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BeanToArray_cn
Athur Ming edited this page Aug 15, 2017
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在fastjson中,支持一种叫做BeanToArray的映射模式。普通模式下,JavaBean映射成json object,BeanToArray模式映射为json array。
class Model {
public int id;
public String name;
}
Model model = new Model();
model.id = 1001;
model.name = "gaotie";
// {"id":1001,"name":"gaotie"}
String text_normal = JSON.toJSONString(model);
// [1001,"gaotie"]
String text_beanToArray = JSON.toJSONString(model, SerializerFeature.BeanToArray);
// support beanToArray & normal mode
JSON.parseObject(text_beanToArray, Feature.SupportArrayToBean);
上面的例子中,BeanToArray模式下,少了Key的输出,节省了空间,json字符串较小,性能也会更好。
BeanToArray可以局部使用,比如:
class Company {
public int code;
public List<Department> departments = new ArrayList<Department>();
}
@JSONType(serialzeFeatures=SerializerFeature.BeanToArray, parseFeatures=Feature.SupportArrayToBean)
class Department {
public int id;
public String name;
public Department() {}
public Department(int id, String name) {this.id = id; this.name = name;}
}
Company company = new Company();
company.code = 100;
company.departments.add(new Department(1001, "Sales"));
company.departments.add(new Department(1002, "Financial"));
// {"code":10,"departments":[[1001,"Sales"],[1002,"Financial"]]}
String text = JSON.toJSONString(company);
在这个例子中,如果Company的属性departments元素很多,局部采用BeanToArray就可以获得很好的性能,而整体又能够获得较好的可读性。
上一个例子也可以这样写:
class Company {
public int code;
@JSONField(serialzeFeatures=SerializerFeature.BeanToArray, parseFeatures=Feature.SupportArrayToBean)
public List<Department> departments = new ArrayList<Department>();
}
使用BeanToArray模式,可以获得媲美protobuf的性能。
create ser deser total size +dfl
protobuf 244 2297 1296 3593 239 149
json/fastjson_array/databind 123 1289 1567 2856 281 163
msgpack/databind 122 1525 2180 3705 233 146
json/fastjson/databind 120 2019 2610 4629 486 262
json/jackson+afterburner/databind 118 2142 3147 5289 485 261
json/jackson/databind 124 2914 4411 7326 485 261
这里的json/fastjson_array/databind就是fastjson启用BeanToArray模式,total性能比protobuf好。具体看这里 https://github.com/alibaba/fastjson/wiki/Benchmark_1_2_11
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