Java8快速读取和写入文件.png
话不多说，先看题：
随机生成 Salary {name, baseSalary, bonus }的记录，如“wxxx,10,1”，每行一条记录，总共1000万记录，写入文本文件（UFT-8编码）， 然后读取文件，name的前两个字符相同的，其年薪累加，比如wx，100万，3个人，最后做排序和分组，输出年薪总额最高的10组：
| wx | 200万 | 10人 |
| lt | 180万 | 8人 |
| ... | ... | ... |
name 4位a-z随机，baseSalary [0,100]随机 bonus[0-5]随机 ，年薪总额 = baseSalary*13 + bonus。
思路：
第一步：先编写一个Salary对象
里面包含有name，baseSalary, bounus属性，然后编写一个构造器，重写toString()方法方便序列化数据，同时编写构建Salary对象的方法build()；
/**
* name 4位a-z随机
* baseSalary 0-100随机
* bonus 0-5随机
* 年薪总额 = baseSalary * 13 + bonus
*/
class Salary {
// name 4位a-z随机,baseSalary 0-100随机,bonus 0-5随机 年薪总额 = baseSalary * 13 + bonus
private String name;
private int baseSalary;
private int bonus;
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public int getBaseSalary() {
return baseSalary;
}
public void setBaseSalary(int baseSalary) {
this.baseSalary = baseSalary;
}
public int getBonus() {
return bonus;
}
public void setBonus(int bonus) {
this.bonus = bonus;
}
public Salary() {
}
public Salary(String name, int baseSalary, int bonus) {
this.name = name;
this.baseSalary = baseSalary;
this.bonus = bonus;
}
public Salary build() {
this.name = getRandomName(4);
// 0-100随机数
this.baseSalary = (int)(100 * Math.random());
// 0-5随机数
this.bonus = (int)(5 * Math.random());
return this;
}
@Override
public String toString() {
return name + " " + baseSalary + " " + bonus;
}
/**
* 生产Name随机函数 4位a-z随机
* @param length
* @return
*/
private static String getRandomName(int length ){
String base = "abcdefghijklmnopqrstuvwxyz";
Random random = new Random();
StringBuffer sb = new StringBuffer();
for ( int i = 0; i < length; i++ ){
int number = random.nextInt(base.length());
sb.append(base.charAt(number));
}
return sb.toString();
}
}
第二步：编写写入方法
a) 第一种方式，使用Java的IO中BufferedWriter写入文件
/**
* 写入文件
* @return
* @throws IOException
*/
public static File writeBuffer() throws IOException {
File file = new File(FILE_NAME);
FileOutputStream fos = new FileOutputStream(file);
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(fos));
int i = AMOUNT;
while(i > 0) {
Salary salary = new Salary().build();
writer.write(salary.toString() + "\r\n");
i --;
}
writer.close();
fos.close();
return file;
}
b) 第二种方式，使用JAVA的NIO中的FileChannel进行写入
/**
* NIO进行写入
* @throws IOException
*/
private static void writeNIO() throws IOException {
FileOutputStream fos = new FileOutputStream(FILE_NAME, true);
FileChannel channel = fos.getChannel();
int i = AMOUNT;
StringBuffer content = new StringBuffer();
while(i > 0) {
Salary salary = new Salary().build();
content.append(salary.toString()).append("\r\n");
i --;
}
ByteBuffer buf = ByteBuffer.wrap(content.toString().getBytes());
buf.put(content.toString().getBytes());
buf.flip();
channel.write(buf);
channel.close();
fos.close();
}
比较下来，单纯从这个代码的性能上讲差不太多！
第三步：读取并解析文件在进行排序
a) 通过JAVA的IO进行读取：
/**
* Java IO读取文件的方式
* @return
* @throws Exception
*/
public static List<Salary> readFileIO() throws Exception {
File file = new File(FILE_NAME);
List<Salary> list = new ArrayList<>();
InputStreamReader reader = new InputStreamReader(new FileInputStream(file)); // 建立一个输入流对象reader
BufferedReader br = new BufferedReader(reader); // 建立一个对象，它把文件内容转成计算机能读懂的语言
String line = ""; // 每一行的内容
int i = 1;
while ((line = br.readLine()) != null) {
String[] split = line.trim().split(" ");// .trim()可以去掉首尾多余的空格
list.add(new Salary(split[0], Integer.valueOf(split[1]), Integer.valueOf(split[2]))); // 添加一个Salary实体
i++;
}
reader.close();
br.close();
return list;
}
b) 通过JAVA的NIO读取：
/**
* JDK8 NIO读取文件
* @return
* @throws Exception
*/
public static List<Salary> readFileNIO() throws Exception {
List<Salary> list = new ArrayList<>();
Files.lines(Paths.get(FILE_NAME)).forEach(line -> {
String[] split = line.trim().split(" ");// .trim()可以去掉首尾多余的空格
list.add(new Salary(split[0], Integer.valueOf(split[1]), Integer.valueOf(split[2]))); // 添加一个Salary实体
});
return list;
}
二者比较下来：使用jdk1.8读取更简单，效率性能更高！
第四步：使用JDK8的Stream进行排序和截取
/**
* 排序并获取前十数据
* @param salaries
*/
public static void sort(List<Salary> salaries) {
Map<String, GroupSalary> result = new HashMap<>();
salaries.forEach(salary -> {
String shortName = salary.getName().substring(0, 2);
GroupSalary groupSalary = null;
List<Salary> salaryList = null;
if (result.containsKey(shortName)) {
groupSalary = result.get(shortName);
salaryList = groupSalary.getSalaries();
} else {
groupSalary = new GroupSalary();
salaryList = new ArrayList<>();
groupSalary.setSalaries(salaryList);
}
salaryList.add(salary);
groupSalary.setShortName(shortName);
groupSalary.setTotal(groupSalary.getTotal() + salary.getBaseSalary() * 13 + salary.getBonus());
result.put(shortName, groupSalary);
});
List<GroupSalary> r = result.entrySet().stream()
.sorted((Map.Entry<String, GroupSalary> o1, Map.Entry<String, GroupSalary> o2) -> o2.getValue().getTotal() - o1.getValue().getTotal())
.map(entry -> entry.getValue()).collect(Collectors.toList()).subList(0,10);
r.forEach(groupSalary -> {
System.out.println(groupSalary.getShortName() + " " + groupSalary.getTotal() + " " + groupSalary.getSalaries().size());
});
}
同时将数据封装在GroupSalary中
class GroupSalary {
private List<Salary> salaries;
private String shortName;
private int total;
public List<Salary> getSalaries() {
return salaries;
}
public void setSalaries(List<Salary> salaries) {
this.salaries = salaries;
}
public String getShortName() {
return shortName;
}
public void setShortName(String shortName) {
this.shortName = shortName;
}
public int getTotal() {
return total;
}
public void setTotal(int total) {
this.total = total;
}
}
到此如果写入100W数据基本上1分钟不到就可以完成写入和读取，欢迎大家进行改写和优化。
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