每位同学独立设计一个药店的药品销售统计系统，实现医药公司定期对销售各药品的记录进行统计，可按药品的编号、单价、销售量或销售额做出排名。在本系统中，对单价的排序采用冒泡排序法，对销售量的排序采用快速排序法，对销售额的排序采用堆排序法。 用读取文件的方法的JAVA代码实现

以下是一个简单的实现示例，假设数据文件的格式为每行包含药品编号、单价、销售量和销售额：

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;

public class DrugStoreStatistics {

    public static void main(String[] args) {
        String fileName = "sales_data.txt"; // 数据文件名
        int numDrugs = 100; // 假设药品数量不超过100
        Drug[] drugs = new Drug[numDrugs]; // 存储药品信息的数组

        // 读取数据文件并初始化药品数组
        try (BufferedReader br = new BufferedReader(new FileReader(fileName))) {
            String line;
            int i = 0;
            while ((line = br.readLine()) != null) {
                String[] fields = line.split("\\s+"); // 假设数据字段间用空格分隔
                int code = Integer.parseInt(fields[0]);
                double price = Double.parseDouble(fields[1]);
                int quantity = Integer.parseInt(fields[2]);
                double sales = Double.parseDouble(fields[3]);
                Drug drug = new Drug(code, price, quantity, sales);
                drugs[i++] = drug;
            }
        } catch (IOException e) {
            e.printStackTrace();
        }

        // 按单价排序
        bubbleSortByPrice(drugs);

        // 按销售量排序
        quickSortByQuantity(drugs, 0, numDrugs-1);

        // 按销售额排序
        heapSortBySales(drugs);

        // 输出排序结果
        for (Drug drug : drugs) {
            System.out.println(drug);
        }
    }

    // 药品类
    static class Drug {
        int code;
        double price;
        int quantity;
        double sales;

        public Drug(int code, double price, int quantity, double sales) {
            this.code = code;
            this.price = price;
            this.quantity = quantity;
            this.sales = sales;
        }

        @Override
        public String toString() {
            return String.format("%d\t%.2f\t%d\t%.2f", code, price, quantity, sales);
        }
    }

    // 冒泡排序按单价排序
    static void bubbleSortByPrice(Drug[] drugs) {
        int n = drugs.length;
        for (int i = 0; i < n-1; i++) {
            for (int j = 0; j < n-i-1; j++) {
                if (drugs[j].price > drugs[j+1].price) {
                    Drug temp = drugs[j];
                    drugs[j] = drugs[j+1];
                    drugs[j+1] = temp;
                }
            }
        }
    }

    // 快速排序按销售量排序
    static void quickSortByQuantity(Drug[] drugs, int left, int right) {
        if (left < right) {
            int pivot = partitionByQuantity(drugs, left, right);
            quickSortByQuantity(drugs, left, pivot-1);
            quickSortByQuantity(drugs, pivot+1, right);
        }
    }

    static int partitionByQuantity(Drug[] drugs, int left, int right) {
        Drug pivot = drugs[right];
        int i = left - 1;
        for (int j = left; j < right; j++) {
            if (drugs[j].quantity < pivot.quantity) {
                i++;
                Drug temp = drugs[i];
                drugs[i] = drugs[j];
                drugs[j] = temp;
            }
        }
        Drug temp = drugs[i+1];
        drugs[i+1] = drugs[right];
        drugs[right] = temp;
        return i+1;
    }

    // 堆排序按销售额排序
    static void heapSortBySales(Drug[] drugs) {
        int n = drugs.length;
        for (int i = n/2-1; i >= 0; i--) {
            heapifyBySales(drugs, n, i);
        }
        for (int i = n-1; i >= 0; i--) {
            Drug temp = drugs[0];
            drugs[0] = drugs[i];
            drugs[i] = temp;
            heapifyBySales(drugs, i, 0);
        }
    }

    static void heapifyBySales(Drug[] drugs, int n, int i) {
        int largest = i;
        int left = 2*i + 1;
        int right = 2*i + 2;
        if (left < n && drugs[left].sales > drugs[largest].sales) {
            largest = left;
        }
        if (right < n && drugs[right].sales > drugs[largest].sales) {
            largest = right;
        }
        if (largest != i) {
            Drug temp = drugs[i];
            drugs[i] = drugs[largest];
            drugs[largest] = temp;
            heapifyBySales(drugs, n, largest);
        }
    }
}

注意：以上代码仅供参考，实际场景下需要根据具体需求进行修改和优化。