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+# M6 - Map-reduce
+
+**Problem statement:**
+Design MongoDB database and perform following Map reduce operation:
+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)
+Execute the following query:
+
+---
+
+## Creating database
+```mongo
+use mapred;
+
+```
+
+## Inserting data:
+```mongo
+db.emp.insertMany([
+  {
+    Name: {FName: "Tanmay", LName: "Machkar"},
+    Company: "TCS",
+    Salary: 40000,
+    Designation: "Tester",
+    Age: 25,
+    Expertise: ['Mongodb','Mysql','Cassandra'],
+    DOB: new Date("2003-12-02"),
+    Email: "xyz@gmail.com",
+    Contact: 1234567890,
+    Address: [{PAddr: {City: "Pune", Rd: "Bharatmata"}}, {LAddr: {Pin_code: 411001}}]
+  },
+  {
+    Name: {FName: "Rajesh", LName: "Machkar"},
+    Company: "Infosys",
+    Salary: 50000,
+    Designation: "Programmer",
+    Age: 29,
+    Expertise: ['Mongodb','Mysql'],
+    DOB: new Date("1990-12-02"),
+    Email: "xy@gmail.com",
+    Contact: 1234567809,
+    Address: [{PAddr: {City: "Pune", Rd: "JM"}}, {LAddr: {Pin_code: 411047}}]
+  },
+  {
+    Name: {FName: "Tejas", LName: "Machkar"},
+    Company: "TCS",
+    Salary: 20000,
+    Designation: "Developer",
+    Age: 35,
+    Expertise: ['Mongodb'],
+    DOB: new Date("2000-11-22"),
+    Email: "x@gmail.com",
+    Contact: 1234567089,
+    Address: [{PAddr: {City: "Mumbai", Rd: "Airport"}}, {LAddr: {Pin_code: 411030}}]
+  },
+  {
+    Name: {FName: "Deepali", LName: "Machkar"},
+    Company: "Persistent",
+    Salary: 40000,
+    Designation: "Tester",
+    Age: 30,
+    Expertise: ['Mysql'],
+    DOB: new Date("1978-02-12"),
+    Email: "y@gmail.com",
+    Contact: 1234506789,
+    Address: [{PAddr: {City: "Phaltan", Rd: "Highway"}}, {LAddr: {Pin_code: 411012}}]
+  },
+  {
+    Name: {FName: "Om", LName: "Deokar"},
+    Company: "Persistent",
+    Salary: 25000,
+    Designation: "Programmer",
+    Age: 39,
+    Expertise: ['Cassandra'],
+    DOB: new Date("2007-03-15"),
+    Email: "z@gmail.com",
+    Contact: 1234567890,
+    Address: [{PAddr: {City: "Jaipur", Rd: "Pink"}}, {LAddr: {Pin_code: 411056}}]
+  },
+])
+```
+
+## Queries
+
+1. Display the total salary of per company.
+```mongo
+db.emp.mapReduce(
+  function(){
+    emit(this.Company, this.Salary);
+  },
+  function(key, values){
+    return Array.sum(values);
+  },
+  { out: "query1"}
+)
+db.query1.find()
+
+```
+
+2. Display the total salary of company Name:"TCS".
+```mongo
+db.emp.mapReduce(
+  function(){
+    if(this.Company == "TCS"){
+      emit(this.Company, this.Salary);
+    }
+  },
+  function(key, values){
+    return Array.sum(values);
+  },
+  { out: "query2"}
+)
+db.query2.find()
+
+```
+
+3. Return the average salary of company whose address is “Pune".
+```mongo
+db.emp.mapReduce(
+  function(){
+    if(this.Address[0].PAddr.City === "Pune"){
+      emit(this.Company, this.Salary);
+    }
+  },
+  function(key, values){
+    return Array.avg(values);
+  },
+  { out: "query3"}
+)
+db.query3.find()
+
+```
+
+4. Display total count for “City=Pune”.
+```mongo
+db.emp.mapReduce(
+  function(){
+    if(this.Address[0].PAddr.City === "Pune"){
+      emit("Count", 1);
+    }
+  },
+  function(key, values){
+    return Array.sum(values);
+  },
+  { out: "query4"}
+)
+db.query4.find()
+
+```
+
+5. Return count for city pune and age greater than 40.
+```mongo
+db.emp.mapReduce(
+  function(){
+    if(this.Address[0].PAddr.City === "Pune" && this.Age > 25){
+      emit("Count", 1);
+    }
+  },
+  function(key, values){
+    return Array.sum(values);
+  },
+  { out: "query5"}
+)
+db.query5.find()
+
+```
+
+---
+