2 changed files with 2 additions and 158 deletions
--- a/Practical/Practical
+++ b/Practical/Practical
@ -14,7 +14,8 @@ 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:
+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.
--- a/Practical/Practical
+++ b/Practical/Practical
@ -1,157 +0,0 @@
 # 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}
 )
 ```
 ---