Jackson学习笔记(一)

概述

Jackson框架是基于Java平台的一套数据处理工具，被称为“最好的Java Json解析器”。

Jackson框架包含了3个核心库：streaming,databind,annotations.Jackson还包含了其它数据处理类库，此外不作说明。

Jackson版本： 1.x (目前版本从1.1~1.9)与2.x。1.x与2.x从包的命名上可以看出来，1.x的类库中，包命名以：org.codehaus.jackson.xxx开头，而2.x类库中包命令：com.fastxml.jackson.xxx开头

Jackson Home Page：https://github.com/FasterXML/jackson

Jackson Wiki：http://wiki.fasterxml.com/JacksonHome

Jackson doc: https://github.com/FasterXML/jackson-docs

Jackson Download Page：http://wiki.fasterxml.com/JacksonDownload

准备工作

本文所有程序都基于JDK1.7,依赖jackon的三个核心类库：

jackson-core-2.5.3.jar

jackson-annotations-2.5.3.jar

jackson-databind-2.5.3.jar

Jackson处理Json

Jackson提供了三种可选的Json处理方法：流式API(Streaming API) 、树模型(Tree Model)、数据绑定(Data Binding)。从使用角度来看，比较一下这三种处理Json的方式的特性：
Streaming API：是效率最高的处理方式(开销低、读写速度快，但程序编写复杂度高)

Tree Model：是最灵活的处理方式

Data Binding：是最常用的处理方式

下面我们通过例子程序分别使用DataBinding,TreeModel,Streaming的方式来创建和解析Json字符串

1.DataBinding处理Json

Jackson支持Java对象与Json之间的相互转化。java对象序列化为json字符串，json字符串也可以反序列化为相同的java对象。

(1)java对象转化成json:

Province.java

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package com.jackson.json.databinding;

public class Province {

public String name;

public int population;

public String[] city;

}

Country.java

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package com.jackson.json.databinding;

import java.util.ArrayList;

import java.util.Arrays;

import java.util.Date;

import java.util.HashMap;

import java.util.List;

import java.util.Map;

public class Country {

// 注意：被序列化的bean的private属性字段需要创建getter方法或者属性字段应该为public

private String country_id;

private Date birthDate;

private List<String> nation = new ArrayList<String>();

private String[] lakes;

private List<Province> provinces = new ArrayList<Province>();

private Map<String, Integer> traffic = new HashMap<String, Integer>();

public Country() {

// TODO Auto-generated constructor stub

}

public Country(String countryId) {

this.country_id = countryId;

}

public String getCountry_id() {

return country_id;

}

public void setCountry_id(String country_id) {

this.country_id = country_id;

}

public Date getBirthDate() {

return birthDate;

}

public void setBirthDate(Date birthDate) {

this.birthDate = birthDate;

}

public List<String> getNation() {

return nation;

}

public void setNation(List<String> nation) {

this.nation = nation;

}

public String[] getLakes() {

return lakes;

}

public void setLakes(String[] lakes) {

this.lakes = lakes;

}

public Integer get(String key) {

return traffic.get(key);

}

public Map<String, Integer> getTraffic() {

return traffic;

}

public void setTraffic(Map<String, Integer> traffic) {

this.traffic = traffic;

}

public void addTraffic(String key, Integer value) {

traffic.put(key, value);

}

public List<Province> getProvinces() {

return provinces;

}

public void setProvinces(List<Province> provinces) {

this.provinces = provinces;

}

@Override

public String toString() {

return "Country [country_id=" + country_id + ", birthDate=" + birthDate

+ ", nation=" + nation + ", lakes=" + Arrays.toString(lakes)

+ ", province=" + provinces + ", traffic=" + traffic + "]";

}

}

JavaBeanSerializeToJson.java

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package com.jackson.json.databinding;

import java.io.File;

import java.text.SimpleDateFormat;

import java.util.ArrayList;

import java.util.List;

import com.fasterxml.jackson.annotation.JsonInclude.Include;

import com.fasterxml.jackson.databind.ObjectMapper;

import com.fasterxml.jackson.databind.SerializationFeature;

public class JavaBeanSerializeToJson {

public static void convert() throws Exception {

// 使用ObjectMapper来转化对象为Json

ObjectMapper mapper = new ObjectMapper();

// 添加功能，让时间格式更具有可读性

SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd");

mapper.setDateFormat(dateFormat);

Country country = new Country("China");

country.setBirthDate(dateFormat.parse("1949-10-01"));

country.setLakes(new String[] { "Qinghai Lake", "Poyang Lake",

"Dongting Lake", "Taihu Lake" });

List<String> nation = new ArrayList<String>();

nation.add("Han");

nation.add("Meng");

nation.add("Hui");

nation.add("WeiWuEr");

nation.add("Zang");

country.setNation(nation);

Province province = new Province();

province.name = "Shanxi";

province.population = 37751200;

Province province2 = new Province();

province2.name = "ZheJiang";

province2.population = 55080000;

List<Province> provinces = new ArrayList<Province>();

provinces.add(province);

provinces.add(province2);

country.setProvinces(provinces);

country.addTraffic("Train(KM)", 112000);

country.addTraffic("HighWay(KM)", 4240000);

// 为了使JSON视觉上的可读性，增加一行如下代码，注意，在生产中不需要这样，因为这样会增大Json的内容

mapper.configure(SerializationFeature.INDENT_OUTPUT, true);

// 配置mapper忽略空属性

mapper.setSerializationInclusion(Include.NON_EMPTY);

// 默认情况，Jackson使用Java属性字段名称作为 Json的属性名称,也可以使用Jackson annotations(注解)改变Json属性名称

mapper.writeValue(new File("country.json"), country);

}

public static void main(String[] args) throws Exception {

convert();

}

}

程序运行后生成country.json，内容如下：

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{

"country_id" : "China",

"birthDate" : "1949-10-01",

"nation" : [ "Han", "Meng", "Hui", "WeiWuEr", "Zang" ],

"lakes" : [ "Qinghai Lake", "Poyang Lake", "Dongting Lake", "Taihu Lake" ],

"provinces" : [ {

"name" : "Shanxi",

"population" : 37751200

}, {

"name" : "ZheJiang",

"population" : 55080000

} ],

"traffic" : {

"HighWay(KM)" : 4240000,

"Train(KM)" : 112000

}

}

(2)Json字符串反序列化为java对象：

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package com.jackson.json.databinding;

import java.io.File;

import java.io.IOException;

import java.text.SimpleDateFormat;

import java.util.Iterator;

import java.util.List;

import com.fasterxml.jackson.core.JsonParseException;

import com.fasterxml.jackson.databind.DeserializationFeature;

import com.fasterxml.jackson.databind.JsonMappingException;

import com.fasterxml.jackson.databind.ObjectMapper;

/**

* 将Json字符串反序列化为Java对象

*/

public class JsonDeserializeToJava {

public static void main(String[] args) throws Exception {

//ObjectMapper类用序列化与反序列化映射器

ObjectMapper mapper = new ObjectMapper();

File json = new File("country.json");

//当反序列化json时，未知属性会引起的反序列化被打断，这里我们禁用未知属性打断反序列化功能，

//因为，例如json里有10个属性，而我们的bean中只定义了2个属性，其它8个属性将被忽略

mapper.disable(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES);

//从json映射到java对象，得到country对象后就可以遍历查找,下面遍历部分内容，能说明问题就可以了

Country country = mapper.readValue(json, Country.class);

System.out.println("country_id:"+country.getCountry_id());

//设置时间格式，便于阅读

SimpleDateFormat dateformat = new SimpleDateFormat("yyyy-MM-dd");

String birthDate = dateformat.format(country.getBirthDate());

System.out.println("birthDate:"+birthDate);

List<Province> provinces = country.getProvinces();

for (Province province : provinces) {

System.out.println("province:"+province.name + "\n" + "population:"+province.population);

}

}

}

程序运行结果：

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country_id:China

birthDate:1949-10-01

province:Shanxi

population:37751200

province:ZheJiang

population:55080000

2.Tree Model处理Json

(1)tree model生成json:

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package com.jackson.json.treemodel;

import java.io.File;

import java.io.FileWriter;

import com.fasterxml.jackson.core.JsonFactory;

import com.fasterxml.jackson.core.JsonGenerator;

import com.fasterxml.jackson.databind.ObjectMapper;

import com.fasterxml.jackson.databind.SerializationFeature;

import com.fasterxml.jackson.databind.node.ArrayNode;

import com.fasterxml.jackson.databind.node.JsonNodeFactory;

import com.fasterxml.jackson.databind.node.ObjectNode;

public class SerializationExampleTreeModel {

public static void main(String[] args) throws Exception {

//创建一个节点工厂,为我们提供所有节点

JsonNodeFactory factory = new JsonNodeFactory(false);

//创建一个json factory来写tree modle为json

JsonFactory jsonFactory = new JsonFactory();

//创建一个json生成器

JsonGenerator generator = jsonFactory.createGenerator(new FileWriter(new File("country2.json")));

//注意，默认情况下对象映射器不会指定根节点，下面设根节点为country

ObjectMapper mapper = new ObjectMapper();

ObjectNode country = factory.objectNode();

country.put("country_id", "China");

country.put("birthDate", "1949-10-01");

//在Java中，List和Array转化为json后对应的格式符号都是"obj:[]"

ArrayNode nation = factory.arrayNode();

nation.add("Han").add("Meng").add("Hui").add("WeiWuEr").add("Zang");

country.set("nation", nation);

ArrayNode lakes = factory.arrayNode();

lakes.add("QingHai Lake").add("Poyang Lake").add("Dongting Lake").add("Taihu Lake");

country.set("lakes", lakes);

ArrayNode provinces = factory.arrayNode();

ObjectNode province = factory.objectNode();

ObjectNode province2 = factory.objectNode();

province.put("name","Shanxi");

province.put("population", 37751200);

province2.put("name","ZheJiang");

province2.put("population", 55080000);

provinces.add(province).add(province2);

country.set("provinces", provinces);

ObjectNode traffic = factory.objectNode();

traffic.put("HighWay(KM)", 4240000);

traffic.put("Train(KM)", 112000);

country.set("traffic", traffic);

mapper.configure(SerializationFeature.INDENT_OUTPUT, true);

mapper.writeTree(generator, country);

}

}

程序运行生成country2.json,内容如下：

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{"country_id":"China","birthDate":"1949-10-01","nation":["Han","Meng","Hui","WeiWuEr","Zang"],"lakes":["QingHai Lake","Poyang Lake","Dongting Lake","Taihu Lake"],"provinces":[{"name":"Shanxi","population":37751200},{"name":"ZheJiang","population":55080000}],"traffic":{"HighWay(KM)":4240000,"Train(KM)":112000}}

(2) json字符串反序列化为tree mode

DeserializationExampleTreeModel1.java,请注意观察程序中不同的JsonNode的类型变化

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package com.jackson.json.treemodel;

import java.io.File;

import java.util.Iterator;

import com.fasterxml.jackson.databind.JsonNode;

import com.fasterxml.jackson.databind.ObjectMapper;

public class DeserializationExampleTreeModel1 {

public static void main(String[] args) throws Exception {

ObjectMapper mapper = new ObjectMapper();

// Jackson提供一个树节点被称为"JsonNode",ObjectMapper提供方法来读json作为树的JsonNode根节点

JsonNode node = mapper.readTree(new File("country2.json"));

// 看看根节点的类型

System.out.println("node JsonNodeType:"+node.getNodeType());

// 是不是一个容器

System.out.println("node is container Node ? "+node.isContainerNode());

// 得到所有node节点的子节点名称

System.out.println("---------得到所有node节点的子节点名称-------------------------");

Iterator<String> fieldNames = node.fieldNames();

while (fieldNames.hasNext()) {

String fieldName = fieldNames.next();

System.out.print(fieldName+" ");

}

System.out.println("\n-----------------------------------------------------");

// as.Text的作用是有值返回值，无值返回空字符串

JsonNode country_id = node.get("country_id");

System.out.println("country_id:"+country_id.asText() + " JsonNodeType:"+country_id.getNodeType());

JsonNode birthDate = node.get("birthDate");

System.out.println("birthDate:"+birthDate.asText()+" JsonNodeType:"+birthDate.getNodeType());

JsonNode nation = node.get("nation");

System.out.println("nation:"+ nation+ " JsonNodeType:"+nation.getNodeType());

JsonNode lakes = node.get("lakes");

System.out.println("lakes:"+lakes+" JsonNodeType:"+lakes.getNodeType());

JsonNode provinces = node.get("provinces");

System.out.println("provinces JsonNodeType:"+provinces.getNodeType());

boolean flag = true;

for (JsonNode provinceElements : provinces) {

//为了避免provinceElements多次打印，用flag控制打印，能体现provinceElements的JsonNodeType就可以了

if(flag){

System.out.println("provinceElements JsonNodeType:"+provinceElements.getNodeType());

System.out.println("provinceElements is container node? "+provinceElements.isContainerNode());

flag = false;

}

Iterator<String> provinceElementFields = provinceElements.fieldNames();

while (provinceElementFields.hasNext()) {

String fieldName = (String) provinceElementFields.next();

String province;

if ("population".equals(fieldName)) {

province = fieldName + ":" + provinceElements.get(fieldName).asInt();

}else{

province = fieldName + ":" + provinceElements.get(fieldName).asText();

}

System.out.println(province);

}

}

}

}

程序运行后打印结果如下：

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node JsonNodeType:OBJECT

node is container Node ? true

---------得到所有node节点的子节点名称-------------------------

country_id birthDate nation lakes provinces traffic

-----------------------------------------------------

country_id:China JsonNodeType:STRING

birthDate:1949-10-01 JsonNodeType:STRING

nation:["Han","Meng","Hui","WeiWuEr","Zang"] JsonNodeType:ARRAY

lakes:["QingHai Lake","Poyang Lake","Dongting Lake","Taihu Lake"] JsonNodeType:ARRAY

provinces JsonNodeType:ARRAY

provinceElements JsonNodeType:OBJECT

provinceElements is container node? true

name:Shanxi

population:37751200

name:ZheJiang

population:55080000

在来看一下DeserializationExampleTreeModel2.java,本例中使用JsonNode.path的方法，path方法类似于DeserializationExampleTreeModel1.java中使用的get方法，

但当node不存在时,get方法返回null,而path返回MISSING类型的JsonNode

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package com.jackson.json.treemodel;

import java.io.File;

import java.io.IOException;

import java.util.Iterator;

import com.fasterxml.jackson.core.JsonProcessingException;

import com.fasterxml.jackson.databind.JsonNode;

import com.fasterxml.jackson.databind.ObjectMapper;

public class DeserializationExampleTreeModle2 {

public static void main(String[] args) throws JsonProcessingException, IOException{

ObjectMapper mapper = new ObjectMapper();

JsonNode node = mapper.readTree(new File("country2.json"));

//path方法获取JsonNode时，当对象不存在时，返回MISSING类型的JsonNode

JsonNode missingNode = node.path("test");

if(missingNode.isMissingNode()){

System.out.println("JsonNodeType : " + missingNode.getNodeType());

}

System.out.println("country_id:"+node.path("country_id").asText());

JsonNode provinces = node.path("provinces");

for (JsonNode provinceElements : provinces) {

Iterator<String> provincesFields = provinceElements.fieldNames();

while (provincesFields.hasNext()) {

String fieldName = (String) provincesFields.next();

String province;

if("name".equals(fieldName)){

province = fieldName +":"+ provinceElements.path(fieldName).asText();

}else{

province = fieldName +":"+ provinceElements.path(fieldName).asInt();

}

System.out.println(province);

}

}

}

}

程序运行打印结果：

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JsonNodeType : MISSING

country_id:China

name:Shanxi

population:37751200

name:ZheJiang

population:55080000

3.Stream处理Json

(1)stream生成json

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package com.jackson.json.streaming;

import java.io.File;

import java.io.FileWriter;

import java.io.Exception;

import com.fasterxml.jackson.core.JsonFactory;

import com.fasterxml.jackson.core.JsonGenerator;

public class StreamGeneratorJson {

public static void main(String[] args) throws Exception {

JsonFactory factory = new JsonFactory();

//从JsonFactory创建一个JsonGenerator生成器的实例

JsonGenerator generator = factory.createGenerator(new FileWriter(new File("country3.json")));

generator.writeStartObject();

generator.writeFieldName("country_id");

generator.writeString("China");

generator.writeFieldName("provinces");

generator.writeStartArray();

generator.writeStartObject();

generator.writeStringField("name", "Shanxi");

generator.writeNumberField("population", 33750000);

generator.writeEndObject();

generator.writeEndArray();

generator.writeEndObject();

generator.close();

}

}

程序运行后生成country3.json文件内容：

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{"country_id":"China","provinces":[{"name":"Shanxi","population":33750000}]}

(2)stream解析json:

现在adgcountry3.json，我们用Streaming API的方式来解析上面的Json,并查找json中population的值。

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package com.jackson.json.streaming;

import java.io.File;

import java.io.IOException;

import com.fasterxml.jackson.core.JsonFactory;

import com.fasterxml.jackson.core.JsonParseException;

import com.fasterxml.jackson.core.JsonParser;

import com.fasterxml.jackson.core.JsonToken;

/*Jackson API提供了token对每个Json对象，例如，Json开始符号“{”是token指向的第一个解析的对象，

key:value键值对是另一个单独的对象。这个API很强大，但也需要编写大量代码。不推荐使用，平时更多的是使用DataBinding和TreeModel来处理json

*/

public class StreamParserJson {

public static void main(String[] args) throws JsonParseException,

IOException {

JsonFactory factory = new JsonFactory();

// 从JsonFactory创建JsonParser解析器的实例

JsonParser parser = factory.createParser(new File("country3.json"));

while (!parser.isClosed()) {

// 得到一个token,第一次遍历时，token指向json文件中第一个符号"{"

JsonToken token = parser.nextToken();

if (token == null) {

break;

}

// 我们只查找 country3.json中的"population"字段的值，能体现解析的流程就可以了

// 当key是provinces时，我们进入provinces,查找population

if (JsonToken.FIELD_NAME.equals(token)

&& "provinces".equals(parser.getCurrentName())) {

token = parser.nextToken();

if (!JsonToken.START_ARRAY.equals(token)) {

break;

}

// 此时，token指向的应该是"{"

token = parser.nextToken();

if (!JsonToken.START_OBJECT.equals(token)) {

break;

}

while (true) {

token = parser.nextToken();

if (token == null) {

break;

}

if (JsonToken.FIELD_NAME.equals(token)

&& "population".equals(parser.getCurrentName())) {

token = parser.nextToken();

System.out.println(parser.getCurrentName() + " : "

+ parser.getIntValue());

}

}

}

}

}

}

程序运行后，在控制台打印结果如下：

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population : 33750000

总结

上面的例子中，分别用3种方式处理Json，我的体会大致如下：

Stream API方式是开销最低、效率最高，但编写代码复杂度也最高，在生成Json时，需要逐步编写符号和字段拼接json,在解析Json时，需要根据token指向也查找json值，生成和解析json都不是很方便，代码可读性也很低。

Databinding处理Json是最常用的json处理方式，生成json时，创建相关的java对象，并根据json内容结构把java对象组装起来，最后调用writeValue方法即可生成json,

解析时，就更简单了，直接把json映射到相关的java对象，然后就可以遍历java对象来获取值了。

TreeModel处理Json，是以树型结构来生成和解析json，生成json时，根据json内容结构，我们创建不同类型的节点对象，组装这些节点生成json。解析json时，它不需要绑定json到java bean，根据json结构，使用path或get方法轻松查找内容。

学习参考：http://www.cnblogs.com/lee0oo0/articles/2652528.html