above
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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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@ -1,157 +0,0 @@
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# M2 - 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
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attribute and execute following queries:
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1. Final name of Employee where age is less than 30 and salary more
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than 50000.
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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. Selects all documents in the collection where the field age has
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a value less than 30 or the value of the salary field is greater
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than 40000.
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4. Find documents where Designation is not equal to "Developer".
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5. Find _id, Designation, Address and Name from all documents where
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Company_name is "Infosys".
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6. Display only FName and LName of all Employees
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---
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## Creating database & collection:
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```json
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use empDB
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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: 24,
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Expertise: ['Docker', 'Linux', 'Networking', 'Politics'],
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DOB: new Date("1998-03-12"),
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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: 20,
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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. Final name of Employee where age is less than 30 and salary more than 50000.
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```json
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db.Employee.find(
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{
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Age: { $lt: 30 },
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Salary: { $gt: 50000 }
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}
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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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{
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Name: {FName: "Karan", LName: "Salvi"},
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Salary: 35000,
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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. 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.
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```json
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db.Employee.find(
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{
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Age: { $lt: 30 },
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Salary: { $gt: 40000 }
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}
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)
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```
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4. Find documents where Designation is not equal to "Developer".
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```json
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db.Employee.find(
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{
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Designation: { $ne: "Developer" }
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}
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)
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```
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5. Find _id, Designation, Address and Name from all documents where Company_name is "Infosys".
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```json
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db.Employee.find(
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{ Company: "Infosys" },
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{ _id: 1, Designation: 1, Address: 1, Name: 1 }
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)
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```
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6. Display only FName and LName of all Employees.
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```json
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db.Employee.find(
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{},
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{"Name.FName": 1, "Name.LName": 1}
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)
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```
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---
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