Let’s try to solve some of the real time queries faced in the Employee Management System using Java 8 features.
1) Employee Class :
class Employee
{
int id;
String name;
int age;
String gender;
String department;
int yearOfJoining;
double salary;
public Employee(int id, String name, int age, String gender, String department, int yearOfJoining, double salary)
{
this.id = id;
this.name = name;
this.age = age;
this.gender = gender;
this.department = department;
this.yearOfJoining = yearOfJoining;
this.salary = salary;
}
public int getId()
{
return id;
}
public String getName()
{
return name;
}
public int getAge()
{
return age;
}
public String getGender()
{
return gender;
}
public String getDepartment()
{
return department;
}
public int getYearOfJoining()
{
return yearOfJoining;
}
public double getSalary()
{
return salary;
}
@Override
public String toString()
{
return "Id : "+id
+", Name : "+name
+", age : "+age
+", Gender : "+gender
+", Department : "+department
+", Year Of Joining : "+yearOfJoining
+", Salary : "+salary;
}
}
2) List Of Employees : employeeList
List<Employee> employeeList = new ArrayList<Employee>();
employeeList.add(new Employee(111, "Jiya Brein", 32, "Female", "HR", 2011, 25000.0));
employeeList.add(new Employee(122, "Paul Niksui", 25, "Male", "Sales And Marketing", 2015, 13500.0));
employeeList.add(new Employee(133, "Martin Theron", 29, "Male", "Infrastructure", 2012, 18000.0));
employeeList.add(new Employee(144, "Murali Gowda", 28, "Male", "Product Development", 2014, 32500.0));
employeeList.add(new Employee(155, "Nima Roy", 27, "Female", "HR", 2013, 22700.0));
employeeList.add(new Employee(166, "Iqbal Hussain", 43, "Male", "Security And Transport", 2016, 10500.0));
employeeList.add(new Employee(177, "Manu Sharma", 35, "Male", "Account And Finance", 2010, 27000.0));
employeeList.add(new Employee(188, "Wang Liu", 31, "Male", "Product Development", 2015, 34500.0));
employeeList.add(new Employee(199, "Amelia Zoe", 24, "Female", "Sales And Marketing", 2016, 11500.0));
employeeList.add(new Employee(200, "Jaden Dough", 38, "Male", "Security And Transport", 2015, 11000.5));
employeeList.add(new Employee(211, "Jasna Kaur", 27, "Female", "Infrastructure", 2014, 15700.0));
employeeList.add(new Employee(222, "Nitin Joshi", 25, "Male", "Product Development", 2016, 28200.0));
employeeList.add(new Employee(233, "Jyothi Reddy", 27, "Female", "Account And Finance", 2013, 21300.0));
employeeList.add(new Employee(244, "Nicolus Den", 24, "Male", "Sales And Marketing", 2017, 10700.5));
employeeList.add(new Employee(255, "Ali Baig", 23, "Male", "Infrastructure", 2018, 12700.0));
employeeList.add(new Employee(266, "Sanvi Pandey", 26, "Female", "Product Development", 2015, 28900.0));
employeeList.add(new Employee(277, "Anuj Chettiar", 31, "Male", "Product Development", 2012, 35700.0));
3) Real Time Queries On employeeList
Query 3.1 : How many male and female employees are there in the organization?
For queries such as above where you need to group the input elements, use the Collectors.groupingBy() method. In this query, we use Collectors.groupingBy() method which takes two arguments. We pass Employee::getGender as first argument which groups the input elements based on gender and Collectors.counting() as second argument which counts the number of entries in each group.
Map<String, Long> noOfMaleAndFemaleEmployees=
employeeList.stream().collect(Collectors.groupingBy(Employee::getGender, Collectors.counting()));
System.out.println(noOfMaleAndFemaleEmployees);
Output :
{Male=11, Female=6}
Query 3.2 : Print the name of all departments in the organization?
employeeList.stream()
.map(Employee::getDepartment)
.distinct()
.forEach(System.out::println);
Output :
HR
Sales And Marketing
Infrastructure
Product Development
Security And Transport
Account And Finance
Query 3.3 : What is the average age of male and female employees?
Use same method as query 3.1 but pass Collectors.averagingInt(Employee::getAge) instead of Collectors.counting() as the second argument to Collectors.groupingBy().
Map<String, Double> avgAgeOfMaleAndFemaleEmployees=
employeeList.stream().collect(Collectors.groupingBy(Employee::getGender, Collectors.averagingInt(Employee::getAge)));
System.out.println(avgAgeOfMaleAndFemaleEmployees);
Output :
{Male=30.181818181818183, Female=27.166666666666668}
Query 3.4 : Get the details of highest paid employee in the organization?
Use Collectors.maxBy() method which returns maximum element wrapped in an Optional object based on supplied Comparator.
Optional<Employee> highestPaidEmployeeWrapper=
employeeList.stream().collect(Collectors.maxBy(Comparator.comparingDouble(Employee::getSalary)));
Employee highestPaidEmployee = highestPaidEmployeeWrapper.get();
System.out.println("Details Of Highest Paid Employee : ");
System.out.println("==================================");
System.out.println("ID : "+highestPaidEmployee.getId());
System.out.println("Name : "+highestPaidEmployee.getName());
System.out.println("Age : "+highestPaidEmployee.getAge());
System.out.println("Gender : "+highestPaidEmployee.getGender());
System.out.println("Department : "+highestPaidEmployee.getDepartment());
System.out.println("Year Of Joining : "+highestPaidEmployee.getYearOfJoining());
System.out.println("Salary : "+highestPaidEmployee.getSalary());
Output :
Details Of Highest Paid Employee :
==================================
ID : 277
Name : Anuj Chettiar
Age : 31
Gender : Male
Department : Product Development
Year Of Joining : 2012
Salary : 35700.0
Query 3.5 : Get the names of all employees who have joined after 2015?
For such queries which require filtering of input elements, use Stream.filter() method which filters input elements according to supplied Predicate.
employeeList.stream()
.filter(e -> e.getYearOfJoining() > 2015)
.map(Employee::getName)
.forEach(System.out::println);
Output :
Iqbal Hussain
Amelia Zoe
Nitin Joshi
Nicolus Den
Ali Baig
Query 3.5.1 : Get the details of all employees who have joined after 2015?
employeeList.stream()
.filter(e -> e.getYearOfJoining() > 2015)
.forEach(System.out::println);
Output :
Id : 111, Name : Jiya Brein, age : 32, Gender : Female, Department : HR, Year Of Joining : 2011, Salary : 25000.0
Id : 122, Name : Paul Niksui, age : 25, Gender : Male, Department : Sales And Marketing, Year Of Joining : 2015, Salary : 13500.0
Id : 133, Name : Martin Theron, age : 29, Gender : Male, Department : Infrastructure, Year Of Joining : 2012, Salary : 18000.0
Id : 144, Name : Murali Gowda, age : 28, Gender : Male, Department : Product Development, Year Of Joining : 2014, Salary : 32500.0
Id : 155, Name : Nima Roy, age : 27, Gender : Female, Department : HR, Year Of Joining : 2013, Salary : 22700.0
Id : 166, Name : Iqbal Hussain, age : 43, Gender : Male, Department : Security And Transport, Year Of Joining : 2016, Salary : 10500.0
Id : 177, Name : Manu Sharma, age : 35, Gender : Male, Department : Account And Finance, Year Of Joining : 2010, Salary : 27000.0
Id : 188, Name : Wang Liu, age : 31, Gender : Male, Department : Product Development, Year Of Joining : 2015, Salary : 34500.0
Id : 199, Name : Amelia Zoe, age : 24, Gender : Female, Department : Sales And Marketing, Year Of Joining : 2016, Salary : 11500.0
Id : 200, Name : Jaden Dough, age : 38, Gender : Male, Department : Security And Transport, Year Of Joining : 2015, Salary : 11000.5
Id : 211, Name : Jasna Kaur, age : 27, Gender : Female, Department : Infrastructure, Year Of Joining : 2014, Salary : 15700.0
Id : 222, Name : Nitin Joshi, age : 25, Gender : Male, Department : Product Development, Year Of Joining : 2016, Salary : 28200.0
Id : 233, Name : Jyothi Reddy, age : 27, Gender : Female, Department : Account And Finance, Year Of Joining : 2013, Salary : 21300.0
Id : 244, Name : Nicolus Den, age : 24, Gender : Male, Department : Sales And Marketing, Year Of Joining : 2017, Salary : 10700.5
Id : 255, Name : Ali Baig, age : 23, Gender : Male, Department : Infrastructure, Year Of Joining : 2018, Salary : 12700.0
Id : 266, Name : Sanvi Pandey, age : 26, Gender : Female, Department : Product Development, Year Of Joining : 2015, Salary : 28900.0
Id : 277, Name : Anuj Chettiar, age : 31, Gender : Male, Department : Product Development, Year Of Joining : 2012, Salary : 35700.0
Query 3.6 : Count the number of employees in each department?
This query is same as query 3.1 but here we are grouping the elements by department.
Map<String, Long> employeeCountByDepartment=
employeeList.stream().collect(Collectors.groupingBy(Employee::getDepartment, Collectors.counting()));
System.out.println(employeeCountByDepartment);
Output :
Product Development : 5 Security And Transport : 2 Sales And Marketing : 3 Infrastructure : 3 HR : 2 Account And Finance : 2
Query 3.7 : What is the average salary of each department?
Map<String, Double> avgSalaryOfDepartments=
employeeList.stream().collect(Collectors.groupingBy(Employee::getDepartment, Collectors.averagingDouble(Employee::getSalary)));
System.out.println(avgSalaryOfDepartments);
Output :
Product Development : 31960.0 Security And Transport : 10750.25 Sales And Marketing : 11900.166666666666 Infrastructure : 15466.666666666666 HR : 23850.0 Account And Finance : 24150.0
Query 3.8 : Get the details of youngest male employee in the product development department?
Employee youngestMaleEmployeeInProductDevelopment=
employeeList.stream()
.filter(e -> e.getGender()=="Male" && e.getDepartment()=="Product Development")
.min(Comparator.comparingInt(Employee::getAge)).get();
System.out.println("Details Of Youngest Male Employee In Product Development");
System.out.println("----------------------------------------------");
System.out.println("ID : "+youngestMaleEmployeeInProductDevelopment.getId());
System.out.println("Name : "+youngestMaleEmployeeInProductDevelopment.getName());
System.out.println("Age : "+youngestMaleEmployeeInProductDevelopment.getAge());
System.out.println("Year Of Joinging : "+youngestMaleEmployeeInProductDevelopment.getYearOfJoining());
System.out.println("Salary : "+youngestMaleEmployeeInProductDevelopment.getSalary());
Output :
Details Of Youngest Male Employee In Product Development : ———————————————- ID : 222 Name : Nitin Joshi Age : 25 Year Of Joinging : 2016 Salary : 28200.0
Query 3.9 : Who has the most working experience in the organization?
Employee seniorMostEmployee =
employeeList.stream().sorted(Comparator.comparingInt(Employee::getYearOfJoining)).findFirst().get();
// OR
Employee seniorMostEmployee = employeeList.stream().min(Comparator.comparingDouble(Employee::getYearOfJoining)).get();
System.out.println("Senior Most Employee Details :");
System.out.println("----------------------------");
System.out.println("ID : "+seniorMostEmployee.getId());
System.out.println("Name : "+seniorMostEmployee.getName());
System.out.println("Age : "+seniorMostEmployee.getAge());
System.out.println("Gender : "+seniorMostEmployee.getGender());
System.out.println("Age : "+seniorMostEmployee.getDepartment());
System.out.println("Year Of Joinging : "+seniorMostEmployee.getYearOfJoining());
System.out.println("Salary : "+seniorMostEmployee.getSalary());
Output :
Senior Most Employee Details : —————————- ID : 177 Name : Manu Sharma Age : 35 Gender : Male Age : Account And Finance Year Of Joinging : 2010 Salary : 27000.0
Query 3.10 : How many male and female employees are there in the sales and marketing team?
Map<String, Long> countMaleFemaleEmployeesInSalesMarketing=
employeeList.stream()
.filter(e -> e.getDepartment()=="Sales And Marketing")
.collect(Collectors.groupingBy(Employee::getGender, Collectors.counting()));
System.out.println(countMaleFemaleEmployeesInSalesMarketing);
Output :
{Female=1, Male=2}
Query 3.11 : What is the average salary of male and female employees?
Map<String, Double> avgSalaryOfMaleAndFemaleEmployees=
employeeList.stream().collect(Collectors.groupingBy(Employee::getGender, Collectors.averagingDouble(Employee::getSalary)));
System.out.println(avgSalaryOfMaleAndFemaleEmployees);
Output :
{Male=21300.090909090908, Female=20850.0}
Query 3.12 : List down the names of all employees in each department?
Map<String, List<Employee>> employeeListByDepartment=
employeeList.stream().collect(Collectors.groupingBy(Employee::getDepartment));
Set<Entry<String, List<Employee>>> entrySet = employeeListByDepartment.entrySet();
for (Entry<String, List<Employee>> entry : entrySet)
{
System.out.println("--------------------------------------");
System.out.println("Employees In "+entry.getKey() + " : ");
System.out.println("--------------------------------------");
List<Employee> list = entry.getValue();
for (Employee e : list)
{
System.out.println(e.getName());
}
}
Output : ————————————– Employees In Product Development : ————————————– Murali Gowda Wang Liu Nitin Joshi Sanvi Pandey Anuj Chettiar ————————————– Employees In Security And Transport : ————————————– Iqbal Hussain Jaden Dough ————————————– Employees In Sales And Marketing : ————————————– Paul Niksui Amelia Zoe Nicolus Den ————————————– Employees In Infrastructure : ————————————– Martin Theron Jasna Kaur Ali Baig ————————————– Employees In HR : ————————————– Jiya Brein Nima Roy ————————————– Employees In Account And Finance : ————————————– Manu Sharma Jyothi Reddy
Query 3.13 : What is the average salary and total salary of the whole organization?
For this query, we use Collectors.summarizingDouble() on Employee::getSalary which will return statistics of the employee salary like max, min, average and total.
DoubleSummaryStatistics employeeSalaryStatistics=
employeeList.stream().collect(Collectors.summarizingDouble(Employee::getSalary));
System.out.println("Average Salary = "+employeeSalaryStatistics.getAverage());
System.out.println("Total Salary = "+employeeSalaryStatistics.getSum());
Output :
Average Salary = 21141.235294117647
Total Salary = 359401.0
Query 3.14 : Separate the employees who are younger or equal to 25 years from those employees who are older than 25 years.
For this query, we will be using Collectors.partitioningBy() method which separates input elements based on supplied Predicate.
Map<Boolean, List<Employee>> partitionEmployeesByAge=
employeeList.stream().collect(Collectors.partitioningBy(e -> e.getAge() > 25));
System.out.println("Complete Partition Object :: " + partitionEmployeesByAge);
System.out.println("Employee who are younger than or equal to 25 :: " + partitionEmployeesByAge.get(Boolean.FALSE));
System.out.println("Employee who are older than 25 :: " + partitionEmployeesByAge.get(Boolean.TRUE));
Output :
Complete Partition Object ::
{
false = [
Id:111,
Name:Jiya Brein,
age:32,
Gender:Female,
Department:HR,
Year Of Joining:2011,
Salary:25000.0,
Id:133,
Name:Martin Theron,
age:29,
Gender:Male,
Department:Infrastructure,
Year Of Joining:2012,
Salary:18000.0,
Id:144,
Name:Murali Gowda,
age:28,
Gender:Male,
Department:Product Development,
Year Of Joining:2014,
Salary:32500.0,
Id:155,
Name:Nima Roy,
age:27,
Gender:Female,
Department:HR,
Year Of Joining:2013,
Salary:22700.0,
Id:166,
Name:Iqbal Hussain,
age:43,
Gender:Male,
Department:Security And Transport,
Year Of Joining:2016,
Salary:10500.0,
Id:177,
Name:Manu Sharma,
age:35,
Gender:Male,
Department:Account And Finance,
Year Of Joining:2010,
Salary:27000.0,
Id:188,
Name:Wang Liu,
age:31,
Gender:Male,
Department:Product Development,
Year Of Joining:2015,
Salary:34500.0,
Id:200,
Name:Jaden Dough,
age:38,
Gender:Male,
Department:Security And Transport,
Year Of Joining:2015,
Salary:11000.5,
Id:211,
Name:Jasna Kaur,
age:27,
Gender:Female,
Department:Infrastructure,
Year Of Joining:2014,
Salary:15700.0,
Id:233,
Name:Jyothi Reddy,
age:27,
Gender:Female,
Department:Account And Finance,
Year Of Joining:2013,
Salary:21300.0,
Id:266,
Name:Sanvi Pandey,
age:26,
Gender:Female,
Department:Product Development,
Year Of Joining:2015,
Salary:28900.0,
Id:277,
Name:Anuj Chettiar,
age:31,
Gender:Male,
Department:Product Development,
Year Of Joining:2012,
Salary:35700.0
],
true = [
Id:122,
Name:Paul Niksui,
age:25,
Gender:Male,
Department:Sales And Marketing,
Year Of Joining:2015,
Salary:13500.0,
Id:199,
Name:Amelia Zoe,
age:24,
Gender:Female,
Department:Sales And Marketing,
Year Of Joining:2016,
Salary:11500.0,
Id:222,
Name:Nitin Joshi,
age:25,
Gender:Male,
Department:Product Development,
Year Of Joining:2016,
Salary:28200.0,
Id:244,
Name:Nicolus Den,
age:24,
Gender:Male,
Department:Sales And Marketing,
Year Of Joining:2017,
Salary:10700.5,
Id:255,
Name:Ali Baig,
age:23,
Gender:Male,
Department:Infrastructure,
Year Of Joining:2018,
Salary:12700.0
]
}
Employee who are older than 25:: [ Id:111, Name:Jiya Brein, age:32, Gender:Female, Department:HR, Year Of Joining:2011, Salary:25000.0, Id:133, Name:Martin Theron, age:29, Gender:Male, Department:Infrastructure, Year Of Joining:2012, Salary:18000.0, Id:144, Name:Murali Gowda, age:28, Gender:Male, Department:Product Development, Year Of Joining:2014, Salary:32500.0, Id:155, Name:Nima Roy, age:27, Gender:Female, Department:HR, Year Of Joining:2013, Salary:22700.0, Id:166, Name:Iqbal Hussain, age:43, Gender:Male, Department:Security And Transport, Year Of Joining:2016, Salary:10500.0, Id:177, Name:Manu Sharma, age:35, Gender:Male, Department:Account And Finance, Year Of Joining:2010, Salary:27000.0, Id:188, Name:Wang Liu, age:31, Gender:Male, Department:Product Development, Year Of Joining:2015, Salary:34500.0, Id:200, Name:Jaden Dough, age:38, Gender:Male, Department:Security And Transport, Year Of Joining:2015, Salary:11000.5, Id:211, Name:Jasna Kaur, age:27, Gender:Female, Department:Infrastructure, Year Of Joining:2014, Salary:15700.0, Id:233, Name:Jyothi Reddy, age:27, Gender:Female, Department:Account And Finance, Year Of Joining:2013, Salary:21300.0, Id:266, Name:Sanvi Pandey, age:26, Gender:Female, Department:Product Development, Year Of Joining:2015, Salary:28900.0, Id:277, Name:Anuj Chettiar, age:31, Gender:Male, Department:Product Development, Year Of Joining:2012, Salary:35700.0 ]
Employee who are younger than or equal to 25:: [ Id:122, Name:Paul Niksui, age:25, Gender:Male, Department:Sales And Marketing, Year Of Joining:2015, Salary:13500.0, Id:199, Name:Amelia Zoe, age:24, Gender:Female, Department:Sales And Marketing, Year Of Joining:2016, Salary:11500.0, Id:222, Name:Nitin Joshi, age:25, Gender:Male, Department:Product Development, Year Of Joining:2016, Salary:28200.0, Id:244, Name:Nicolus Den, age:24, Gender:Male, Department:Sales And Marketing, Year Of Joining:2017, Salary:10700.5, Id:255, Name:Ali Baig, age:23, Gender:Male, Department:Infrastructure, Year Of Joining:2018, Salary:12700.0 ]
Query 3.15 : Who is the oldest employee in the organization? What is his age and which department he belongs to?
Employee oldestEmployee = employeeList.stream().max(Comparator.comparingInt(Employee::getAge)).get();
System.out.println("Name : "+oldestEmployee.getName());
System.out.println("Age : "+oldestEmployee.getAge());
System.out.println("Department : "+oldestEmployee.getDepartment());
Output :
Name : Iqbal Hussain
Age : 43
Department : Security And Transport
Harshit Jain 