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java Stream流常用方法（全）

网友: 文档中心 2022-03-18 08:54:40

Stream流用法

    • 1、分组
    • 2、过滤
    • 3、List map互转
    • 4、求和/极值
    • 5、求最大/最小值的对象
    • 6、去重
    • 7、排序
    • 8、拼接
    • 9、统计
    • 10、平均值
    • 11、某个值的数量
    • 12、分区
    • 13、截断
    • 14、跳过
    • 15、查找与匹配
    • 16、收集
    • 17、全部转大写

1、分组

// 按照sn分组:  List<Map> dataListMap<String, List<Map<String, Object>>> dataMap = dataList.stream().collect(Collectors.groupingBy(e -> e.get("sn") + ""));//按照职员部分分组: List listMap<String, List<Employee>> collect = list.stream().collect(Collectors.groupingBy(i -> i.getUnitName()));//多条件分组Map<String, Map<String,List<Employee>>> collect =list.stream().collect(Collectors.groupingBy(i -> i.getUnitName(),Collectors.groupingBy(i -> i.getWorkType()))); //按年龄分组，年龄相同的是一组 Map<Integer, List<Person>> 分组 = list.stream().collect(Collectors.groupingBy(Person::getAge));  //按年龄分组后按工资分组，多级分组 Map<Integer, Map<String, List<Person>>> 多级分组 = list.stream().collect(Collectors.groupingBy(Person::getAge, Collectors.groupingBy(x -> {     return x.getSalary() > 3000 ? "高" : "低"; }))); // 分组排序 ，拿已经排好序的过来分组LinkedHashMap<String, List<AttendanceRuleGroup>> groupingByruleGroupList = ruleGroupList.stream().collect(Collectors.groupingBy(AttendanceRuleGroup::getCategory, LinkedHashMap::new, Collectors.toList()));// 分组排序，集合没排序，我们自己按我们想要的排序 LinkedHashMap<String, List<AttendanceRuleGroup>> groupingByruleGroupList = ruleGroupList.stream().sorted(Comparator.comparingLong(AttendanceRuleGroup::getSort).reversed()).collect(Collectors.groupingBy(AttendanceRuleGroup::getCategory, LinkedHashMap::new, Collectors.toList()));

2、过滤

//根据指定sn,过滤出符合的数据: List<Map> deviceDataListList<Map<String, Object>> tempDeviceDataList = deviceDataList.stream().filter(map -> map.get("sn").toString().equals(sn)).collect(Collectors.toList());//筛选出工资大于10000的职员List<Employee> newList = list.stream().filter(item -> {return item.getSalary().compareTo(new BigDecimal(10000)) > 0 && !item.getWorkType().equals("项目经理");}).collect(Collectors.toList());

3、List map互转

1、list转map

// (k1,k2)->k2 避免键重复 k1-取第一个数据；k2-取最后一条数据//key和value,都可以根据传入的值返回不同的MapMap<String, String> deviceMap = hecmEnergyDevicesList.stream().collect(Collectors.toMap(i -> i.getDeviceNum(), j -> j.getDeviceName(), (k1, k2) -> k1));//Map<String, Object> map = list.stream().collect(Collectors.toMap(i -> i.getEmpName() + i.getUnitName(), j -> j, (k1, k2) -> k1));

2、map转list

//在.map里面构造数据 return什么数据就转成什么类型的listList<Employee> collect = map.entrySet().stream().map(item -> {Employee employee = new Employee();employee.setId(item.getKey());employee.setEmpName(item.getValue());return employee;}).collect(Collectors.toList());

4、求和/极值

//在egyList里面求cols的和public static BigDecimal getSumBig(List<Map<String,Object>> egyList, String cols){ BigDecimal consuBig = egyList.stream()  .filter((Map m)->StringUtils.isNotEmpty(m.get(cols)+"") && !"null".equals(String.valueOf(m.get(cols)))   && !"-".equals(String.valueOf(m.get(cols))))  .map((Map m)->new BigDecimal(m.get(cols)+""))  .reduce(BigDecimal.ZERO,BigDecimal::add); return consuBig;}//List list//Bigdecimal求和/极值: BigDecimal sum = list.stream().map(Employee::getSalary).reduce(BigDecimal.ZERO,BigDecimal::add);BigDecimal max = list.stream().map(Employee::getSalary).reduce(BigDecimal.ZERO,BigDecimal::max);//基本数据类型求和/极值:Integer sum = list.stream().mapToInt(Employee::getId).sum();OptionalInt optionalMax = list.stream().mapToInt(Employee::getId).max();optionalMax.getAsInt();

5、求最大/最小值的对象

Optional<Employee> optional = list.stream().collect(Collectors.maxBy(Comparator.comparing(Employee::getId))); if (optional.isPresent()) { // 判断是否有值 Employee user = optional.get(); }return optional.orElse(new Employee());

6、去重

//去重之后进行拼接: List deviceNodeListSrting deviceNodeStr = deviceNodeList.stream().distinct().collect(Collectors.joining("','"));//直接去重返回list// List deviceIdList List<String> deviceIdList = deviceIdList.stream().distinct().collect(Collectors.toList());

7、排序

//按照时间排序 1升 -1降Collections.sort(listFast, (p1, p2) -> {     return String.valueOf(p1.get("time")).compareTo(p2.get("time") + "");});// s1-s2 升序   s2-s1降序Collections.sort(list,(s1,s2) -> s1.getSalary().compareTo(s2.getSalary()));//多条件排序: List list, s1-s2 升序   s2-s1降序list.sort(Comparator.comparing(Employee::getSalary).reversed().thenComparing(Employee::getId).reversed());

8、拼接

//将某个字段,按照某个字符串拼接:  List<Map> deviceMapList String sns = deviceMapList.stream()     .map((m)->m.get("sn")+"").collect(Collectors.joining(","));//使用场景很多,在sql里面用于组织in的值.比如:SELECT sn,time,value FROM electric_real_time WHERE FIND_IN_SET(sn,?)List<Map<String, Object>> dataList = JdbcUtil.getJdbcTemplate().queryForList(dataSql, sns) List<String> strs = Arrays.asList("a","b","cd");  //连接所有内容 String str = strs.stream().collect(Collectors.joining()); System.out.println(str); //输出：abcd  //连接所有内容,中间加一个逗号隔开 String str1 = strs.stream().collect(Collectors.joining(",")); System.out.println(str1); //输出：a,b,cd  //连接所有内容,中间加一个逗号隔开，两边加上括号 String str2 = strs.stream().collect(Collectors.joining(",","(",")")); System.out.println(str2); //输出：(a,b,cd)

9、统计

//统计：和、数量、最大值、最小值、平均值: List listIntSummaryStatistics collect = list.stream().collect(Collectors.summarizingInt(Employee::getId));System.out.println("和：" + collect.getSum());System.out.println("数量：" + collect.getCount());System.out.println("最大值：" + collect.getMax());System.out.println("最小值：" + collect.getMin());System.out.println("平均值：" + collect.getAverage());

10、平均值

OptionalDouble average = list.stream().mapToInt(Employee::getId).average();average.getAsDouble();

11、某个值的数量

//List listMap<BigDecimal, Long> collect = list.stream().collect(Collectors.groupingBy(i -> i.getSalary(),Collectors.counting()));//List<Map> egyListlong count = egyList.stream()     .filter((Map m)->StringUtils.isNotEmpty(m.get(cols)+""))     .map((Map m)->new BigDecimal(m.get(cols)+""))     .count();

12、分区

//List list//单层分区Map<Boolean, List<Employee>> collect = list.stream().collect(Collectors.partitioningBy(i -> i.getId() == 1));//分区 满足条件的一个区，不满足条件的一个区 Map<Boolean, List<Person>> collect1 = list.stream().collect(Collectors.partitioningBy(e -> e.getSalary() < 2000));//多层分区Map<Boolean, Map<Boolean,List<Employee>>> collect = list.stream().collect(Collectors.partitioningBy(i -> i.getId() == 1,Collectors.partitioningBy(i -> i.getSalary().compareTo(new BigDecimal(20000)) == 0)));

13、截断

 List<Integer> list = Arrays.asList(1,2,3,4,5,6,7,8);  //中间操作：不会执行任何操作 Stream<Integer> stream = list.stream()  .filter(e -> {      System.out.println("过滤 中间操作");      return e>3;  })  .limit(2);  //终止操作：一次性执行全部内容，惰性求值 stream.forEach(System.out::println);

14、跳过

 List<Integer> list = Arrays.asList(1,2,3,4,5,6,7,8);  //中间操作：不会执行任何操作 Stream<Integer> stream = list.stream()  .skip(5);  //终止操作：一次性执行全部内容，惰性求值 stream.forEach(System.out::println);

15、查找与匹配

 List<Person> list = Arrays.asList(  new Person(18,3939),  new Person(38,9999),  new Person(17,9999),  new Person(19,9988),  new Person(38,99) );  //是否匹配所有元素 此处返回false boolean b = list.stream().allMatch(e -> e.getAge() == 18); System.out.println(b);  //至少匹配一个元素，此处返回true boolean b1 = list.stream().anyMatch(e -> e.getAge() == 19); System.out.println(b1);  //流中是否没有匹配元素，此处返回false boolean b2 = list.stream().noneMatch(e -> e.getAge() == 19); System.out.println(b2);  //排序后获取第一个元素 Optional<Person> first = list.stream().sorted((x, y) -> x.getAge().compareTo(y.getAge())).findFirst(); System.out.println(first);  //获取流中任意一个元素 list.stream().findAny();  //返回流中元素的总个数 list.stream().count();  //返回流中最大值 此处根据年龄比较 Optional<Person> max = list.stream().max((x, y) -> x.getAge().compareTo(y.getAge())); System.out.println(max.get());  //返回流中最小值 此处根据年龄比较 Optional<Person> min = list.stream().min((x, y) -> x.getAge().compareTo(y.getAge())); System.out.println(min.get());  //获取最小的年龄 Optional<Integer> age = list.stream().map(Person::getAge).min(Integer::compareTo); System.out.println(age.get());   //获取一个并行流，并行流会使用多个线程操作流，stream()获取的是串行流，单个线程操作流 list.parallelStream(); //查找第一个元素 Optional<Dish> collect = menu.stream().filter(dish -> dish.getCalories() > 1000).findFrist();

16、收集

 //取出所有年龄放到list集合中 List<Integer> toList = list.stream().map(Person::getAge)  .collect(Collectors.toList());  //取出所有年龄放到set集合中 Set<Integer> toSet = list.stream().map(Person::getAge)  .collect(Collectors.toSet());  //取出所有年龄放到hashSet集合中 HashSet<Integer> toHashSet = list.stream().map(Person::getAge)  .collect(Collectors.toCollection(HashSet::new));  //获取集合中元素总和 Long count = list.stream().collect(Collectors.counting());  //获取年龄平均值 Double avg = list.stream().collect(Collectors.averagingInt(Person::getAge));  //获取工资总和 Double sum = list.stream().collect(Collectors.summingDouble(Person::getSalary));  //获取工资最大值的人 Optional<Person> max = list.stream().collect(Collectors.maxBy((p1, p2) -> Double.compare(p1.getSalary(), p2.getSalary()))); System.out.println(max.get());  //获取工资最小值的人 Optional<Person> min = list.stream().collect(Collectors.minBy((p1, p2) -> Double.compare(p1.getSalary(), p2.getSalary()))); System.out.println(min.get());  //获取元素个数、总和、最小值、平均值、最大值 DoubleSummaryStatistics collect = list.stream().collect(Collectors.summarizingDouble(Person::getSalary)); System.out.println(collect); //输出结果:DoubleSummaryStatistics{count=5, sum=34024.000000, min=99.000000, average=6804.800000, max=9999.000000}

17、全部转大写

 List<String> list = Arrays.asList("a","vvv","ddd");  //中间操作：不会执行任何操作 Stream<String> stream = list.stream()  .map(x -> x.toUpperCase());  //终止操作：一次性执行全部内容，惰性求值 stream.forEach(System.out::println);
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