概念与定义
什么是 edm 辅助序列化器?
edm 辅助序列化器(edmassistedserializer)是 apache olingo odata 框架中的一种特殊序列化器,专门设计用于在缺少完整 edm(实体数据模型)信息的情况下进行数据序列化。
核心概念
- edm(entity data model): odata 服务的元数据模型,定义了实体类型、属性、关系等
- 辅助(assisted): 表示该序列化器可以在没有完整 edm 信息的情况下工作
- 智能推断: 能够根据数据本身推断出类型和结构信息
设计目标

核心特点
1. edm 信息可选
// 可以在没有 edm 信息的情况下工作
edmassistedserializer serializer = odata.createedmassistedserializer(contenttype.application_json);
// 如果有 edm 信息,会利用它进行验证和优化
serializerresult result = serializer.entitycollection(
metadata, // 可选的 servicemetadata
null, // 可选的 edmentitytype
entitycollection, // 必需的数据
options // 序列化选项
);2. 智能类型推断
// 自动推断数据类型 entity entity = new entity(); entity.addproperty(new property(null, "name", valuetype.primitive, "john")); entity.addproperty(new property(null, "age", valuetype.primitive, 25)); entity.addproperty(new property(null, "salary", valuetype.primitive, 50000.50)); entity.addproperty(new property(null, "isactive", valuetype.primitive, true)); // 序列化器会自动推断: // name -> string // age -> integer // salary -> double // isactive -> boolean
3. 版本感知
// 支持不同 odata 版本
list<string> versions = arrays.aslist("4.01", "4.0");
edmassistedserializer serializer = odata.createedmassistedserializer(contenttype.application_json, versions);
// 根据版本自动选择合适的常量和行为
// v4.0: 使用 constantsv00
// v4.01+: 使用 constantsv014. 元数据级别控制
// 不同的元数据级别 edmassistedserializer nometadata = odata.createedmassistedserializer(contenttype.json_no_metadata); edmassistedserializer minimalmetadata = odata.createedmassistedserializer(contenttype.json); edmassistedserializer fullmetadata = odata.createedmassistedserializer(contenttype.json_full_metadata);
与标准序列化器的区别
对比表格
| 特性 | 标准序列化器 (odataserializer) | edm 辅助序列化器 (edmassistedserializer) |
|---|---|---|
| edm 依赖 | 必须有完整的 edm 信息 | edm 信息可选,可以没有 |
| 类型安全 | 编译时类型检查 | 运行时类型推断 |
| 性能 | 更高(有完整类型信息) | 略低(需要推断类型) |
| 灵活性 | 较低,结构固定 | 更高,支持动态结构 |
| 使用场景 | 完整的 odata 服务 | 轻量级或动态数据序列化 |
| 支持格式 | json, xml | 仅 json |
| 开发速度 | 需要先定义 edm | 可以直接开始开发 |
| 适用阶段 | 生产环境 | 开发、原型、集成阶段 |
使用决策流程

工作原理
序列化流程

类型推断机制
// 类型推断示例
public class typeinferenceexample {
public void demonstratetypeinference() {
entity entity = new entity();
// 字符串类型推断
entity.addproperty(new property(null, "stringprop", valuetype.primitive, "hello"));
// 输出: "stringprop": "hello"
// 数值类型推断
entity.addproperty(new property(null, "intprop", valuetype.primitive, 42));
// 输出: "intprop@odata.type": "#int32", "intprop": 42
entity.addproperty(new property(null, "doubleprop", valuetype.primitive, 3.14));
// 输出: "doubleprop@odata.type": "#double", "doubleprop": 3.14
// 布尔类型推断
entity.addproperty(new property(null, "boolprop", valuetype.primitive, true));
// 输出: "boolprop": true
// 日期类型推断
entity.addproperty(new property(null, "dateprop", valuetype.primitive,
calendar.getinstance()));
// 输出: "dateprop@odata.type": "#datetimeoffset", "dateprop": "2025-01-15t10:30:00z"
// 复杂类型推断
complexvalue address = new complexvalue();
address.getvalue().add(new property(null, "street", valuetype.primitive, "main st"));
address.getvalue().add(new property(null, "city", valuetype.primitive, "seattle"));
entity.addproperty(new property(null, "address", valuetype.complex, address));
// 输出: "address": { "street": "main st", "city": "seattle" }
}
}详细api分析
核心接口
public interface edmassistedserializer {
/**
* 序列化实体集合
* @param metadata 服务元数据(可选)
* @param referencedentitytype 引用的实体类型(可选)
* @param entitycollection 要序列化的实体集合
* @param options 序列化选项
* @return 序列化结果
*/
serializerresult entitycollection(
servicemetadata metadata,
edmentitytype referencedentitytype,
abstractentitycollection entitycollection,
edmassistedserializeroptions options
) throws serializerexception;
}实现类分析
public class edmassistedjsonserializer implements edmassistedserializer {
// 关键字段
private final boolean isieee754compatible; // ieee754 兼容性
private final boolean isodatametadatanone; // 无元数据模式
private final boolean isodatametadatafull; // 完整元数据模式
private final iconstants constants; // 版本常量
// 构造函数
public edmassistedjsonserializer(final contenttype contenttype) {
this.isieee754compatible = contenttypehelper.isodataieee754compatible(contenttype);
this.isodatametadatanone = contenttypehelper.isodatametadatanone(contenttype);
this.isodatametadatafull = contenttypehelper.isodatametadatafull(contenttype);
this.constants = new constantsv00();
}
// 版本感知构造函数
public edmassistedjsonserializer(final contenttype contenttype, final iconstants constants) {
this.isieee754compatible = contenttypehelper.isodataieee754compatible(contenttype);
this.isodatametadatanone = contenttypehelper.isodatametadatanone(contenttype);
this.isodatametadatafull = contenttypehelper.isodatametadatafull(contenttype);
this.constants = constants;
}
}序列化选项
public class edmassistedserializeroptions {
private contexturl contexturl;
public static builder with() {
return new builder();
}
public static final class builder {
private final edmassistedserializeroptions options;
private builder() {
options = new edmassistedserializeroptions();
}
public builder contexturl(final contexturl contexturl) {
options.contexturl = contexturl;
return this;
}
public edmassistedserializeroptions build() {
return options;
}
}
}使用场景
1. 快速原型开发
场景描述: 在项目初期,需要快速验证 odata 接口设计,但还没有完整的 edm 模型。
@restcontroller
@requestmapping("/api/prototype")
public class prototypecontroller {
private final odata odata = odata.newinstance();
@getmapping("/users")
public responseentity<string> getusers() throws serializerexception, ioexception {
// 快速创建测试数据,无需预定义 edm
entitycollection users = new entitycollection();
// 用户1
entity user1 = new entity();
user1.addproperty(new property(null, "id", valuetype.primitive, 1));
user1.addproperty(new property(null, "name", valuetype.primitive, "alice"));
user1.addproperty(new property(null, "email", valuetype.primitive, "alice@example.com"));
user1.addproperty(new property(null, "age", valuetype.primitive, 28));
user1.addproperty(new property(null, "isactive", valuetype.primitive, true));
users.getentities().add(user1);
// 用户2
entity user2 = new entity();
user2.addproperty(new property(null, "id", valuetype.primitive, 2));
user2.addproperty(new property(null, "name", valuetype.primitive, "bob"));
user2.addproperty(new property(null, "email", valuetype.primitive, "bob@example.com"));
user2.addproperty(new property(null, "age", valuetype.primitive, 35));
user2.addproperty(new property(null, "isactive", valuetype.primitive, false));
users.getentities().add(user2);
// 使用 edm 辅助序列化器
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.json_full_metadata);
contexturl contexturl = contexturl.with()
.entityset("users")
.selectlist("id,name,email,age,isactive")
.build();
edmassistedserializeroptions options = edmassistedserializeroptions.with()
.contexturl(contexturl)
.build();
serializerresult result = serializer.entitycollection(
null, null, users, options);
return responseentity.ok()
.contenttype(mediatype.parsemediatype("application/json"))
.body(ioutils.tostring(result.getcontent(), standardcharsets.utf_8));
}
}输出结果:
{
"@odata.context": "$metadata#users(id,name,email,age,isactive)",
"value": [
{
"@odata.id": null,
"id@odata.type": "#int32",
"id": 1,
"name": "alice",
"email": "alice@example.com",
"age@odata.type": "#int32",
"age": 28,
"isactive": true
},
{
"@odata.id": null,
"id@odata.type": "#int32",
"id": 2,
"name": "bob",
"email": "bob@example.com",
"age@odata.type": "#int32",
"age": 35,
"isactive": false
}
]
}
2. 动态数据源集成
场景描述: 从外部数据库或 api 动态获取数据,数据结构可能会变化。
@service
public class dynamicdataservice {
private final odata odata = odata.newinstance();
private final jdbctemplate jdbctemplate;
public dynamicdataservice(jdbctemplate jdbctemplate) {
this.jdbctemplate = jdbctemplate;
}
/**
* 动态查询任意表格数据并序列化为 odata 格式
*/
public string querytableasodata(string tablename, list<string> columns)
throws serializerexception, ioexception {
// 构建动态 sql
string sql = "select " + string.join(", ", columns) + " from " + tablename;
// 执行查询
list<map<string, object>> rows = jdbctemplate.queryforlist(sql);
// 转换为 odata 实体集合
entitycollection entities = new entitycollection();
for (map<string, object> row : rows) {
entity entity = new entity();
for (map.entry<string, object> entry : row.entryset()) {
string columnname = entry.getkey();
object value = entry.getvalue();
// 动态确定值类型
valuetype valuetype = determinevaluetype(value);
entity.addproperty(new property(null, columnname, valuetype, value));
}
entities.getentities().add(entity);
}
// 使用 edm 辅助序列化器
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_json);
contexturl contexturl = contexturl.with()
.entityset(tablename)
.selectlist(string.join(",", columns))
.build();
edmassistedserializeroptions options = edmassistedserializeroptions.with()
.contexturl(contexturl)
.build();
serializerresult result = serializer.entitycollection(
null, null, entities, options);
return ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
}
private valuetype determinevaluetype(object value) {
if (value == null) return valuetype.primitive;
if (value instanceof string) return valuetype.primitive;
if (value instanceof number) return valuetype.primitive;
if (value instanceof boolean) return valuetype.primitive;
if (value instanceof date || value instanceof calendar) return valuetype.primitive;
if (value instanceof map) return valuetype.complex;
if (value instanceof collection) return valuetype.collection_primitive;
return valuetype.primitive;
}
}3. 数据转换管道
场景描述: 在数据集成管道中,需要将不同格式的数据统一转换为 odata 格式。
@component
public class datatransformationpipeline {
private final odata odata = odata.newinstance();
/**
* 将 csv 数据转换为 odata json 格式
*/
public string transformcsvtoodata(string csvcontent, string entitysetname)
throws serializerexception, ioexception {
string[] lines = csvcontent.split("\n");
if (lines.length < 2) {
throw new illegalargumentexception("csv must have at least header and one data row");
}
// 解析表头
string[] headers = lines[0].split(",");
entitycollection entities = new entitycollection();
// 解析数据行
for (int i = 1; i < lines.length; i++) {
string[] values = lines[i].split(",");
entity entity = new entity();
for (int j = 0; j < headers.length && j < values.length; j++) {
string header = headers[j].trim();
string value = values[j].trim();
// 尝试推断类型并转换
object typedvalue = parsevalue(value);
entity.addproperty(new property(null, header, valuetype.primitive, typedvalue));
}
entities.getentities().add(entity);
}
return serializetoodata(entities, entitysetname);
}
/**
* 将 json 数组转换为 odata 格式
*/
public string transformjsonarraytoodata(string jsonarray, string entitysetname)
throws serializerexception, ioexception {
objectmapper mapper = new objectmapper();
try {
list<map<string, object>> datalist = mapper.readvalue(jsonarray,
new typereference<list<map<string, object>>>() {});
entitycollection entities = new entitycollection();
for (map<string, object> datamap : datalist) {
entity entity = new entity();
for (map.entry<string, object> entry : datamap.entryset()) {
string key = entry.getkey();
object value = entry.getvalue();
valuetype valuetype = determinevaluetype(value);
entity.addproperty(new property(null, key, valuetype, value));
}
entities.getentities().add(entity);
}
return serializetoodata(entities, entitysetname);
} catch (exception e) {
throw new runtimeexception("failed to parse json array", e);
}
}
private string serializetoodata(entitycollection entities, string entitysetname)
throws serializerexception, ioexception {
// 支持多版本
list<string> versions = arrays.aslist("4.01", "4.0");
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_json, versions);
contexturl contexturl = contexturl.with()
.entityset(entitysetname)
.build();
edmassistedserializeroptions options = edmassistedserializeroptions.with()
.contexturl(contexturl)
.build();
serializerresult result = serializer.entitycollection(
null, null, entities, options);
return ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
}
private object parsevalue(string value) {
// 尝试解析为不同类型
if (value.isempty() || "null".equalsignorecase(value)) {
return null;
}
// 布尔值
if ("true".equalsignorecase(value) || "false".equalsignorecase(value)) {
return boolean.parseboolean(value);
}
// 整数
try {
return integer.parseint(value);
} catch (numberformatexception e) {
// 不是整数,继续尝试其他类型
}
// 浮点数
try {
return double.parsedouble(value);
} catch (numberformatexception e) {
// 不是浮点数,继续尝试其他类型
}
// 日期(简单格式)
try {
simpledateformat dateformat = new simpledateformat("yyyy-mm-dd");
return dateformat.parse(value);
} catch (parseexception e) {
// 不是日期格式
}
// 默认作为字符串
return value;
}
private valuetype determinevaluetype(object value) {
if (value == null) return valuetype.primitive;
if (value instanceof string) return valuetype.primitive;
if (value instanceof number) return valuetype.primitive;
if (value instanceof boolean) return valuetype.primitive;
if (value instanceof date) return valuetype.primitive;
if (value instanceof map) return valuetype.complex;
if (value instanceof list) return valuetype.collection_primitive;
return valuetype.primitive;
}
}4. 微服务数据聚合
场景描述: 从多个微服务聚合数据,各服务的数据格式可能不同。
@restcontroller
@requestmapping("/api/aggregation")
public class dataaggregationcontroller {
private final odata odata = odata.newinstance();
@autowired
private userservice userservice;
@autowired
private orderservice orderservice;
@autowired
private productservice productservice;
/**
* 聚合用户、订单和产品数据
*/
@getmapping("/dashboard")
public responseentity<string> getdashboarddata() throws serializerexception, ioexception {
entitycollection dashboarddata = new entitycollection();
// 聚合用户数据
list<user> users = userservice.getactiveusers();
for (user user : users) {
entity userentity = new entity();
userentity.addproperty(new property(null, "type", valuetype.primitive, "user"));
userentity.addproperty(new property(null, "id", valuetype.primitive, user.getid()));
userentity.addproperty(new property(null, "name", valuetype.primitive, user.getname()));
userentity.addproperty(new property(null, "email", valuetype.primitive, user.getemail()));
userentity.addproperty(new property(null, "lastlogin", valuetype.primitive, user.getlastlogin()));
// 动态添加用户统计信息
map<string, object> stats = userservice.getuserstats(user.getid());
for (map.entry<string, object> stat : stats.entryset()) {
userentity.addproperty(new property(null,
"stats_" + stat.getkey(), valuetype.primitive, stat.getvalue()));
}
dashboarddata.getentities().add(userentity);
}
// 聚合订单数据
list<order> recentorders = orderservice.getrecentorders(30);
for (order order : recentorders) {
entity orderentity = new entity();
orderentity.addproperty(new property(null, "type", valuetype.primitive, "order"));
orderentity.addproperty(new property(null, "id", valuetype.primitive, order.getid()));
orderentity.addproperty(new property(null, "userid", valuetype.primitive, order.getuserid()));
orderentity.addproperty(new property(null, "amount", valuetype.primitive, order.getamount()));
orderentity.addproperty(new property(null, "status", valuetype.primitive, order.getstatus()));
orderentity.addproperty(new property(null, "createdat", valuetype.primitive, order.getcreatedat()));
dashboarddata.getentities().add(orderentity);
}
// 聚合产品数据(动态属性)
list<map<string, object>> productdata = productservice.getproductanalytics();
for (map<string, object> product : productdata) {
entity productentity = new entity();
productentity.addproperty(new property(null, "type", valuetype.primitive, "product"));
// 动态添加所有产品属性
for (map.entry<string, object> entry : product.entryset()) {
valuetype valuetype = determinevaluetype(entry.getvalue());
productentity.addproperty(new property(null,
entry.getkey(), valuetype, entry.getvalue()));
}
dashboarddata.getentities().add(productentity);
}
// 使用 edm 辅助序列化器序列化混合数据
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_json);
contexturl contexturl = contexturl.with()
.entityset("dashboarddata")
.build();
edmassistedserializeroptions options = edmassistedserializeroptions.with()
.contexturl(contexturl)
.build();
serializerresult result = serializer.entitycollection(
null, null, dashboarddata, options);
string jsonoutput = ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
return responseentity.ok()
.contenttype(mediatype.application_json)
.body(jsonoutput);
}
private valuetype determinevaluetype(object value) {
if (value == null) return valuetype.primitive;
if (value instanceof string) return valuetype.primitive;
if (value instanceof number) return valuetype.primitive;
if (value instanceof boolean) return valuetype.primitive;
if (value instanceof date || value instanceof calendar) return valuetype.primitive;
if (value instanceof map) return valuetype.complex;
if (value instanceof collection) return valuetype.collection_primitive;
return valuetype.primitive;
}
}代码案例
案例1: 基础使用
public class basicusageexample {
public void basicexample() throws serializerexception, ioexception {
odata odata = odata.newinstance();
// 1. 创建 edm 辅助序列化器
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_json);
// 2. 创建数据
entity person = new entity();
person.addproperty(new property(null, "firstname", valuetype.primitive, "john"));
person.addproperty(new property(null, "lastname", valuetype.primitive, "doe"));
person.addproperty(new property(null, "age", valuetype.primitive, 30));
entitycollection people = new entitycollection();
people.getentities().add(person);
// 3. 序列化
serializerresult result = serializer.entitycollection(
null, null, people, null);
// 4. 获取结果
string json = ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
system.out.println(json);
}
}案例2: 复杂类型处理
public class complextypeexample {
public void complextypeexample() throws serializerexception, ioexception {
odata odata = odata.newinstance();
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.json_full_metadata);
// 创建包含复杂类型的实体
entity employee = new entity();
employee.addproperty(new property(null, "employeeid", valuetype.primitive, 1001));
employee.addproperty(new property(null, "name", valuetype.primitive, "alice johnson"));
// 创建地址复杂类型
complexvalue address = new complexvalue();
address.getvalue().add(new property(null, "street", valuetype.primitive, "123 main st"));
address.getvalue().add(new property(null, "city", valuetype.primitive, "seattle"));
address.getvalue().add(new property(null, "state", valuetype.primitive, "wa"));
address.getvalue().add(new property(null, "zipcode", valuetype.primitive, "98101"));
employee.addproperty(new property(null, "address", valuetype.complex, address));
// 创建联系方式复杂类型
complexvalue contact = new complexvalue();
contact.getvalue().add(new property(null, "email", valuetype.primitive, "alice@company.com"));
contact.getvalue().add(new property(null, "phone", valuetype.primitive, "+1-555-0123"));
employee.addproperty(new property(null, "contact", valuetype.complex, contact));
// 创建技能集合
list<string> skills = arrays.aslist("java", "spring", "odata", "sql");
employee.addproperty(new property(null, "skills", valuetype.collection_primitive, skills));
entitycollection employees = new entitycollection();
employees.getentities().add(employee);
// 设置上下文 url
contexturl contexturl = contexturl.with()
.entityset("employees")
.build();
edmassistedserializeroptions options = edmassistedserializeroptions.with()
.contexturl(contexturl)
.build();
serializerresult result = serializer.entitycollection(
null, null, employees, options);
string json = ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
system.out.println("complex type example output:");
system.out.println(json);
}
}输出结果:
{
"@odata.context": "$metadata#employees",
"value": [
{
"@odata.id": null,
"employeeid@odata.type": "#int32",
"employeeid": 1001,
"name": "alice johnson",
"address": {
"street": "123 main st",
"city": "seattle",
"state": "wa",
"zipcode": "98101"
},
"contact": {
"email": "alice@company.com",
"phone": "+1-555-0123"
},
"skills@odata.type": "#collection(string)",
"skills": ["java", "spring", "odata", "sql"]
}
]
}
案例3: 版本差异处理
public class versionhandlingexample {
public void compareversions() throws serializerexception, ioexception {
odata odata = odata.newinstance();
// 创建测试数据
entity product = new entity();
product.addproperty(new property(null, "productid", valuetype.primitive, 1));
product.addproperty(new property(null, "name", valuetype.primitive, "laptop"));
product.addproperty(new property(null, "price", valuetype.primitive, 999.99));
product.addproperty(new property(null, "instock", valuetype.primitive, true));
entitycollection products = new entitycollection();
products.getentities().add(product);
// v4.0 序列化
list<string> versionsv40 = arrays.aslist("4.0");
edmassistedserializer serializerv40 = odata.createedmassistedserializer(
contenttype.application_json, versionsv40);
serializerresult resultv40 = serializerv40.entitycollection(
null, null, products, null);
string jsonv40 = ioutils.tostring(resultv40.getcontent(), standardcharsets.utf_8);
system.out.println("odata v4.0 output:");
system.out.println(jsonv40);
// v4.01 序列化
list<string> versionsv401 = arrays.aslist("4.01");
edmassistedserializer serializerv401 = odata.createedmassistedserializer(
contenttype.application_json, versionsv401);
serializerresult resultv401 = serializerv401.entitycollection(
null, null, products, null);
string jsonv401 = ioutils.tostring(resultv401.getcontent(), standardcharsets.utf_8);
system.out.println("\nodata v4.01 output:");
system.out.println(jsonv401);
}
}案例4: 元数据级别对比
public class metadatalevelexample {
public void comparemetadatalevels() throws serializerexception, ioexception {
odata odata = odata.newinstance();
// 创建测试数据
entity order = new entity();
order.addproperty(new property(null, "orderid", valuetype.primitive, 12345));
order.addproperty(new property(null, "customername", valuetype.primitive, "john smith"));
order.addproperty(new property(null, "orderdate", valuetype.primitive,
calendar.getinstance()));
order.addproperty(new property(null, "totalamount", valuetype.primitive, 129.99));
entitycollection orders = new entitycollection();
orders.getentities().add(order);
contexturl contexturl = contexturl.with()
.entityset("orders")
.build();
edmassistedserializeroptions options = edmassistedserializeroptions.with()
.contexturl(contexturl)
.build();
// 1. 无元数据
edmassistedserializer nometadata = odata.createedmassistedserializer(
contenttype.json_no_metadata);
serializerresult resultnometa = nometadata.entitycollection(
null, null, orders, options);
string jsonnometa = ioutils.tostring(resultnometa.getcontent(), standardcharsets.utf_8);
system.out.println("no metadata:");
system.out.println(jsonnometa);
// 2. 最小元数据
edmassistedserializer minimalmetadata = odata.createedmassistedserializer(
contenttype.json);
serializerresult resultminimal = minimalmetadata.entitycollection(
null, null, orders, options);
string jsonminimal = ioutils.tostring(resultminimal.getcontent(), standardcharsets.utf_8);
system.out.println("\nminimal metadata:");
system.out.println(jsonminimal);
// 3. 完整元数据
edmassistedserializer fullmetadata = odata.createedmassistedserializer(
contenttype.json_full_metadata);
serializerresult resultfull = fullmetadata.entitycollection(
null, null, orders, options);
string jsonfull = ioutils.tostring(resultfull.getcontent(), standardcharsets.utf_8);
system.out.println("\nfull metadata:");
system.out.println(jsonfull);
}
}案例5: 错误处理和边界情况
public class errorhandlingexample {
public void demonstrateerrorhandling() {
odata odata = odata.newinstance();
// 1. 不支持的内容类型
try {
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_xml); // 不支持 xml
} catch (serializerexception e) {
system.out.println("expected error - unsupported format: " + e.getmessage());
}
// 2. 空数据处理
try {
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_json);
entitycollection emptycollection = new entitycollection();
serializerresult result = serializer.entitycollection(
null, null, emptycollection, null);
string json = ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
system.out.println("empty collection result: " + json);
} catch (exception e) {
system.out.println("error handling empty collection: " + e.getmessage());
}
// 3. 空值属性处理
try {
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.application_json);
entity entitywithnulls = new entity();
entitywithnulls.addproperty(new property(null, "name", valuetype.primitive, "test"));
entitywithnulls.addproperty(new property(null, "nullvalue", valuetype.primitive, null));
entitywithnulls.addproperty(new property(null, "emptystring", valuetype.primitive, ""));
entitycollection collection = new entitycollection();
collection.getentities().add(entitywithnulls);
serializerresult result = serializer.entitycollection(
null, null, collection, null);
string json = ioutils.tostring(result.getcontent(), standardcharsets.utf_8);
system.out.println("null values handling: " + json);
} catch (exception e) {
system.out.println("error handling null values: " + e.getmessage());
}
}
}最佳实践
1. 选择合适的元数据级别
public class metadatabestpractices {
// 生产环境 - 使用最小元数据以减少带宽
public edmassistedserializer createproductionserializer() throws serializerexception {
odata odata = odata.newinstance();
return odata.createedmassistedserializer(contenttype.json);
}
// 开发和调试 - 使用完整元数据便于调试
public edmassistedserializer createdevelopmentserializer() throws serializerexception {
odata odata = odata.newinstance();
return odata.createedmassistedserializer(contenttype.json_full_metadata);
}
// 性能敏感场景 - 使用无元数据
public edmassistedserializer createperformanceserializer() throws serializerexception {
odata odata = odata.newinstance();
return odata.createedmassistedserializer(contenttype.json_no_metadata);
}
}2. 版本管理策略
public class versionmanagementbestpractices {
private final odata odata = odata.newinstance();
// 支持多版本的通用方法
public edmassistedserializer createversionawareserializer(
contenttype contenttype, string clientversion) throws serializerexception {
list<string> supportedversions = determinesupportedversions(clientversion);
return odata.createedmassistedserializer(contenttype, supportedversions);
}
private list<string> determinesupportedversions(string clientversion) {
list<string> versions = new arraylist<>();
if (clientversion != null && clientversion.startswith("4.01")) {
versions.add("4.01");
versions.add("4.0"); // 向后兼容
} else {
versions.add("4.0");
}
return versions;
}
}3. 性能优化
public class performanceoptimization {
// 序列化器复用
private final map<string, edmassistedserializer> serializercache = new concurrenthashmap<>();
private final odata odata = odata.newinstance();
public edmassistedserializer getcachedserializer(contenttype contenttype, list<string> versions)
throws serializerexception {
string key = contenttype.tocontenttypestring() + "_" +
(versions != null ? string.join(",", versions) : "default");
return serializercache.computeifabsent(key, k -> {
try {
return versions != null && !versions.isempty()
? odata.createedmassistedserializer(contenttype, versions)
: odata.createedmassistedserializer(contenttype);
} catch (serializerexception e) {
throw new runtimeexception("failed to create serializer", e);
}
});
}
// 批量序列化优化
public string serializelargedataset(list<entity> entities, string entitysetname)
throws serializerexception, ioexception {
edmassistedserializer serializer = getcachedserializer(
contenttype.json_no_metadata, null);
// 分批处理大数据集
int batchsize = 1000;
stringbuilder result = new stringbuilder();
result.append("{\"value\":[");
for (int i = 0; i < entities.size(); i += batchsize) {
int endindex = math.min(i + batchsize, entities.size());
list<entity> batch = entities.sublist(i, endindex);
entitycollection batchcollection = new entitycollection();
batchcollection.getentities().addall(batch);
serializerresult batchresult = serializer.entitycollection(
null, null, batchcollection, null);
string batchjson = ioutils.tostring(batchresult.getcontent(), standardcharsets.utf_8);
// 提取值数组部分
if (i > 0) result.append(",");
// 处理批次json...
}
result.append("]}");
return result.tostring();
}
}4. 类型安全
public class typesafetybestpractices {
// 使用类型安全的属性创建器
public static class propertybuilder {
public static property createstringproperty(string name, string value) {
return new property(null, name, valuetype.primitive, value);
}
public static property createintproperty(string name, integer value) {
return new property(null, name, valuetype.primitive, value);
}
public static property createdoubleproperty(string name, double value) {
return new property(null, name, valuetype.primitive, value);
}
public static property createbooleanproperty(string name, boolean value) {
return new property(null, name, valuetype.primitive, value);
}
public static property createdateproperty(string name, date value) {
return new property(null, name, valuetype.primitive, value);
}
public static property createcomplexproperty(string name, complexvalue value) {
return new property(null, name, valuetype.complex, value);
}
public static property createcollectionproperty(string name, collection<?> value) {
return new property(null, name, valuetype.collection_primitive, value);
}
}
// 使用示例
public entity createtypesafeentity() {
entity entity = new entity();
entity.addproperty(propertybuilder.createstringproperty("name", "john doe"));
entity.addproperty(propertybuilder.createintproperty("age", 30));
entity.addproperty(propertybuilder.createdoubleproperty("salary", 75000.0));
entity.addproperty(propertybuilder.createbooleanproperty("isactive", true));
entity.addproperty(propertybuilder.createdateproperty("hiredate", new date()));
return entity;
}
}常见问题
q1: edm 辅助序列化器与标准序列化器的性能差异有多大?
a: 在大多数场景下,性能差异在 10-20% 之间。主要开销来自运行时类型推断。
public class performancecomparison {
@test
public void compareperformance() throws exception {
// 准备测试数据
entitycollection testdata = createlargetestdataset(10000);
// 测试标准序列化器
long starttime = system.currenttimemillis();
odataserializer standardserializer = odata.createserializer(contenttype.application_json);
// ... 序列化逻辑
long standardtime = system.currenttimemillis() - starttime;
// 测试 edm 辅助序列化器
starttime = system.currenttimemillis();
edmassistedserializer assistedserializer = odata.createedmassistedserializer(
contenttype.application_json);
// ... 序列化逻辑
long assistedtime = system.currenttimemillis() - starttime;
system.out.println("standard serializer: " + standardtime + "ms");
system.out.println("assisted serializer: " + assistedtime + "ms");
system.out.println("performance ratio: " + ((double)assistedtime / standardtime));
}
}q2: 如何处理循环引用?
a: edm 辅助序列化器不会自动处理循环引用,需要在创建数据时避免。
public class circularreferencehandling {
public entity createentitywithoutcircularref(user user, set<string> processedids) {
if (processedids.contains(user.getid())) {
// 创建引用实体,避免循环
entity refentity = new entity();
refentity.addproperty(propertybuilder.createstringproperty("id", user.getid()));
refentity.addproperty(propertybuilder.createstringproperty("name", user.getname()));
return refentity;
}
processedids.add(user.getid());
entity entity = new entity();
entity.addproperty(propertybuilder.createstringproperty("id", user.getid()));
entity.addproperty(propertybuilder.createstringproperty("name", user.getname()));
// 安全地添加关联实体
if (user.getmanager() != null) {
entity managerentity = createentitywithoutcircularref(user.getmanager(), processedids);
entity.addproperty(new property(null, "manager", valuetype.complex,
convertentitytocomplexvalue(managerentity)));
}
return entity;
}
}q3: 如何优化大数据集的序列化?
a: 使用流式处理和分批序列化:
public class largedatasetoptimization {
public void streamlargedataset(iterator<entity> entityiterator, outputstream outputstream)
throws ioexception, serializerexception {
jsongenerator jsongenerator = new jsonfactory().creategenerator(outputstream);
jsongenerator.writestartobject();
jsongenerator.writearrayfieldstart("value");
edmassistedserializer serializer = odata.createedmassistedserializer(
contenttype.json_no_metadata);
while (entityiterator.hasnext()) {
entity entity = entityiterator.next();
entitycollection singleentitycollection = new entitycollection();
singleentitycollection.getentities().add(entity);
serializerresult result = serializer.entitycollection(
null, null, singleentitycollection, null);
// 直接写入流,避免内存积累
ioutils.copy(result.getcontent(), outputstream);
if (entityiterator.hasnext()) {
jsongenerator.writeraw(",");
}
}
jsongenerator.writeendarray();
jsongenerator.writeendobject();
jsongenerator.close();
}
}总结
edm 辅助序列化器的价值
- 开发效率: 无需预先定义完整的 edm 模型,可以快速开始开发
- 灵活性: 能够处理动态结构的数据,适应数据模型的变化
- 集成友好: 便于与外部系统集成,处理格式不统一的数据
- 原型开发: 适合快速原型开发和概念验证
适用场景总结
| 场景 | 适用性 | 推荐理由 |
|---|---|---|
| 快速原型开发 | ⭐⭐⭐⭐⭐ | 无需预定义 edm,快速验证想法 |
| 动态数据源 | ⭐⭐⭐⭐⭐ | 能够处理结构变化的数据 |
| 数据集成 | ⭐⭐⭐⭐ | 统一不同格式的数据输出 |
| 微服务聚合 | ⭐⭐⭐⭐ | 整合多个服务的异构数据 |
| 生产环境 | ⭐⭐⭐ | 性能略低,但提供更大灵活性 |
最终建议
- 开发阶段: 优先使用 edm 辅助序列化器,加快开发速度
- 生产环境: 如果数据结构稳定,考虑迁移到标准序列化器以获得更好性能
- 混合使用: 对于不同的接口,可以根据需求选择不同的序列化器
- 渐进式采用: 从 edm 辅助序列化器开始,逐步完善 edm 模型
edm 辅助序列化器是 apache olingo odata 框架中的一个强大工具,它在保持 odata 协议兼容性的同时,提供了极大的开发灵活性。通过合理使用,可以显著提高开发效率并简化数据集成工作。
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