一、Lambda 表达式基础
1. 替代匿名内部类
// 传统写法
Runnable r1 = new Runnable() {@Overridepublic void run() {System.out.println("Hello World");}
};// Lambda 写法
Runnable r2 = () -> {System.out.println("hello");};
2. 函数式接口排序
List<String> list = Arrays.asList("apple", "banana", "orange");// 传统 Comparator
list.sort(new Comparator<String>() {@Overridepublic int compare(String s1, String s2) {return s1.length() - s2.length();}
});// Lambda 写法
list.sort((s1, s2) -> s1.length() - s2.length());
二、Stream 流操作
1. 过滤(Filter)
List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6);// 获取所有偶数
List<Integer> evenNumbers = numbers.stream().filter(n -> n % 2 == 0).collect(Collectors.toList()); // [2, 4, 6]
2. 映射(Map)
List<String> words = Arrays.asList("java", "python", "c++");// 转为大写
List<String> upperCaseWords = words.stream().map(String::toUpperCase).collect(Collectors.toList()); // [JAVA, PYTHON, C++]
3. 排序(Sorted)
List<String> names = Arrays.asList("Tom", "Jerry", "Alice");// 按长度排序
List<String> sortedNames = names.stream().sorted((s1, s2) -> s1.length() - s2.length()).collect(Collectors.toList()); // [Tom, Alice, Jerry]
4. 收集(Collect)转set、map
// 转为 Set
Set<Integer> numberSet = numbers.stream().collect(Collectors.toSet());// 转为 Map
Map<String, Integer> wordLengthMap = words.stream().collect(Collectors.toMap(word -> word, word -> word.length()));
5. 去重(Distinct)
List<Integer> nums = Arrays.asList(1, 2, 2, 3, 3, 3);
List<Integer> distinctNums = nums.stream().distinct().collect(Collectors.toList()); // [1, 2, 3]
6. 限制和跳过(Limit & Skip)
// 分页操作:跳过前2个,取3个
List<Integer> page = numbers.stream().skip(2).limit(3).collect(Collectors.toList()); // [3, 4, 5]
7. 匹配(Match)
boolean hasEven = numbers.stream().anyMatch(n -> n % 2 == 0); // trueboolean allEven = numbers.stream().allMatch(n -> n % 2 == 0); // false
8. 统计(Count/Sum/Average)
long count = numbers.stream().count(); // 6int sum = numbers.stream().mapToInt(Integer::intValue).sum(); // 21OptionalDouble avg = numbers.stream().mapToInt(Integer::intValue).average(); // 3.5
9. 分组(GroupingBy)
List<String> languages = Arrays.asList("Java", "Python", "C++", "JavaScript");// 按字符串长度分组
Map<Integer, List<String>> groupByLength = languages.stream().collect(Collectors.groupingBy(String::length));
// 输出:{2=[C++], 4=[Java], 6=[Python], 10=[JavaScript]}
10. 连接字符串(Joining)
String joined = languages.stream().collect(Collectors.joining(", "));
// 输出:Java, Python, C++, JavaScript
三、并行流(Parallel Stream)
// 使用并行流提升处理速度
long count = numbers.parallelStream().filter(n -> n % 2 == 0).count();
总结特性:
-
Lambda 表达式:简化匿名内部类,使代码更简洁
-
Stream API:
-
链式调用:支持多个操作串联
-
延迟执行:只有遇到终止操作时才会执行
-
并行处理:通过
parallelStream()
实现并行化
-
-
常用操作分类:
-
中间操作:
filter
,map
,sorted
,distinct
等 -
终止操作:
collect
,forEach
,count
,reduce
等
-
通过组合这些操作,可以高效处理集合数据,且代码可读性大幅提升。
(望各位潘安、各位子健/各位彦祖、于晏不吝赐教!多多指正!🙏)