Java8 分组
诗水人间 人气:0在SQL中经常会用到分组,我们也常常遇到一些组合分组的场景。
有下面的一个User类
import lombok.Builder; import lombok.Data; import java.time.LocalDateTime; @Data @Builder public class User { private String name; private int id; private String city; private String sex; private LocalDateTime birthDay; }
java8分组 传统写法(单个字段分组)
场景:根据 城市 进行分组
使用的是方法引用:User::getCity
来完成分组
import java.time.LocalDateTime; import java.time.format.DateTimeFormatter; import java.util.Arrays; import java.util.List; import java.util.Map; import java.util.stream.Collectors; public class Demo2 { public static void main(String[] args) { DateTimeFormatter df = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); // data list List<User> userList = Arrays.asList( User.builder().id(123456).name("Zhang, San").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(777777).name("Zhang, San").city("ShangHai").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(888888).name("Li, Si").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(999999).name("Zhan, San").city("HangZhou").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(555555).name("Li, Si").city("NaJin").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build() ); Map<String, List<User>> groupMap = userList.stream() .collect(Collectors.groupingBy(User::getCity)); groupMap.forEach((k, v) -> { System.out.println(k); System.out.println(v); }); } }
java8分组 传统写法(多个字段分组)
①
场景:根据 城市,性别
进行分组
一般的写法会是下面的这种写法,通过lambda表达式将key的生成逻辑传入进去:u -> u.getCity() + "|" + u.getSex()
来实现分组的效果。
import java.time.LocalDateTime; import java.time.format.DateTimeFormatter; import java.util.Arrays; import java.util.List; import java.util.Map; import java.util.stream.Collectors; public class Demo2 { public static void main(String[] args) { DateTimeFormatter df = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); // data list List<User> userList = Arrays.asList( User.builder().id(123456).name("Zhang, San").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(777777).name("Zhang, San").city("ShangHai").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(888888).name("Li, Si").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(999999).name("Zhan, San").city("HangZhou").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(555555).name("Li, Si").city("NaJin").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build() ); Map<String, List<User>> groupMap = userList.stream() .collect(Collectors.groupingBy(u -> u.getCity() + "|" + u.getSex())); groupMap.forEach((k, v) -> { System.out.println(k); System.out.println(v); }); } }
分析:多个分组条件 与 单个分组条件 两种写法
单个条件的分组用的比较多,userList.stream().collect(Collectors.groupingBy(User::getCity));
这种方法引用的方式看起来很清爽。
在我们遇到多个字段的分组的时候,我并不太想使用前面那种传统的写法①。
我在想,既然单个字段的分组写法是:
userList.stream().collect(Collectors.groupingBy(User::getCity));
那么多个字段的写法可否是下面这种( 类推 ),传入多个方法引用!
userList.stream().collect(Collectors.groupingBy(User::getCity,User::getSex));
很可惜 jdk 类库中Collectors 没有提供这种写法
多个字段的优雅写法
因为jdk没有提供这种写法,于是自己就想写了一个Util
来帮助我们使用多个方法引用的方式完成组合分组
MyBeanUtil groupingBy(userList, User::getSex, User::getCity);
Demo:
import java.time.LocalDateTime; import java.time.format.DateTimeFormatter; import java.util.*; import java.util.function.Function; import java.util.stream.Collectors; public class MyBeanUtil { public static void main(String[] args) { DateTimeFormatter df = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); // data list List<User> userList = Arrays.asList( User.builder().id(123456).name("Zhang, San").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(777777).name("Zhang, San").city("ShangHai").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(888888).name("Li, Si").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(999999).name("Zhan, San").city("HangZhou").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(555555).name("Li, Si").city("NaJin").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build() ); // 进行分组,根据名字和城市分组 Map<String, List<User>> groupMap = groupingBy(userList, User::getSex, User::getCity); //打印分组结果 groupMap.forEach((k, v) -> { System.out.println(k); System.out.println(v); }); } /** * 将数据分组,根据方法引用(bean的get方法) * * @param list 为分组的数据 * @param functions get方法数组 */ @SafeVarargs public static <T, R> Map<String, List<T>> groupingBy(List<T> list, Function<T, R>... functions) { return list.stream().collect(Collectors.groupingBy(t -> groupingBy(t, functions))); } /** * 分组工具根据函数式接口使用分组,将数据根据分组结果进行拆分 */ @SafeVarargs public static <T, R> String groupingBy(T t, Function<T, R>... functions) { if (functions == null || functions.length == 0) { throw new NullPointerException("functions数组不可以为空"); } else if (functions.length == 1) { return functions[0].apply(t).toString(); } else { return Arrays.stream(functions).map(fun -> fun.apply(t).toString()).reduce((str1, str2) -> str1 + "|" + str2).get(); } } }
再度优化
依然不是很满足这种写法,因为这种写法需要借助 Util 类,不够接地气!
我更希望是下面这种接地气的写法:能够完全集成在jdk类库中
userList.stream().collect(Collectors.groupingBy(User::getCity,User::getSex));
为了达到上述的效果,那么显然我们是需要修改jdk源代码的;
于是我就将java.util.stream.Collectors
源码完整copy出来,然后加入下面3个方法
public static <T, K> Collector<T, ?, HashMap<K, List<T>>> groupingBy(Function<? super T, ? extends K>... classifier) { return groupingBy("|", classifier); } public static <T, K> Collector<T, ?, HashMap<K, List<T>>> groupingBy(String split, Function<? super T, ? extends K>... classifier) { return groupingBy(split, classifier, HashMap::new, toList()); } public static <T, K, D, A, M extends Map<? super K, D>> Collector<T, ?, M> groupingBy(String split, Function<? super T, ? extends K>[] classifierArr, Supplier<M> mapFactory, Collector<? super T, A, D> downstream) { Supplier<A> downstreamSupplier = downstream.supplier(); BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator(); BiConsumer<Map<K, A>, T> accumulator = (m, t) -> { String key = Arrays.stream(classifierArr).map(classifier -> Objects.requireNonNull(classifier.apply(t))).map(String::valueOf).reduce((s1, s2) -> s1 + split + s2).get(); A container = m.computeIfAbsent((K) key, k -> downstreamSupplier.get()); downstreamAccumulator.accept(container, t); }; BinaryOperator<Map<K, A>> merger = Collectors.<K, A, Map<K, A>>mapMerger(downstream.combiner()); @SuppressWarnings("unchecked") Supplier<Map<K, A>> mangledFactory = (Supplier<Map<K, A>>) mapFactory; if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) { return new CollectorImpl<>(mangledFactory, accumulator, merger, CH_ID); } else { @SuppressWarnings("unchecked") Function<A, A> downstreamFinisher = (Function<A, A>) downstream.finisher(); Function<Map<K, A>, M> finisher = intermediate -> { intermediate.replaceAll((k, v) -> downstreamFinisher.apply(v)); @SuppressWarnings("unchecked") M castResult = (M) intermediate; return castResult; }; return new CollectorImpl<>(mangledFactory, accumulator, merger, finisher, CH_NOID); } }
就达到了我们预期的效果,为了方便大家也一起体验一下,我已经将demo完整的放到了github上
源码地址:https://github.com/1015770492/CollectorsDemo
下载好源码后,找到下面这个类
Demo:
import java.io.Serializable; import java.time.LocalDateTime; import java.time.format.DateTimeFormatter; import java.util.*; public class MultiGroupByDemo { public static void main(String[] args) { DateTimeFormatter df = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); // data list List<User> userList = Arrays.asList( User.builder().id(123456).name("Zhang, San").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(777777).name("Zhang, San").city("ShangHai").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(888888).name("Li, Si").city("ShangHai").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(999999).name("Zhan, San").city("HangZhou").sex("woman").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build(), User.builder().id(555555).name("Li, Si").city("NaJin").sex("man").birthDay(LocalDateTime.parse("2022-07-01 12:00:00", df)).build() ); /* * maybe we can */ // 1.Use the default vertical separator System.out.println("Use the default vertical separator:"); HashMap<String, List<User>> defaultSpilt = userList.stream().collect(Collectors.groupingBy(User::getName, User::getCity)); printMap(defaultSpilt); System.out.println(); // 2.Use custom delimiters System.out.println("Use custom delimiters:"); userList.stream().collect(Collectors.groupingBy("--", User::getName, User::getCity, User::getId)); HashMap<? extends Serializable, List<User>> collect = userList.stream().collect(Collectors.groupingBy("--", User::getName, User::getCity, User::getId)); printMap(collect); System.out.println(); // 3.Use custom delimiters System.out.println("Use custom delimiters:"); userList.stream().collect(Collectors.groupingBy("--", User::getName, User::getCity, User::getId)); HashMap<? extends Serializable, List<User>> collect2 = userList.stream().collect(Collectors.groupingBy(User::getName, User::getCity, User::getBirthDay)); printMap(collect2); } public static <T> void printMap(Map<? extends Serializable, List<T>> map){ map.forEach((k, v) -> { System.out.println(k); System.out.println(v); }); } }
最后我希望这个特性能被JDK所吸收,这样可以方便大家更好的使用这些好用的特性
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