从一个Stream中过滤null值
复习一个Stream 包含 null 数据的例子.
Java8Examples.java
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package com.mkyong.java8; import java.util.List;import java.util.stream.Collectors;import java.util.stream.Stream; public class Java8Examples { public static void main(String[] args) { Stream<String> language = Stream.of("java", "python", "node", null, "ruby", null, "php"); List<String> result = language.collect(Collectors.toList()); result.forEach(System.out::println); }} |
output
java
python
node
null // <--- NULL
ruby
null // <--- NULL
php
Solution（解决）
为了解决上面的问题，我们使用： Stream.filter(x -> x!=null)
Java8Examples.java
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package com.mkyong.java8; import java.util.List;import java.util.stream.Collectors;import java.util.stream.Stream; public class Java8Examples { public static void main(String[] args) { Stream<String> language = Stream.of("java", "python", "node", null, "ruby", null, "php"); //List<String> result = language.collect(Collectors.toList()); List<String> result = language.filter(x -> x!=null).collect(Collectors.toList()); result.forEach(System.out::println); }} |
output
java
python
node
ruby
php
另外，过滤器还可以用： Objects::nonNull
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import java.util.List;List<String> result = language.filter(Objects::nonNull).collect(Collectors.toList()); |
stream方法过滤条件的使用
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@Data@AllArgsConstructor public class User { private Long id; // id private Integer age; // 年龄 private Byte gentle; // 性别 private String name; // 名字 private Integer rank; // 排名 } User user0 = new User(1L, 18, (byte) 0, "张三", 1); User user1 = new User(2L, 20, (byte) 1, "李四", 4); User user2 = new User(3L, 35, (byte) 0, "王五", 2); User user3 = new User(4L, 29, (byte) 1, "赵六", 3); |
下面以List为例
实际上只要是Collection的子类，玩法都类似
1、生成stream
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List<User> list = Arrays.asList(user0, user1, user2, user3);Stream<User> stream = null;stream = list.stream(); // 需要预判NPEstream = Optional.of(list).orElseGet(Collections::emptyList).stream(); // 需要预判NPEstream = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream();stream = Optional.ofNullable(list).orElseGet(Collections::emptyList).parallelStream(); // 并行处理流stream = Stream.of(user0, user1, user2, user3).parallel(); // 直接构造stream = Stream.of(Arrays.asList(user0, user1), Arrays.asList(user2, user3)).flatMap(Collection::stream); // flatMap合并 |
2、stream操作
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// 过滤出性别为0的userList<User> userList = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().filter(user -> (byte) 0 == user.getGentle()).collect(Collectors.toList()); // 获取排名大于1的用户年龄setSet<Integer> ageList = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().filter(user -> 1 < user.getRank()).map(User::getAge).collect(Collectors.toSet()); // 合计性别为0的user的年龄Integer totalAge = Optional.ofNullable(userList).orElseGet(Collections::emptyList).stream().map(User::getAge).reduce(0, Integer::sum); // 按排名倒序排列List<User> sortedUserList = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().sorted(Comparator.comparing(User::getRank, Comparator.reverseOrder())).collect(Collectors.toList()); // 获取排名第2高的userUser rankUser = Optional.ofNullable(sortedUserList).orElseGet(Collections::emptyList).stream().skip(1).findFirst().get(); // 排名最高的userUser highestRankUser = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().max(Comparator.comparing(User::getRank)).get(); // 是否存在排名大于1的userboolean flag = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().anyMatch(user -> user.getRank() > 1); // 是否所有user排名都大于1boolean flag = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().allMatch(user -> user.getRank() > 1); // 是否所有user排名都不大于5boolean flag = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().noneMatch(user -> user.getRank() > 5); // 按唯一id分组Map<Long, User> idUserMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.toMap(User::getId, Function.identity())); // 按唯一id,名字分组Map<Long, String> idNameMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.toMap(User::getId, User::getName)); // 按年龄,名字分组，相同年龄的后出现的被覆盖Map<Integer, String> ageNameMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.toMap(User::getAge, User::getName, (a, b) -> a)); // 按性别分组Map<Byte, List<User>> gentleUserMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.groupingBy(User::getGentle)); // 按排名是否大于3分组Map<Boolean, List<User>> partitionUserMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.partitioningBy(user -> user.getRank() > 3)); // 按性别名字分组Map<Byte, List<String>> gentleNameMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.groupingBy(User::getGentle, Collectors.mapping(User::getName, Collectors.toList()))); // 按性别年龄总和分组Map<Byte, Integer> gentleTotalAgeMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.groupingBy(User::getGentle, Collectors.reducing(0, User::getAge, Integer::sum))); // 迭代操作Stream.iterate(0, i -> i + 1).limit(list.size()).forEach(i -> { System.out.println(list.get(i).getName());}); // guava table转换Table<Long, String, Integer> idNameRankTable = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().map(user -> ImmutableTable.of(user.getId(), user.getName(), user.getRank())).collect(HashBasedTable::create, HashBasedTable::putAll, HashBasedTable::putAll); |
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// stream只能被terminal一次，下面是错误示范Stream<User> stream = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream();stream.collect(Collectors.toMap(User::getId, Function.identity()));stream.collect(Collectors.toMap(User::getId, User::getName)); // java.lang.IllegalStateException: stream has already been operated upon or closed // ssc-common的com.meicloud.mcu.common.util.StreamUtil简单封装了一些流操作，欢迎试用 // 参考资料：https://www.ibm.com/developerworks/cn/java/j-lo-java8streamapi/index.html |
以上为个人经验，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/wangmuming/article/details/72747183
