使用java8 新特性stream流对List＜Map＜String, Object＞＞集合进行遍历、过滤、查询、去重、排序、分组

对于一个List>类型的数据，可以使用Java 8的新特性stream流来进行遍历、过滤、查询、去重、排序、分组等操作。

遍历：

List> dataList = new ArrayList>();//添加数据Map map1 = new HashMap();map1.put("id", 1);map1.put("name", "张三");dataList.add(map1);Map map2 = new HashMap();map2.put("id", 2);map2.put("name", "李四");dataList.add(map2);//使用stream流进行遍历dataList.stream().forEach(map -> {    System.out.println("id：" + map.get("id") + "，name：" + map.get("name"));});

过滤：

List> dataList = new ArrayList>();//添加数据Map map1 = new HashMap();map1.put("id", 1);map1.put("name", "张三");map1.put("age", 20);dataList.add(map1);Map map2 = new HashMap();map2.put("id", 2);map2.put("name", "李四");map2.put("age", 30);dataList.add(map2);//使用stream流进行过滤dataList.stream().filter(map -> (Integer) map.get("age") > 25).forEach(map -> {    System.out.println("id：" + map.get("id") + "，name：" + map.get("name"));});

查询：

List> dataList = new ArrayList>();//添加数据Map map1 = new HashMap();map1.put("id", 1);map1.put("name", "张三");map1.put("age", 20);dataList.add(map1);Map map2 = new HashMap();map2.put("id", 2);map2.put("name", "李四");map2.put("age", 30);dataList.add(map2);//使用stream流进行查询Optional> optionalMap = dataList.stream().filter(map -> (Integer) map.get("id") == 1).findFirst();if (optionalMap.isPresent()) {    Map map = optionalMap.get();    System.out.println("id：" + map.get("id") + "，name：" + map.get("name") + "，age：" + map.get("age"));}

去重：

List> dataList = new ArrayList>();//添加数据Map map1 = new HashMap();map1.put("id", 1);map1.put("name", "张三");map1.put("age", 20);dataList.add(map1);Map map2 = new HashMap();map2.put("id", 2);map2.put("name", "李四");map2.put("age", 30);dataList.add(map2);Map map3 = new HashMap();map3.put("id", 2);map3.put("name", "李四");map3.put("age", 30);dataList.add(map3);//使用stream流进行去重List> distinctList = dataList.stream().distinct().collect(Collectors.toList());distinctList.stream().forEach(map -> {    System.out.println("id：" + map.get("id") + "，name：" + map.get("name") + "，age：" + map.get("age"));});

排序：

List> dataList = new ArrayList>();//添加数据Map map1 = new HashMap();map1.put("id", 1);map1.put("name", "张三");map1.put("age", 20);dataList.add(map1);Map map2 = new HashMap();map2.put("id", 2);map2.put("name", "李四");map2.put("age", 30);dataList.add(map2);Map map3 = new HashMap();map3.put("id", 3);map3.put("name", "王五");map3.put("age", 25);dataList.add(map3);//使用stream流进行排序List> sortedList = dataList.stream().sorted((map1, map2) -> (Integer) map1.get("age") - (Integer) map2.get("age")).collect(Collectors.toList());sortedList.stream().forEach(map -> {    System.out.println("id：" + map.get("id") + "，name：" + map.get("name") + "，age：" + map.get("age"));});

分组：

List> dataList = new ArrayList>();//添加数据Map map1 = new HashMap();map1.put("id", 1);map1.put("name", "张三");map1.put("age", 20);dataList.add(map1);Map map2 = new HashMap();map2.put("id", 2);map2.put("name", "李四");map2.put("age", 30);dataList.add(map2);Map map3 = new HashMap();map3.put("id", 3);map3.put("name", "王五");map3.put("age", 25);dataList.add(map3);//使用stream流进行分组Map>> groupMap = dataList.stream().collect(Collectors.groupingBy(map -> (Integer) map.get("age")));for (Map.Entry>> entry : groupMap.entrySet()) {    Integer age = entry.geTKEy();    List> list = entry.getValue();    System.out.println("年龄为" + age + "的人数为" + list.size());}

来源地址：https://blog.csdn.net/MidYear/article/details/131722819