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《Java使用Stream流的Lambda语法进行List转Map的操作方式》:本文主要介绍Java使用Stream流的Lambda语法进行List转Map的操作方式,具有很好的参考价值,希望对大...
注:标题的<>被替换成了《》,标题带有<>会因为Bug被吞。
背景
在平时开发过程中难免会碰到有些时候需要将一个List转成Map又或者是将Map转成List,我们可以采用粗暴的方式来进行转换,但这样一是不够优雅,二是数据过多的时候性能不是很高。
Lambda如果平时经常使用就可以知道这种语法糖有多方便使用,可以让代码变得十分简洁,而本篇便是用来说明使用Stream流的Lambda语法来优雅的进行List和Map的互转操作,并分析其性能差异。
一些简单的便不做分析了,比如map()、peek()、filter()等方法,主要着重分析collect()的toMap()方法。
Stream流的Lambda语法应用实例
1、定义要操作的UserDto
先定义一个UserDto以便直接后续使用,其代码如下:
public class UserDto { private String name; private String sex; private String job; @Override public String toString() { return "{\"name\":\"" + name + "\",\"sex\":\"" + sex + "\",\"job\":\"" + job + "\"}"; } // 后面其它的属性和getter、setter方法都忽略 }
2、List转成Map
List转成Map有很多方式,使用foreach的方式什么转换都可以完成,但在本篇将会分享几个遍历的操作。
List《UserDto》转成Map《String, UserDto》
首先分享一下最简单的转换:
由List<UserDto>转成以UserDto的name当成Key,而UserDto当成Value的Map操作,即Map<String, UserDto>形式。
代码如下:
public class MainTest {
public static void main(String[] args) {
UserDto userDto1 = new UserDto("test1", "man", "worker1");
UserDto userDto2 = new UserDto("test2", "woman", "worker2");
UserDto userDto3 = new UserDto("test3", "woman", "worker2");
UserDto userDto4 = new UserDto("test4", "man", "worker3");
List<UserDto> userList = Arrays
.asList(userDto1, userDto2, userDto3, userDto4);
System.out.println(userList);
// 使用stream流将List转成Map
Map<String, UserDto> userMap = userList.stream()
.collect(Collectors.toMap(UserDto::getName, dto2 -> dto2));
System.out.println(userMap);
}
}
-------------打印结果-------------
[{"name":"test1","sex":"man","job":"worker1"}, {"namhttp://www.chinasem.cne":"test2","sex":"woman","job":"worker2"},
{"name":"test3","sex":"woman","job":"worker2"}, {"name":"test4","sex":"man","job":"worker3"}]
{test4={"name":"test4","sex":"man","job":"worker3"},test2={"name":"test2","sex":"woman","job":"worker2"},
test3={"name":"test3","sex":"woman","job":"worker2"},test1={"name":"test1http://www.chinasem.cn","sex":"man","job":"worker1"}}
List《UserDto》转成Map《String, Map《String, Object》》
接下来分享下将List<UserDto>转成Map<String, Map<String, Object>>形式的Lambda操作:
public class MainTest { public static void main(String[] args) { UserDto userDto1 = new UserDto("test1", "man", "worker1"); UserDto userDto2 = new UserDto("test2", "woman", "worker2"); UserDto userDto3 = new UserDto("test3", "woman", "worker2"); UserDto userDto4 = new UserDto("test4", "man", "worker3"); List<UserDto> userList = Arrays .asList(userDto1, userDto2, userDto3, userDto4); System.out.println(userList); // 使用stream流将List转成Map Map<String, Map<String, Object>> userMap = userList.stream() .collect(Collectors.toMap(UserDto::getName, dto2 -> new HashMap<String, Object>(){{ put("name", dto2.getName()); put("sex", dto2.getSex()); put("job", dto2.getJob());}})); System.out.println(userMap); } } -------------打印结果------------- [{"name":"test1","sex":"man","job":"worker1"}, {"name":"test2","sex":"woman","job":"worker2"}, {"name":"test3","sex":"woman","job":"worker2"}, {"name":"test4","sex":"man","job":"worker3"}] {test4={sex=man, name=test4, job=worker3}, test2={sex=woman, name=test2, job=worker2}, test3={sex=woman, name=test3, job=worker2}, test1={sex=man, name=test1, job=worker1}}
List《UserDto》转Map《String, String》
接下来分享下将List<UserDto>转成Map<String, String>形式的Lambda操作,当然Map中String泛型也可以是Integer、Long甚至其它的类型,按照下面的方式进行相应的替换就行了:
public class MainTest { public static void main(String[] args) { UserDto userDto1 = new UserDto("test1", "man", "worker1"); UserDto userDto2 = new UserDto("test2", "woman", "worker2"); UserDto userDto3 = new UserDto("test3", "woman", "worker2"); UserDto userDto4 = new UserDto("test4", "man", "worker3"); List<UserDto> userList = Arrays .asList(userDto1, userDto2, userDto3, userDto4); System.out.println(userList); // 使用stream流将List转成Map Map<String, String> userMap = userList.stream() .collect(Collectors.toMap(UserDto::getName, UserDto::getSex)); System.out.println(userMap); } } -------------打印结果------------- [{"name":"test1","sex":"man","job":"worker1"}, {"name":"test2","sex":"woman","job":"worker2"}, {"name":"test3","sex":"woman","job":"worker2"}, {"name":"test4","sex":"man","job":"worker3"}] {test4=man, test2=woman, test3=woman, test1=man}
List《Map《String, Object》》转Map《String, UserDto》
由List<Map<String, Object>>转Map<String, UserDto>操作中,Map中的String也可以是Long、Integer或者其它的类型:
public class MainTest { public static void main(String[] args) { Map<String, Object> userMap1 = new HashMap<String, Object>(8) {{ put("name", "test1");put("sex", "man");put("job", "worker1"); }}; Map<String, Object> userMap2 = new HashMap<String, Object>(8) {{ put("name", "test2");put("sex", "woman");put("job", "worker2"); }}; Map<String, Object> userMap3 = new HashMap<String, Object>(8) {{ put("name", "test3");put("sex", "woman");put("job", "worker2"); }}; Map<String, Object> userMap4 = new HashMap<String, Object>(8) {{ put("name", "test4");put("sex", "man");put("job", "worker3"); }}; List<Map<String, Object>> userList = Arrays.asList(userMap1, userMap2, userMap3, userMap4); System.out.println(userList); // 使用stream流将List转成Map Map<String, UserDto> userMap = userList.stream() .collect(Collectors.toMap(map1 -> (String) map1.get("name"), map2 -> new UserDto((String) map2.get("name"), (String) map2.get("sex"), (String) map2.get("job")))); System.out.println(userMap); } } -------------打印结果------------- [{name=test1, job=worker1, sex=man}, {name=test2, job=worker2, sex=woman}, {name=test3, job=worker2, sex=woman}, {name=test4, job=worker3, sex=man}] {test4={"name":"test4","sex":"man","job":"worker3"}, test2={"name":"test2","sex":"woman","job":"worker2"}, test3={"name":"test3","sex":"woman","job":"worker2"}, test1={"name":"test1","sex":"man","job":"worker1"}}
List《Map《String, Object》》转Map《String, String》
由List<Map<String, Object>>转Map<String, String>操作中,Map中的String也可以是Long、Integer或者其它的类型:
public class MainTest {
public static void main(String[] args) {
Map<String, Object> userMap1 = new HashMap<String, Object>(8) {{
put("name", "test1");put("sex", "man");put("job", "worker1");
}};
Map<String, Object> userMap2 = new HashMap<String, Object>(8) {{
put("name", "test2");put("sex", "woman");put("job", "worker2");
}};
Map<String, Object> userMap3 = new HashMap<String, Object>(8) {{
put("name", "test3");put("sex", "woman");put("job", "worker2");
}};
Map<String, Object> userMap4 = new HashMap<String, Object>(8) {{
put("name", "test4");put("sex", "man");put("jobpython", "worker3");
}};
List<Map<String, Object>> userList = Arrays.asList(userMap1, userMap2, userMap3, userMap4);
System.out.println(userList);
// 使用stream流将List转成Map
Map<String, String> userMap = userList.stream()
.collect(Collectors.toMap(map1 -> (String) map1.get("name"),
map2 -> (String) map2.get("sex")));
System.out.println(userMap);
}
}
-------------打印结果-------------
[{name=test1, job=worker1, sex=man}, {name=test2, job=worker2, sex=woman}, {name=test3, job=worker2, sex=woman}, {name=test4, job=worker3, sex=man}]
{test4=man, test2=woman, test3=woman, test1=man}
List《Map《String, Object》》转Map《String, Map《String, Object》》
由List<Map<String, Object>>转Map<String, Map<String, Object>>操作中,Map中的String也可以是Long、Integer或者其它的类型:
public class MainTest { public static void main(String[] args) { Map<String, Object> userMap1 = new HashMap<String, Object>(8) {{ put("name", "test1");put("sex", "man");put("job", "worker1"); }}; Map<String, Object> userMap2 = new HashMap<String, Object>(8) {{ put("name", "test2");put("sex", "woman");put("job", "worker2"); }}; Map<String, Object> userMap3 = new HashMap<String, Object>(8) {{ put("name", "test3");put("sex", "woman");put("job", "worker2"); }}; Map<String, Object> userMap4 = new HashMap<String, Object>(8) {{ put("name", "test4");put("sex", "man");put("job", "worker3"); }}; List<Map<String, Object>> userList = Arrays.asList(userMap1, userMap2, userMap3, userMap4); System.out.println(userList); // 使用stream流将List转成Map Map<String, Map<String, Object>> userMap = userList.stream() .collect(Collectors.toMap(map1 -> (String) map1.get("name"), map2 -> map2)); System.out.println(userMap); } } -------------打印结果------------- [{name=test1, job=worker1, sex=man}, {name=test2, job=worker2, sex=woman}, {name=test3, job=worker2, sex=woman}, {name=test4, job=worker3, sex=man}] {test4={name=test4, job=worker3, sex=man}, test2={name=test2, job=worker2, sex=woman}, test3={name=test3, job=worker2, sex=woman}, test1={name=test1, job=worker1, sex=man}}
List《Map》转Map《String, List《Map》》
由List转Map>,根据Map中的某个值进行分组:
public class MainTest { public static void main(String[] args) { Map<String, Object> userMap1 = new HashMap<String, Object>(8) {{ put("name", "test1");put("sex", "man");put("job", "worker1"); }}; Map<String, Object> userMap2 = new HashMap<String, Object>(8) {{ put("name", "test2");put("sex", "woman");put("job", "worker2"); }}; Map<String, Object> userMap3 = new HashMap<String, Object>(8) {{ put("name", "test3");put("sex", "woman");put("job", "worker2"); }}; Map<String, Object> userMap4 = new HashMap<String, Object>(8) {{ put("name", "test4");put("sex", "man");put("job", "worker3"); }}; List<Map<String, Object>> userList = Arrays.asList(userMap1, userMap2, userMap3, userMap4); System.out.println(userList); // 使用stream流将List转成Map Map<String, List<Map<String, Object>>> userMap = userList.stream() .collect(Collectors.groupingBy(map1 -> (String) map1.China编程get("sex"))); System.out.println(userMap); } } -------------打印结果------------- [{name=test1, job=worker1, sex=man}, {name=test2, job=worker2, sex=woman}, {name=test3, job=worker2, sex=woman}, {name=test4, job=worker3, sex=man}] {woman=[{name=test2, job=worker2, sex=woman}, {name=test3, job=worker2, sex=woman}], man=[{name=test1, job=worker1, sex=man}, {name=test4, job=worker3, sex=man}]}
性能说明
需要注意的是Stream使用流处理也是有使用限制的,比如初始化时间和性能限制:
- 初始化时间:系统第一次使用Stream流的时候初始化时间如果是1W数据以内的需要几十毫秒,如果是10W数据以内的初始化需要100毫秒左右,100W初始化需要1000毫秒左右,1000W初始化则需要2500毫秒左右,而foreach的初始化时间和后续的时间是差不多的;
- 运行性能:数据量在1W级别以下的时间花费差不多,10W数据以内的Stream流比性能是foreach的1/2,100W数据以内的Stream流性能是foreach的3/5,而到了1000W数据量级下Stream又变成了foreach的一倍左右,foreach到了1000W数据量级下最开始运行时间还保持在1400毫秒左右,到了后面则跑到了6000毫秒甚至7000毫秒,不知道是不是因为GC导致的。
因此使用Stream时适用于低数据量的情况,当数据量级在1W以下是Stream流和foreach都可以使用,性能差别不大;到了10W-100W时应该使用foreach性能更快;而到了1000W量级的情况下就该使用Stream或者其它的大数据解析框架了。
使用上述方式的20次平均运行时间表(仅代表本机I5-8400 2.8Ghz-2.81Ghz的规格CPU运行效率):
运行方式 | 数据量级 | 初始化时间(ms) | 初始化后的 平均运行效率(ms) |
foreach | 1W | 38 | 1 |
stream流 | 1W | 1 | 1 |
foreach | 10W | 28 | 6 |
stream流 | 10W | 54 | 12 |
foreach | 100W | 139 | 111 |
stream流 | 100W | 1300 | 181 |
foreach | 1000W | 2500 | 3500 |
stream流 | 1000W | 1130 | 6000 |
总结
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