java基礎(chǔ)理論Stream的Filter與謂詞邏輯

更新時間：2022年03月16日 10:37:09 作者：字母哥哥

這篇文章主要為大家介紹了java基礎(chǔ)理論Stream的Filter與謂詞邏輯，有需要的朋友可以借鑒參考下，希望能夠有所幫助，祝大家多多進步，早日升職加薪

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一、基礎(chǔ)代碼準備

建立一個實體類，該實體類有五個屬性。下面的代碼使用了lombok的注解Data、AllArgsConstructor，這樣我們就不用寫get、set方法和全參構(gòu)造函數(shù)了。lombok會幫助我們在編譯期生成這些模式化的代碼。

@Data
@AllArgsConstructor
public class Employee {
   private Integer id;
   private Integer age;   //年齡
   private String gender;  //性別
   private String firstName;  
   private String lastName;
}

寫一個測試類，這個測試類的內(nèi)容也很簡單，新建十個Employee 對象

public class StreamFilterPredicate {
    public static void main(String[] args){
        Employee e1 = new Employee(1,23,"M","Rick","Beethovan");
        Employee e2 = new Employee(2,13,"F","Martina","Hengis");
        Employee e3 = new Employee(3,43,"M","Ricky","Martin");
        Employee e4 = new Employee(4,26,"M","Jon","Lowman");
        Employee e5 = new Employee(5,19,"F","Cristine","Maria");
        Employee e6 = new Employee(6,15,"M","David","Feezor");
        Employee e7 = new Employee(7,68,"F","Melissa","Roy");
        Employee e8 = new Employee(8,79,"M","Alex","Gussin");
        Employee e9 = new Employee(9,15,"F","Neetu","Singh");
        Employee e10 = new Employee(10,45,"M","Naveen","Jain");
        List<Employee> employees = Arrays.asList(e1, e2, e3, e4, e5, e6, e7, e8, e9, e10);
        List<Employee> filtered = employees.stream()
                .filter(e -> e.getAge() > 70 && e.getGender().equals("M"))
                .collect(Collectors.toList());
        System.out.println(filtered);

    }

}

需要注意的是上面的filter傳入了lambda表達式(之前的章節(jié)我們已經(jīng)講過了)，表達過濾年齡大于70并且男性的Employee員工。輸出如下：

[Employee(id=8, age=79, gender=M, firstName=Alex, lastName=Gussin)]

二、什么是謂詞邏輯？

下面要說我們的重點了，通過之前的章節(jié)的講解，我們已經(jīng)知道lambda表達式表達的是一個匿名接口函數(shù)的實現(xiàn)。那具體到Stream.filter()中，它表達的是什么呢？看下圖：可以看出它表達的是一個Predicate接口，在英語中這個單詞的意思是：謂詞。

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什么是謂詞？（百度百科）

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什么是謂詞邏輯？

WHERE 和 AND 限定了主語employee是什么，那么WHERE和AND語句所代表的邏輯就是謂詞邏輯

SELECT *
FROM employee
WHERE age > 70
AND gender = 'M'

三、謂詞邏輯的復用

通常情況下，filter函數(shù)中l(wèi)ambda表達式為一次性使用的謂詞邏輯。如果我們的謂詞邏輯需要被多處、多場景、多代碼中使用，通常將它抽取出來單獨定義到它所限定的主語實體中。比如：將下面的謂詞邏輯定義在Employee實體class中。

   public static Predicate<Employee> ageGreaterThan70 = x -> x.getAge() >70;
   public static Predicate<Employee> genderM = x -> x.getGender().equals("M");

3.1.and語法（并集）

List<Employee> filtered = employees.stream()
        .filter(Employee.ageGreaterThan70.and(Employee.genderM))
        .collect(Collectors.toList());

輸出如下：

[Employee(id=8, age=79, gender=M, firstName=Alex, lastName=Gussin)]

3.2.or語法（交集）

List<Employee> filtered = employees.stream()
        .filter(Employee.ageGreaterThan70.or(Employee.genderM))
        .collect(Collectors.toList());

輸出如下：實際上就是年齡大于70的和所有的男性（由于79的那位也是男性，所以就是所有的男性）

[Employee(id=1, age=23, gender=M, firstName=Rick, lastName=Beethovan), Employee(id=3, age=43, gender=M, firstName=Ricky, lastName=Martin), Employee(id=4, age=26, gender=M, firstName=Jon, lastName=Lowman), Employee(id=6, age=15, gender=M, firstName=David, lastName=Feezor), Employee(id=8, age=79, gender=M, firstName=Alex, lastName=Gussin), Employee(id=10, age=45, gender=M, firstName=Naveen, lastName=Jain)]

3.3.negate語法（取反）

List<Employee> filtered = employees.stream()
        .filter(Employee.ageGreaterThan70.or(Employee.genderM).negate())
        .collect(Collectors.toList());

輸出如下：把上一小節(jié)代碼的結(jié)果取反，實際上就是所有的女性

[Employee(id=2, age=13, gender=F, firstName=Martina, lastName=Hengis), Employee(id=5, age=19, gender=F, firstName=Cristine, lastName=Maria), Employee(id=7, age=68, gender=F, firstName=Melissa, lastName=Roy), Employee(id=9, age=15, gender=F, firstName=Neetu, lastName=Singh)]

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