[НП] - Генерички кластер

import java.util.*;

abstract class Element{
    protected long id;

    public Element(long id) {
        this.id = id;
    }

    public abstract double getDistance(Element el);
}

class Point2D extends Element{
    private float x;
    private float y;

    public Point2D(long id, float x, float y) {
        super(id);
        this.x = x;
        this.y = y;
    }

    public long getId() {
        return id;
    }

    public float getX() {
        return x;
    }

    public float getY() {
        return y;
    }

    public double getDistance(Element el){
        Point2D point = (Point2D) el;
        return Math.sqrt(Math.pow((x - point.x), 2) + Math.pow((y -point.y),2));
    }
}

class Cluster<T extends Point2D>{
    List<T> elements;

    public Cluster() {
        this.elements = new ArrayList<>();
    }

    public void addItem(T element){
        elements.add(element);
    }

    public void near(long id, int top){
        T element = null;
        for (T el:elements){
            if (el.id == id)
                element = el;
        }

        T finalElement = element;
        elements.sort(Comparator.comparing(el -> el.getDistance(finalElement)));
        for (int i=0; i<top; i++){
            System.out.println(String.format("%d. %d -> %.3f", i+1, elements.get(i+1).id, elements.get(i+1).getDistance(finalElement)));
        }
    }
}

public class ClusterTest {
    public static void main(String[] args) {
        Scanner scanner = new Scanner(System.in);
        Cluster<Point2D> cluster = new Cluster<>();
        int n = scanner.nextInt();
        scanner.nextLine();
        for (int i = 0; i < n; ++i) {
            String line = scanner.nextLine();
            String[] parts = line.split(" ");
            long id = Long.parseLong(parts[0]);
            float x = Float.parseFloat(parts[1]);
            float y = Float.parseFloat(parts[2]);
            cluster.addItem(new Point2D(id, x, y));
        }
        int id = scanner.nextInt();
        int top = scanner.nextInt();
        cluster.near(id, top);
        scanner.close();
    }
}