FastJson简介
FastJson三个核心类
Maven
Java API
反序列化一个简单Json字符串
反序列化一个简单JSON字符串成Java对象组
反序列化一个复杂的JSON字符串
反序列化
序列化
序列化和反序列化日期
JsonObject的一些操作
jsonArray的一些操作
Scala API
demo日志内容
反序列化简单json字符串
反序列化简单json字符串组
String处理
List处理
反序列化
JSON协议在日常开发中很常用，包括前后端的数据接口，日志字段的保存等，通常都采用JSON协议。FastJson是阿里的开源框架，很好用，估计开发的同学都有使用过。这里做一个简单的用法总结，配一些demo。除了Java版本外，由于在Spark也经常清洗日志，所以配上了Scala版本，方便日后查询使用。完整代码可以参考Github:https://github.com/tygxy/BigData
JSON：fastjson的解析器，用于json字符串和javaBean、Json对象的转换
JSONObject：fastJson提供的json对象
JSONArray：fastJson提供json数组对象
<dependency> <groupId>com.alibaba</groupId> <artifactId>fastjson</artifactId> <version>1.2.47</version> </dependency>
反序列化一个简单Json字符串
public class User {
private String name; private int age; public String getName() { return name;
} public void setName(String name) { this.name = name;
} public int getAge() { return age;
} public void setAge(int age) { this.age = age;
}
}String jsonString = "{\"name\":\"张三\",\"age\":50}";
User user= JSON.parseObject(jsonString,User.class);
System.out.println("name:"+user.getName()+" age:"+user.getAge());// 输出结果 name:张三 age:50反序列化操作
创建JavaBean的User类
反序列化一个简单JSON字符串成Java对象组
String jsonArrayString = "[{\"name\":\"张三\",\"age\":50},{\"name\":\"李四\",\"age\":51}]";
List<User> userList = JSON.parseArray(jsonArrayString,User.class);
Iterator it = userList.iterator();while (it.hasNext()) {
User u = (User)it.next();
System.out.println("name:"+u.getName()+" age:"+u.getAge());
}// 输出结果 name:张三 age:50
name:李四 age:51反序列化一个复杂的JSON字符串
public class Course { private String courseName; private String code; public Course (String courseName, String code){ this.setCourseName(courseName); this.setCode(code);
} public String getCourseName() { return courseName;
} public void setCourseName(String courseName) { this.courseName = courseName;
} public String getCode() { return code;
} public void setCode(String code) { this.code = code;
}
}public class Student { private int id; private String studentName; private int age; public Student(int id, String studentName, int age) { this.setId(id); this.setStudentName(studentName); this.setAge(age);
} public int getId() { return id;
} public void setId(int id) { this.id = id;
} public String getStudentName() { return studentName;
} public void setStudentName(String studentName) { this.studentName = studentName;
} public int getAge() { return age;
} public void setAge(int age) { this.age = age;
}
}public class Teacher { private String teacherName; private int age; private Course course; private List<Student> students; public Teacher(String teacherName, int age, Course course, List<Student> students) { this.setTeacherName(teacherName); this.setAge(age); this.setCourse(course); this.setStudents(students);
} public String getTeacherName() { return teacherName;
} public void setTeacherName(String teacherName) { this.teacherName = teacherName;
} public int getAge() { return age;
} public void setAge(int age) { this.age = age;
} public Course getCourse() { return course;
} public void setCourse(Course course) { this.course = course;
} public List<Student> getStudents() { return students;
} public void setStudents(List<Student> students) { this.students = students;
}
}String complexJsonString = "{\"teacherName\":\"crystall\",\"age\":27,\"course\":{\"courseName\":\"english\",\"code\":1270},\"students\":[{\"id\":1,\"studentName\":\"lily\",\"age\":12},{\"id\":2,\"studentName\":\"lucy\",\"age\":15}]}";
Teacher teacher = JSON.parseObject(complexJsonString,Teacher.class);反序列化操作
分别创建JavaBean的Course类、Student类、Teacher类
序列化一个Java Bean对象
User u = new User();
u.setName("王五");
u.setAge(30);
System.out.println(JSON.toJSONString(u));// 输出结果 {"age":30,"name":"王五"}
User u1 = new User();
u1.setAge(30);
System.out.println(JSON.toJSONString(u1,SerializerFeature.WriteMapNullValue)); // 输出null，输出结果 {"age":30,"name":null}
System.out.println(JSON.toJSONString(u1,SerializerFeature.WriteNullStringAsEmpty)); // 输出""，输出结果 {"age":30,"name":""}Date date = new Date();String dateString = JSON.toJSONStringWithDateFormat(date, "yyyy-MM-dd HH:mm:ss");
System.out.println(dateString);// 输出结果 "2018-08-03 09:44:21"String dateString1 = "{\"time\":\"2018-08-01 22:22:22\"}";
System.out.println(JSON.parseObject(dateString1));// 输出结果 {"time":"2018-08-01 22:22:22"}String jsonString1 = "{\"name\":\"张三\",\"age\":50}";
JSONObject jsonObject = JSON.parseObject(jsonString1);
System.out.println(jsonObject.keySet()); // 输出key集合，输出结果 [name, age]if(jsonObject.containsKey("sex")) { // 判断key是否存在，输出结果 false
System.out.println(true);
} else {
System.out.println(false);
}
jsonObject.put("sex","man"); // 添加k/v键值对，输出结果 {"sex":"man","name":"张三","age":50}
System.out.println(jsonObject);if (jsonObject.containsValue("man")) { // 判断value是否存在，输出结果 false
System.out.println(true);
} else {
System.out.println(false);
}String jsonArrayString1 = "[{\"id\":1,\"studentName\":\"lily\",\"age\":12},{\"id\":2,\"studentName\":\"lucy\",\"age\":15}]";
JSONArray jsonArray = JSON.parseArray(jsonArrayString1);for (int i = 0; i < jsonArray.size(); i++) { // 遍历输出
JSONObject jsonObj= jsonArray.getJSONObject(i);
System.out.println(jsonObj.get("id"));
}
Student s3 = new Student(3,"学生乙",15);
jsonArray.add(s3); // 添加新jsonobject对象，输出结果 3System.out.println(jsonArray.size());if(jsonArray.contains(s3)) { // 判断是否存在，输出结果 true
System.out.println(true);
} else {
System.out.println(false);
}demo日志内容
{"name":"张三","age":10}
{"name":"李四","age":11}
{"name":"李四"}
{"age":11}{"data":[{"label":"123","acc":1,"version":"4.3.1"}]}
{"data":[{"label":"789","acc":1,"version":"4.3.1"},{"label":"78","acc":100,"version":"4.3.1"}]}
{"data":[{"label":"5356","acc":1,"version":"4.3.1"}]}data1.log
data.log
反序列化简单json字符串
val spark = SparkSession.builder().master("local[2]").appName("FastJsonTest").getOrCreate()
val input1 = "data.log"val jsonRDD1 = spark.sparkContext.textFile(input1)
val dataRDD1 = jsonRDD1.map(json => {
val jsonObject = JSON.parseObject(json)
val name = jsonObject.getOrDefault("name",null)
val age = jsonObject.getOrDefault("age",null)
(name,age)
})
dataRDD1.foreach(println)// 输出结果 (李四,null)
(null,11)
(张三,10)
(李四,11)反序列化简单json字符串组，实现一行变多行地解析json字符串。这个我也没找到很好的方法，欢迎读者指教一下
val input2 = "data1.log"val jsonRDD2 = spark.sparkContext.textFile(input2)
val dataRDD2 = jsonRDD2.map(json => { JSON.parseObject(json).getJSONArray("data").toString
}).map(x => x.substring(1,x.length-1).replace("},{","}---{")) // 去掉字符串中的[]，并替换},{成}---{，目的是用于区分
.flatMap(x => x.split("---")) // 字符串按----拆分
.map(x => JSON.parseObject(x))
val data2 = dataRDD2.map(jsonObject => {
val version = jsonObject.getOrDefault("version",null)
val label = jsonObject.getOrDefault("label",null)
val acc = jsonObject.getOrDefault("acc",null)
(version,label,acc)
})
data2.foreach(println)// 输出结果(4.3.1,5356,1)
(4.3.1,123,1)
(4.3.1,789,1)
(4.3.1,78,100)val dataRDD3 = jsonRDD2.flatMap(json => {
val jsonArray = JSON.parseObject(json).getJSONArray("data") var dataList : List[String] = List() // 创建一个List
for (i <- 0 to jsonArray.size()-1) {
dataList = jsonArray.get(i).toString :: dataList
}
dataList
}).map(x => JSON.parseObject(x))
val data3 = dataRDD3.map(jsonObject => {
val version = jsonObject.getOrDefault("version",null)
val label = jsonObject.getOrDefault("label",null)
val acc = jsonObject.getOrDefault("acc",null)
(version,label,acc)
})
data3.foreach(println)// 输出结果(4.3.1,5356,1)
(4.3.1,123,1)
(4.3.1,789,1)
(4.3.1,78,100)方法二：List
方法一：字符串处理
序列化一个简单java Bean对象
val arr = Seq("tom:10", "bob:14", "hurry:9")
val dataRdd = spark.sparkContext.parallelize(arr)
val dataString = dataRdd.map(x => {
val arr = x.split(":")
val name = arr(0)
val age = arr(1).toInt
val u = new User(name,age)
u
}).map(x => { JSON.toJSONString(x,SerializerFeature.WriteMapNullValue) // 这里需要显示SerializerFeature中的某一个，否则会报同时匹配两个方法的错误})
dataString.foreach(println)// 输出结果{"age":10,"name":"tom"}
{"age":14,"name":"bob"}
{"age":9,"name":"hurry"}https://segmentfault.com/a/1190000011212806
https://www.cnblogs.com/cdf-opensource-007/p/7106018.html
https://github.com/alibaba/fastjson
https://blog.csdn.net/universsky2015/article/details/77965563?locationNum=9&fps=1
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