feat: add EmployeeFileCreation program with stream-based analytics

Implemented EmployeeFileCreation.java to generate 'employees_output.txt'
containing employee records and analytical results. Demonstrates Java
Streams for grouping, filtering, partitioning, and aggregating employee
data such as average salary, gender ratio, department insights, and
experience metrics.

Signed-off-by: https://github.com/Someshdiwan <[email protected]>

Author: Someshdiwan

Java 8 Crash Course/Java 8 Streams/src/EmployeeFileCreation.java

@@ -0,0 +1,182 @@
+import java.io.File;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.util.*;
+import java.util.stream.Collectors;
+
+record Employee(int id,
+                String name,
+                int age,
+                String gender,
+                String department,
+                int yearOfJoining,
+                double salary)
+{}
+
+public class EmployeeFileCreation {
+    public static void main(String[] args) {
+        List<Employee> emps = new ArrayList<>();
+
+        emps.add(new Employee(1, "Jhansi", 32, "Female", "HR", 2011, 25000.0));
+        emps.add(new Employee(2, "Smith", 25, "Male", "Sales", 2015, 13500.0));
+        emps.add(new Employee(3, "David", 29, "Male", "Infrastructure", 2012, 18000.0));
+        emps.add(new Employee(4, "Orlen", 28, "Male", "Development", 2014, 32500.0));
+        emps.add(new Employee(5, "Charles", 27, "Male", "HR", 2013, 22700.0));
+        emps.add(new Employee(6, "Cathy", 43, "Male", "Security", 2016, 10500.0));
+        emps.add(new Employee(7, "Ramesh", 35, "Male", "Finance", 2010, 27000.0));
+        emps.add(new Employee(8, "Suresh", 31, "Male", "Development", 2015, 34500.0));
+        emps.add(new Employee(9, "Gita", 24, "Female", "Sales", 2016, 11500.0));
+        emps.add(new Employee(10, "Mahesh", 38, "Male", "Security", 2015, 11000.5));
+        emps.add(new Employee(11, "Gouri", 27, "Female", "Infrastructure", 2014, 15700.0));
+        emps.add(new Employee(12, "Nithin", 25, "Male", "Development", 2016, 28200.0));
+        emps.add(new Employee(13, "Swathi", 27, "Female", "Finance", 2013, 21300.0));
+        emps.add(new Employee(14, "Buttler", 24, "Male", "Sales", 2017, 10700.5));
+        emps.add(new Employee(15, "Ashok", 23, "Male", "Infrastructure", 2018, 12700.0));
+        emps.add(new Employee(16, "Sanvi", 26, "Female", "Development", 2015, 28900.0));
+
+        try {
+            // Create file
+            File file = new File("employees_output.txt");
+            FileWriter writer = new FileWriter(file);
+
+            // Write all employee data to file
+            writer.write("===== EMPLOYEE DATA =====\n\n");
+            for (Employee emp : emps) {
+                writer.write(emp.toString() + "\n");
+            }
+
+            writer.write("\n===== QUERY RESULTS =====\n\n");
+
+            // 1. Male and Female count
+            writer.write("1. Male and Female Employee Count:\n");
+            Map<String, Long> map1 = emps.stream()
+                .collect(Collectors.groupingBy(Employee::gender, Collectors.counting()));
+            writer.write(map1.toString() + "\n\n");
+
+            // 2. All departments
+            writer.write("2. All Departments:\n");
+            List<String> departments = emps.stream()
+                .map(Employee::department)
+                .distinct()
+                .toList();
+            departments.forEach(dept -> {
+                try {
+                    writer.write(dept + "\n");
+                } catch (IOException e) {
+                    e.printStackTrace();
+                }
+            });
+            writer.write("\n");
+
+            // 3. Average age by gender
+            writer.write("3. Average Age by Gender:\n");
+            Map<String, Double> map = emps.stream()
+                .collect(Collectors.groupingBy(Employee::gender, Collectors.averagingInt(Employee::age)));
+            writer.write(map.toString() + "\n\n");
+
+            // 4. Highest paid employee
+            writer.write("4. Highest Paid Employee:\n");
+            Optional<Employee> optional = emps.stream()
+                .collect(Collectors.maxBy(Comparator.comparingDouble(Employee::salary)));
+            if(optional.isPresent()) {
+                writer.write(optional.get().toString() + "\n\n");
+            }
+
+            // 5. Employees joined after 2015
+            writer.write("5. Employees Joined After 2015:\n");
+            List<String> names = emps.stream()
+                .filter(e -> e.yearOfJoining() > 2015)
+                .map(Employee::name)
+                .toList();
+            names.forEach(name -> {
+                try {
+                    writer.write(name + "\n");
+                } catch (IOException e) {
+                    e.printStackTrace();
+                }
+            });
+            writer.write("\n");
+
+            // 6. Employee count per department
+            writer.write("6. Employee Count Per Department:\n");
+            Map<String, Long> map2 = emps.stream()
+                .collect(Collectors.groupingBy(Employee::department, Collectors.counting()));
+            writer.write(map2.toString() + "\n\n");
+
+            // 7. Average salary per department
+            writer.write("7. Average Salary Per Department:\n");
+            Map<String, Double> map3 = emps.stream()
+                .collect(Collectors.groupingBy(Employee::department, Collectors.averagingDouble(Employee::salary)));
+            writer.write(map3.toString() + "\n\n");
+
+            // 8. Youngest male in Development
+            writer.write("8. Youngest Male in Development Department:\n");
+            Optional<Employee> optional2 = emps.stream()
+                .filter(e -> e.gender().equals("Male") && e.department().equals("Development"))
+                .min(Comparator.comparing(Employee::age));
+            if(optional2.isPresent()) {
+                writer.write(optional2.get().toString() + "\n\n");
+            }
+
+            // 9. Most experienced employee
+            writer.write("9. Most Experienced Employee:\n");
+            Optional<Employee> optional1 = emps.stream()
+                .collect(Collectors.minBy(Comparator.comparing(Employee::yearOfJoining)));
+            if(optional1.isPresent()) {
+                writer.write(optional1.get().toString() + "\n\n");
+            }
+
+            // 10. Male and Female in Sales
+            writer.write("10. Male and Female in Sales Team:\n");
+            Map<String, Long> map4 = emps.stream()
+                .filter(e -> e.department().equals("Sales"))
+                .collect(Collectors.groupingBy(Employee::gender, Collectors.counting()));
+            writer.write(map4.toString() + "\n\n");
+
+            // 11. Average and Total salary
+            writer.write("11. Average and Total Salary of Organization:\n");
+            String result4 = emps.stream()
+                .collect(Collectors.teeing(
+                    Collectors.averagingDouble(Employee::salary),
+                    Collectors.summingDouble(Employee::salary),
+                    (avg, total) -> "Average: " + avg + ", Total: " + total)
+                );
+            writer.write(result4 + "\n\n");
+
+            // 12. Partition by age
+            writer.write("12. Employees <= 25 years:\n");
+            Map<Boolean, List<Employee>> collect2 = emps.stream()
+                .collect(Collectors.partitioningBy(emp -> emp.age() <= 25));
+            List<Employee> list1 = collect2.get(true);
+            List<Employee> list2 = collect2.get(false);
+            writer.write(list1.toString() + "\n\n");
+            writer.write("12b. Employees > 25 years:\n");
+            writer.write(list2.toString() + "\n\n");
+
+            // 13. Oldest employee
+            writer.write("13. Oldest Employee:\n");
+            Optional<Employee> max = emps.stream()
+                .max(Comparator.comparing(Employee::age));
+            max.ifPresentOrElse(e -> {
+                try {
+                    writer.write(e.toString() + "\n");
+                } catch (IOException ex) {
+                    ex.printStackTrace();
+                }
+            }, () -> {
+                try {
+                    writer.write("No employee available\n");
+                } catch (IOException ex) {
+                    ex.printStackTrace();
+                }
+            });
+
+            writer.close();
+            System.out.println("File 'employees_output.txt' created successfully!");
+
+        } catch (IOException e) {
+            System.out.println("Error creating file: " + e.getMessage());
+            e.printStackTrace();
+        }
+    }
+}

Java 8 Crash Course/Java 8 Streams/src/employees_output.txt

@@ -0,0 +1,71 @@
+===== EMPLOYEE DATA =====
+
+Employee[id=1, name=Jhansi, age=32, gender=Female, department=HR, yearOfJoining=2011, salary=25000.0]
+Employee[id=2, name=Smith, age=25, gender=Male, department=Sales, yearOfJoining=2015, salary=13500.0]
+Employee[id=3, name=David, age=29, gender=Male, department=Infrastructure, yearOfJoining=2012, salary=18000.0]
+Employee[id=4, name=Orlen, age=28, gender=Male, department=Development, yearOfJoining=2014, salary=32500.0]
+Employee[id=5, name=Charles, age=27, gender=Male, department=HR, yearOfJoining=2013, salary=22700.0]
+Employee[id=6, name=Cathy, age=43, gender=Male, department=Security, yearOfJoining=2016, salary=10500.0]
+Employee[id=7, name=Ramesh, age=35, gender=Male, department=Finance, yearOfJoining=2010, salary=27000.0]
+Employee[id=8, name=Suresh, age=31, gender=Male, department=Development, yearOfJoining=2015, salary=34500.0]
+Employee[id=9, name=Gita, age=24, gender=Female, department=Sales, yearOfJoining=2016, salary=11500.0]
+Employee[id=10, name=Mahesh, age=38, gender=Male, department=Security, yearOfJoining=2015, salary=11000.5]
+Employee[id=11, name=Gouri, age=27, gender=Female, department=Infrastructure, yearOfJoining=2014, salary=15700.0]
+Employee[id=12, name=Nithin, age=25, gender=Male, department=Development, yearOfJoining=2016, salary=28200.0]
+Employee[id=13, name=Swathi, age=27, gender=Female, department=Finance, yearOfJoining=2013, salary=21300.0]
+Employee[id=14, name=Buttler, age=24, gender=Male, department=Sales, yearOfJoining=2017, salary=10700.5]
+Employee[id=15, name=Ashok, age=23, gender=Male, department=Infrastructure, yearOfJoining=2018, salary=12700.0]
+Employee[id=16, name=Sanvi, age=26, gender=Female, department=Development, yearOfJoining=2015, salary=28900.0]
+
+===== QUERY RESULTS =====
+
+1. Male and Female Employee Count:
+{Male=11, Female=5}
+
+2. All Departments:
+HR
+Sales
+Infrastructure
+Development
+Security
+Finance
+
+3. Average Age by Gender:
+{Male=29.818181818181817, Female=27.2}
+
+4. Highest Paid Employee:
+Employee[id=8, name=Suresh, age=31, gender=Male, department=Development, yearOfJoining=2015, salary=34500.0]
+
+5. Employees Joined After 2015:
+Cathy
+Gita
+Nithin
+Buttler
+Ashok
+
+6. Employee Count Per Department:
+{Sales=3, Finance=2, Development=4, Infrastructure=3, HR=2, Security=2}
+
+7. Average Salary Per Department:
+{Sales=11900.166666666666, Finance=24150.0, Development=31025.0, Infrastructure=15466.666666666666, HR=23850.0, Security=10750.25}
+
+8. Youngest Male in Development Department:
+Employee[id=12, name=Nithin, age=25, gender=Male, department=Development, yearOfJoining=2016, salary=28200.0]
+
+9. Most Experienced Employee:
+Employee[id=7, name=Ramesh, age=35, gender=Male, department=Finance, yearOfJoining=2010, salary=27000.0]
+
+10. Male and Female in Sales Team:
+{Female=1, Male=2}
+
+11. Average and Total Salary of Organization:
+Average: 20231.3125, Total: 323701.0
+
+12. Employees <= 25 years:
+[Employee[id=2, name=Smith, age=25, gender=Male, department=Sales, yearOfJoining=2015, salary=13500.0], Employee[id=9, name=Gita, age=24, gender=Female, department=Sales, yearOfJoining=2016, salary=11500.0], Employee[id=12, name=Nithin, age=25, gender=Male, department=Development, yearOfJoining=2016, salary=28200.0], Employee[id=14, name=Buttler, age=24, gender=Male, department=Sales, yearOfJoining=2017, salary=10700.5], Employee[id=15, name=Ashok, age=23, gender=Male, department=Infrastructure, yearOfJoining=2018, salary=12700.0]]
+
+12b. Employees > 25 years:
+[Employee[id=1, name=Jhansi, age=32, gender=Female, department=HR, yearOfJoining=2011, salary=25000.0], Employee[id=3, name=David, age=29, gender=Male, department=Infrastructure, yearOfJoining=2012, salary=18000.0], Employee[id=4, name=Orlen, age=28, gender=Male, department=Development, yearOfJoining=2014, salary=32500.0], Employee[id=5, name=Charles, age=27, gender=Male, department=HR, yearOfJoining=2013, salary=22700.0], Employee[id=6, name=Cathy, age=43, gender=Male, department=Security, yearOfJoining=2016, salary=10500.0], Employee[id=7, name=Ramesh, age=35, gender=Male, department=Finance, yearOfJoining=2010, salary=27000.0], Employee[id=8, name=Suresh, age=31, gender=Male, department=Development, yearOfJoining=2015, salary=34500.0], Employee[id=10, name=Mahesh, age=38, gender=Male, department=Security, yearOfJoining=2015, salary=11000.5], Employee[id=11, name=Gouri, age=27, gender=Female, department=Infrastructure, yearOfJoining=2014, salary=15700.0], Employee[id=13, name=Swathi, age=27, gender=Female, department=Finance, yearOfJoining=2013, salary=21300.0], Employee[id=16, name=Sanvi, age=26, gender=Female, department=Development, yearOfJoining=2015, salary=28900.0]]
+
+13. Oldest Employee:
+Employee[id=6, name=Cathy, age=43, gender=Male, department=Security, yearOfJoining=2016, salary=10500.0]