Java流操作总结
2020-08-10 本文已影响0人
岛上码农
Java流(Stream)操作自Java 8引入,通过Stream操作可以简化代码编写,提高代码执行效率。流整体操作分为创建(Supplier)、转换、约简和收集几个操作。
创建流
创建流最常见的方式是调用Collection.stream()方法,将集合数据转换为流,也可以通过generate方法创建流。如下所示:
public static void main(String[] args) {
//从Collection中产生流
ArrayList<String> strings = new ArrayList<>();
for (int i = 0; i < 20; ++i) {
strings.add("string" + i);
}
Stream<String> stringStream = strings.stream();
show("stringStream", stringStream);
//使用generate产生流
Stream<Integer> integerStream = Stream.generate(() -> (int) (Math.random() * 100));
show("integerStream", integerStream);
//使用iterate产生序列
Stream<Integer> integerStream1 = Stream.iterate(0, n -> n + 1);
show("integerStream1", integerStream1);
//使用of方法创建流
Stream<String> stringStream1 = Stream.of("Bob", "Mark", "Alice", "Edd");
show("stringStream1", stringStream1);
//正则表达式产生流
String sentences = "I had a dog whose name was Bingo. B, I, N, G, O, Bingo was his name, Oh!";
Stream<String> words = Pattern.compile("\\PL+").splitAsStream(sentences);
show("PatterStream", words);
}
public static<T> void show(String title, Stream<T> stream) {
final int size = 10;
List<T> array = stream.limit(size).collect(Collectors.toList());
System.out.println(title + ": ");
for (int i = 0; i < array.size(); ++i) {
if (i > 0) {
System.out.print(", ");
}
if (i < array.size()) {
System.out.print(array.get(i));
} else {
System.out.print("...");
}
}
System.out.println();
}
流的转换
流的转换即将一个给定的流通过流的方法转换为另一个流,常见的方法有filter,map,distinct, sorted,reverse等方法。
- filter方法保留满足filter方法中的条件表达式的元素;
- map方法可以对流中的元素进行一个转换操作;
- distinct方法将流中重复的元素去除
- sorted按给定的比较方法进行排序
String sentences = "I had a dog whose name was Bingo. B, I, N, G, O, Bingo was his name, Oh!";
//保留长度大于2的单词
Stream<String> words1 = Pattern.compile("\\PL+").splitAsStream(sentences).filter(s -> s.length() > 2);
show("PatterStream1", words1);
//将单词转换为大写
Stream<String> words2 = Pattern.compile("\\PL+").splitAsStream(sentences).map(String::toUpperCase);
show("PatterStream2", words2);
//去除重复的单词
Stream<String> words3 = Pattern.compile("\\PL+").splitAsStream(sentences).distinct();
show("PatterStream3", words3);
//按长度对单词进行排序
Stream<String> words4 = Pattern.compile("\\PL+").splitAsStream(sentences).sorted(Comparator.comparing(String::length));
show("PatterStream4", words4);
//按长度对单词进行排序后反序
Stream<String> words5 = Pattern.compile("\\PL+").splitAsStream(sentences).sorted(Comparator.comparing(String::length).reversed());
show("PatterStream4", words5);
流的约减(Reduce)
流经过处理后,提供了一系列方法从流中抽取数据。抽取数据是一种终结操作,常用的方法如下:
- count方法:获取流中满足条件的元素个数
- min、max方法:按照给定的比较方法获取最小最大值,注意该方法返回的是一个Optional<T>的包装类,这是因为流可能为空。
- find查找方法:包括findFirst,findAny等。
- match方法:根据条件查找是否有匹配条件的元素,有anyMatch,allMatch和noneMatch,返回的是boolean类型。
- 消费流:通过方法消费流中的元素,例如使用forEach迭代,传递方法处理流中的每个元素。
- 转换为Collection或数组:通过collect方法传递Collectors类提供的toCollection方法可以转换为Collection或者调用toArray方法转换为数组。
- 拼接:使用Collectors.join方法可以拼接流.
- 统计,使用IntSummaryStatistics、DoubleSummaryStatistics和LongSummaryStatistics方法构造统计对象,获取 总数,平均值,最大值,最小值。需要注意调用Collectors.summarizing{Int,Double, Long}方法需要传递一个lambda表达式,确定统计的内容。
//获取单词的数量
long wordsCount = Pattern.compile("\\PL+").splitAsStream(sentences).filter(s -> s.length() > 2).count();
System.out.println("Number of words length greater than 2: " + wordsCount);
//获取最长的单词
Optional<String> longestWord = Pattern.compile("\\PL+").splitAsStream(sentences).max(Comparator.comparing(String::length));
System.out.println("longestWord: " + longestWord.orElse("null"));
//获取最短的单词
Optional<String> shortestWord = Pattern.compile("\\PL+").splitAsStream(sentences).min(Comparator.comparing(String::length));
System.out.println("shortestWord: " + shortestWord.orElse("null"));
//获取第一个以h开头的单词
Optional<String> firstWordsStartWithH = Pattern.compile("\\PL+").splitAsStream(sentences)
.filter(s -> s.toLowerCase().startsWith("h")).findFirst();
System.out.println("firstWordsStartWithH: " + firstWordsStartWithH.orElse("Not Found"));
//获取任何一个以h开头的单词
Optional<String> anyWordsStartWithH = Pattern.compile("\\PL+").splitAsStream(sentences)
.filter(s -> s.toLowerCase().startsWith("h")).findAny();
System.out.println("anyWordsStartWithH: " + anyWordsStartWithH.orElse("Not Found"));
//查找其中是否有was这个单词
boolean hasWas = Pattern.compile("\\PL+").splitAsStream(sentences).anyMatch("was"::equals);
System.out.println("hasWas: " + hasWas);
//查找其中全部是was这个单词
boolean allWas = Pattern.compile("\\PL+").splitAsStream(sentences).allMatch("was"::equals);
System.out.println("allWas: " + allWas);
//使用forEach方法打印全部单词的大写
Pattern.compile("\\PL+").splitAsStream(sentences).map(String::toUpperCase).forEach(System.out::print);
//将流转为Collection
List<String> wordsList = Pattern.compile("\\PL+").splitAsStream(sentences).collect(Collectors.toList());
System.out.println("wordsList: " + wordsList);
//将流转为数组
String[] wordsArray = Pattern.compile("\\PL+").splitAsStream(sentences).toArray(String[]::new);
System.out.println("wordsArray: " + Arrays.toString(wordsArray));
//将流拼接为字符串
String wordsToSentences = Pattern.compile("\\PL+").splitAsStream(sentences).collect(Collectors.joining(", "));
System.out.println("wordsToSentences: " + wordsToSentences);
//数据统计:统计单词的长度
IntSummaryStatistics lengthSummary = Pattern.compile("\\PL+").splitAsStream(sentences).
collect(Collectors.summarizingInt(String::length));
System.out.println("Longest word length: " + lengthSummary.getMax());
System.out.println("Shortest word length: " + lengthSummary.getMin());
System.out.println("Average word length: " + lengthSummary.getAverage());
- 收集到Map:使用Collectors.toMap转到Map数据中。
- 分组:使用groupingBy进行分组
public static class User {
private String name;
private int id;
//1=male, 0 = female, 2= unknown
private int sex = 2;
public User(int id, String name, int sex) {
this.id = id;
this.name = name;
if (sex == 0 || sex == 1) {
this.sex = sex;
}
}
public int getId() {
return id;
}
public String getName() {
return name;
}
public int getSex() {
return sex;
}
@Override
public String toString() {
return "User{id = " + id + ", name = " + name + ", sex = " + sex + "}";
}
}
//省略部分代码...
public static Stream<User> userStream() {
return Stream.of(
new User(1, "Box", 1),
new User(2, "Succi", 0),
new User(3, "Lily", 0),
new User(4, "Sara", 0),
new User(5, "Mark", 1)
);
}
//main方法
public static void main(String[] args) {
//...
//映射为id -> User格式
Map<Integer, User> userMap = userStream().collect(Collectors.toMap(User::getId, Function.identity()));
for (Integer key:userMap.keySet()) {
System.out.println("id " + key + ": " + userMap.get(key));
}
//映射为id -> User.name格式
Map<Integer, String> idToNameMap = userStream().collect(Collectors.toMap(User::getId, User::getName));
System.out.println(idToNameMap);
//按性别分组
Map<Integer, Set<User>> sexToUserMap = userStream().collect(Collectors.groupingBy(User::getSex, Collectors.toSet()));
for (Integer key:sexToUserMap.keySet()) {
Set<User> usersOfSex = sexToUserMap.get(key);
System.out.println("Sex " + key + ": " + usersOfSex);
}
}