JsonDeserializer 不适用于 Class 但仅适用于 class 的单个元素
JsonDeserializer does not work on the Class but only on the single element of the class
我创建了一个新的反序列化器，可以将空字符串写成 null
public class CustomDeserializer extends JsonDeserializer<String> {
@Override
public String deserialize(JsonParser jsonParser, DeserializationContext context) throws IOException {
JsonNode node = jsonParser.readValueAsTree();
if (node.asText().isEmpty()) {
return null;
}
return node.toString();
}
}
试图在每个用户字段上制作单个注释，自定义工作但通过在整个 class 上插入注释，我无法再打印 Json 消息
@JsonDeserialize(using = CustomDeserializer.class)
public class User {
private String firstName;
private String lastName;
private String age;
private String address; }
CustomExceptionHandler 向我抛出此错误：Class MethodArgumentNotValidException
这是我的 Kafka 消费者，这是我唯一输入验证注释的消费者，但即使删除它也会给我同样的错误
public class KafkaConsumer {
@Autowired
private UserRepository userRepository;
@KafkaListener(topics = "${spring.kafka.topic.name}")
public void listen(@Validated User user) {
User user = new User(user);
UserRepository.save(user.getName(), user);
}
}
对象映射器
public ObjectMapper getObjectMapper() {
ObjectMapper mapper = new ObjectMapper();
mapper.registerModule(new JavaTimeModule());
mapper.configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false);
mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
mapper.setSerializationInclusion(Include.NON_NULL);
return mapper;
}
是否可以让它在整个 class 中发挥作用？
如果您希望空 String 表示 整个 对象被视为 null，您可以启用 ACCEPT_EMPTY_STRING_AS_NULL_OBJECT Jackson deserialization feature，默认禁用。
您可以在配置 ObjectMapper 时包含它：
public ObjectMapper getObjectMapper() {
ObjectMapper mapper = new ObjectMapper();
mapper.registerModule(new JavaTimeModule());
mapper.configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false);
mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
mapper.setSerializationInclusion(Include.NON_NULL);
// Enable ACCEPT_EMPTY_STRING_AS_NULL_OBJECT deserialization feature
mapper.enable(DeserializationFeature.ACCEPT_EMPTY_STRING_AS_NULL_OBJECT);
return mapper;
}
如上所述，当您想将表示 整个 对象的空 String 视为 null 时，它很有用；但是，它不适用于 String 类型的单个属性：在后一种情况下，您可以安全地使用自定义反序列化器，因此，解决方案实际上是两种方法的混合，使用 ACCEPT_EMPTY_STRING_AS_NULL_OBJECT 反序列化处理整个对象的功能，以及处理单个 String 属性的自定义反序列化器。
请参阅 this and 相关的 SO 问题。
您也可以改进自定义 User 反序列化器。请考虑例如（为了清楚起见，我将名称重构为 UserDeserializer）：
import java.io.IOException;
import java.lang.annotation.Annotation;
import java.lang.reflect.Field;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonAlias;
import com.fasterxml.jackson.core.JsonParser;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.DeserializationContext;
import com.fasterxml.jackson.databind.JsonDeserializer;
import com.fasterxml.jackson.databind.JsonNode;
public class UserDeserializer extends JsonDeserializer<User> {
@Override
public User deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
JsonNode node = jsonParser.readValueAsTree();
Iterator<String> fieldNames = node.fieldNames();
// Process Jackson annotations looking for aliases
Map<String, String> fieldAliases = this.getAliases();
User user = new User();
boolean anyNonNull = false;
// Iterate over every field. The deserialization process assume simple properties
while(fieldNames.hasNext()) {
String fieldName = fieldNames.next();
JsonNode fieldValue = node.get(fieldName);
String fieldValueTextRepresentation = fieldValue.asText();
if (fieldValueTextRepresentation != null && !fieldValueTextRepresentation.trim().isEmpty()) {
// Check if the field is aliased
String actualFieldName = fieldAliases.get(fieldName);
if (actualFieldName == null) {
actualFieldName = fieldName;
}
this.setFieldValue(user, actualFieldName, fieldValueTextRepresentation);
anyNonNull = true;
}
}
return anyNonNull ? user : null;
}
// Set field value via Reflection
private void setFieldValue(User user, String fieldName, String fieldValueTextRepresentation) {
try {
Field field = User.class.getDeclaredField(fieldName);
Object fieldValue = null;
Class clazz = field.getType();
// Handle each class type: probably this code can be improved, but it is extensible and adaptable,
// you can include as many cases as you need.
if (clazz.isAssignableFrom(String.class)) {
fieldValue = fieldValueTextRepresentation;
} else if (clazz.isAssignableFrom(LocalDate.class)) {
// Adjust the date pattern as required
// For example, if you are receiving the information
// like this: year-month-day, as in the provided example,
// you can use the following pattern
fieldValue = LocalDate.parse(fieldValueTextRepresentation, DateTimeFormatter.ofPattern("yyyy-MM-dd"));
} else if (clazz.isAssignableFrom(Integer.class)) {
fieldValue = Integer.parseInt(fieldValueTextRepresentation);
}
field.setAccessible(true);
field.set(user, fieldValue);
} catch (Exception e) {
// Handle the problem as appropriate
e.printStackTrace();
}
}
/* Look for Jackson aliases */
private Map<String, String> getAliases() {
Map<String, String> fieldAliases = new HashMap<>();
Field[] fields = User.class.getDeclaredFields();
for (Field field: fields) {
Annotation annotation = field.getAnnotation(JsonAlias.class);
if (annotation != null) {
String fieldName = field.getName();
JsonAlias jsonAliasAnnotation = (JsonAlias) annotation;
String[] aliases = jsonAliasAnnotation.value();
for (String alias: aliases) {
fieldAliases.put(alias, fieldName);
}
}
}
return fieldAliases;
}
}
有了这个序列化器，给定一个 User class 类似于：
import java.time.LocalDate;
import com.fasterxml.jackson.annotation.JsonAlias;
import com.fasterxml.jackson.databind.annotation.JsonDeserialize;
@JsonDeserialize(using = UserDeserializer.class)
public class User {
private String firstName;
private String lastName;
private Integer age;
private String address;
@JsonAlias("dateofbirth")
private LocalDate dateOfBirth;
// Setters and getters omitted for brevity
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
User user = (User) o;
if (firstName != null ? !firstName.equals(user.firstName) : user.firstName != null) return false;
if (lastName != null ? !lastName.equals(user.lastName) : user.lastName != null) return false;
if (age != null ? !age.equals(user.age) : user.age != null) return false;
if (address != null ? !address.equals(user.address) : user.address != null) return false;
return dateOfBirth != null ? dateOfBirth.equals(user.dateOfBirth) : user.dateOfBirth == null;
}
@Override
public int hashCode() {
int result = firstName != null ? firstName.hashCode() : 0;
result = 31 * result + (lastName != null ? lastName.hashCode() : 0);
result = 31 * result + (age != null ? age.hashCode() : 0);
result = 31 * result + (address != null ? address.hashCode() : 0);
result = 31 * result + (dateOfBirth != null ? dateOfBirth.hashCode() : 0);
return result;
}
以及以下 JSON（我更改为 dateofbirth 字段的名称只是为了测试别名）：
{"firstName":"John","age":40,"dateofbirth":"1978-03-16"}
您应该获得适当的结果，请考虑以下测试：
public static void main(String... args) throws JsonProcessingException {
User user = new User();
user.setFirstName("John");
user.setAge(40);
user.setDateOfBirth(LocalDate.of(1978, Month.MARCH, 16));
ObjectMapper mapper = new ObjectMapper();
mapper.setSerializationInclusion(JsonInclude.Include.NON_NULL);
String json = "{\"firstName\":\"John\",\"age\":40,\"dateofbirth\":\"1978-03-16\"}";
User reconstructed = mapper.readValue(json, User.class);
System.out.println(user.equals(reconstructed));
}
最后，请注意，为了让您的 @KafkaListener 处理 null 值，您必须使用带有 required = false 的 @Payload 注释，例如:
public class KafkaConsumer {
@Autowired
private UserRepository userRepository;
@KafkaListener(topics = "${spring.kafka.topic.name}")
public void listen(@Payload(required = false) User user) {
// Handle null value
if (user == null) {
// Consider logging the event
// logger.debug("Null message received");
System.out.println("Null message received");
return;
}
// Continue as usual
User user = new User(user);
UserRepository.save(user.getName(), user);
}
}
参见相关的 Spring Kafka documentation and this Github issue and the related commit. 也可能相关。
CustomDeserializer 是为类型 String 定义的，它用于反序列化 User 对象。这就是为什么反序列化器在应用时在单个 User 字段上工作，而不是在整个 User 对象上工作的原因。为了在整个 User 对象上应用反序列化器，CustomDeserializer 应该是 User 类型。像这样：
public class CustomDeserializer extends JsonDeserializer<User> {
@Override
public User deserialize(JsonParser jsonParser, DeserializationContext context) throws
IOException {
JsonNode node = jsonParser.readValueAsTree();
String firstName = null;
String lastName = null;
String age = null;
String address = null;
if(node.has("firstName") && !node.get("firstName").asText().isEmpty()) {
firstName = node.get("firstName").asText();
}
if(node.has("lastName") && !node.get("lastName").asText().isEmpty()) {
lastName = node.get("lastName").asText();
}
if(node.has("age") && !node.get("age").asText().isEmpty()) {
age = node.get("age").asText();
}
if(node.has("address") && !node.get("address").asText().isEmpty()) {
address = node.get("address").asText();
}
if(firstName == null && lastName == null && age == null && address == null) {
return null;
}
return new User(firstName, lastName, age, address);
}
}
现在，这可用于反序列化整个 User 对象：
示例输入：
{
"firstName" : "",
"lastName" : "Paul",
"age" : "31"
}
将被反序列化为：
User{firstName='null', lastName='Paul', age='31', address='null'}
我创建了一个新的反序列化器，可以将空字符串写成 null
public class CustomDeserializer extends JsonDeserializer<String> {
@Override
public String deserialize(JsonParser jsonParser, DeserializationContext context) throws IOException {
JsonNode node = jsonParser.readValueAsTree();
if (node.asText().isEmpty()) {
return null;
}
return node.toString();
}
}
试图在每个用户字段上制作单个注释，自定义工作但通过在整个 class 上插入注释，我无法再打印 Json 消息
@JsonDeserialize(using = CustomDeserializer.class)
public class User {
private String firstName;
private String lastName;
private String age;
private String address; }
CustomExceptionHandler 向我抛出此错误：Class MethodArgumentNotValidException 这是我的 Kafka 消费者，这是我唯一输入验证注释的消费者，但即使删除它也会给我同样的错误
public class KafkaConsumer {
@Autowired
private UserRepository userRepository;
@KafkaListener(topics = "${spring.kafka.topic.name}")
public void listen(@Validated User user) {
User user = new User(user);
UserRepository.save(user.getName(), user);
}
}
对象映射器
public ObjectMapper getObjectMapper() {
ObjectMapper mapper = new ObjectMapper();
mapper.registerModule(new JavaTimeModule());
mapper.configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false);
mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
mapper.setSerializationInclusion(Include.NON_NULL);
return mapper;
}
是否可以让它在整个 class 中发挥作用？
如果您希望空 String 表示 整个 对象被视为 null，您可以启用 ACCEPT_EMPTY_STRING_AS_NULL_OBJECT Jackson deserialization feature，默认禁用。
您可以在配置 ObjectMapper 时包含它：
public ObjectMapper getObjectMapper() {
ObjectMapper mapper = new ObjectMapper();
mapper.registerModule(new JavaTimeModule());
mapper.configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false);
mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
mapper.setSerializationInclusion(Include.NON_NULL);
// Enable ACCEPT_EMPTY_STRING_AS_NULL_OBJECT deserialization feature
mapper.enable(DeserializationFeature.ACCEPT_EMPTY_STRING_AS_NULL_OBJECT);
return mapper;
}
如上所述，当您想将表示 整个 对象的空 String 视为 null 时，它很有用；但是，它不适用于 String 类型的单个属性：在后一种情况下，您可以安全地使用自定义反序列化器，因此，解决方案实际上是两种方法的混合，使用 ACCEPT_EMPTY_STRING_AS_NULL_OBJECT 反序列化处理整个对象的功能，以及处理单个 String 属性的自定义反序列化器。
请参阅 this and
您也可以改进自定义 User 反序列化器。请考虑例如（为了清楚起见，我将名称重构为 UserDeserializer）：
import java.io.IOException;
import java.lang.annotation.Annotation;
import java.lang.reflect.Field;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonAlias;
import com.fasterxml.jackson.core.JsonParser;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.DeserializationContext;
import com.fasterxml.jackson.databind.JsonDeserializer;
import com.fasterxml.jackson.databind.JsonNode;
public class UserDeserializer extends JsonDeserializer<User> {
@Override
public User deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
JsonNode node = jsonParser.readValueAsTree();
Iterator<String> fieldNames = node.fieldNames();
// Process Jackson annotations looking for aliases
Map<String, String> fieldAliases = this.getAliases();
User user = new User();
boolean anyNonNull = false;
// Iterate over every field. The deserialization process assume simple properties
while(fieldNames.hasNext()) {
String fieldName = fieldNames.next();
JsonNode fieldValue = node.get(fieldName);
String fieldValueTextRepresentation = fieldValue.asText();
if (fieldValueTextRepresentation != null && !fieldValueTextRepresentation.trim().isEmpty()) {
// Check if the field is aliased
String actualFieldName = fieldAliases.get(fieldName);
if (actualFieldName == null) {
actualFieldName = fieldName;
}
this.setFieldValue(user, actualFieldName, fieldValueTextRepresentation);
anyNonNull = true;
}
}
return anyNonNull ? user : null;
}
// Set field value via Reflection
private void setFieldValue(User user, String fieldName, String fieldValueTextRepresentation) {
try {
Field field = User.class.getDeclaredField(fieldName);
Object fieldValue = null;
Class clazz = field.getType();
// Handle each class type: probably this code can be improved, but it is extensible and adaptable,
// you can include as many cases as you need.
if (clazz.isAssignableFrom(String.class)) {
fieldValue = fieldValueTextRepresentation;
} else if (clazz.isAssignableFrom(LocalDate.class)) {
// Adjust the date pattern as required
// For example, if you are receiving the information
// like this: year-month-day, as in the provided example,
// you can use the following pattern
fieldValue = LocalDate.parse(fieldValueTextRepresentation, DateTimeFormatter.ofPattern("yyyy-MM-dd"));
} else if (clazz.isAssignableFrom(Integer.class)) {
fieldValue = Integer.parseInt(fieldValueTextRepresentation);
}
field.setAccessible(true);
field.set(user, fieldValue);
} catch (Exception e) {
// Handle the problem as appropriate
e.printStackTrace();
}
}
/* Look for Jackson aliases */
private Map<String, String> getAliases() {
Map<String, String> fieldAliases = new HashMap<>();
Field[] fields = User.class.getDeclaredFields();
for (Field field: fields) {
Annotation annotation = field.getAnnotation(JsonAlias.class);
if (annotation != null) {
String fieldName = field.getName();
JsonAlias jsonAliasAnnotation = (JsonAlias) annotation;
String[] aliases = jsonAliasAnnotation.value();
for (String alias: aliases) {
fieldAliases.put(alias, fieldName);
}
}
}
return fieldAliases;
}
}
有了这个序列化器，给定一个 User class 类似于：
import java.time.LocalDate;
import com.fasterxml.jackson.annotation.JsonAlias;
import com.fasterxml.jackson.databind.annotation.JsonDeserialize;
@JsonDeserialize(using = UserDeserializer.class)
public class User {
private String firstName;
private String lastName;
private Integer age;
private String address;
@JsonAlias("dateofbirth")
private LocalDate dateOfBirth;
// Setters and getters omitted for brevity
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (o == null || getClass() != o.getClass()) return false;
User user = (User) o;
if (firstName != null ? !firstName.equals(user.firstName) : user.firstName != null) return false;
if (lastName != null ? !lastName.equals(user.lastName) : user.lastName != null) return false;
if (age != null ? !age.equals(user.age) : user.age != null) return false;
if (address != null ? !address.equals(user.address) : user.address != null) return false;
return dateOfBirth != null ? dateOfBirth.equals(user.dateOfBirth) : user.dateOfBirth == null;
}
@Override
public int hashCode() {
int result = firstName != null ? firstName.hashCode() : 0;
result = 31 * result + (lastName != null ? lastName.hashCode() : 0);
result = 31 * result + (age != null ? age.hashCode() : 0);
result = 31 * result + (address != null ? address.hashCode() : 0);
result = 31 * result + (dateOfBirth != null ? dateOfBirth.hashCode() : 0);
return result;
}
以及以下 JSON（我更改为 dateofbirth 字段的名称只是为了测试别名）：
{"firstName":"John","age":40,"dateofbirth":"1978-03-16"}
您应该获得适当的结果，请考虑以下测试：
public static void main(String... args) throws JsonProcessingException {
User user = new User();
user.setFirstName("John");
user.setAge(40);
user.setDateOfBirth(LocalDate.of(1978, Month.MARCH, 16));
ObjectMapper mapper = new ObjectMapper();
mapper.setSerializationInclusion(JsonInclude.Include.NON_NULL);
String json = "{\"firstName\":\"John\",\"age\":40,\"dateofbirth\":\"1978-03-16\"}";
User reconstructed = mapper.readValue(json, User.class);
System.out.println(user.equals(reconstructed));
}
最后，请注意，为了让您的 @KafkaListener 处理 null 值，您必须使用带有 required = false 的 @Payload 注释，例如:
public class KafkaConsumer {
@Autowired
private UserRepository userRepository;
@KafkaListener(topics = "${spring.kafka.topic.name}")
public void listen(@Payload(required = false) User user) {
// Handle null value
if (user == null) {
// Consider logging the event
// logger.debug("Null message received");
System.out.println("Null message received");
return;
}
// Continue as usual
User user = new User(user);
UserRepository.save(user.getName(), user);
}
}
参见相关的 Spring Kafka documentation and this Github issue and the related commit.
CustomDeserializer 是为类型 String 定义的，它用于反序列化 User 对象。这就是为什么反序列化器在应用时在单个 User 字段上工作，而不是在整个 User 对象上工作的原因。为了在整个 User 对象上应用反序列化器，CustomDeserializer 应该是 User 类型。像这样：
public class CustomDeserializer extends JsonDeserializer<User> {
@Override
public User deserialize(JsonParser jsonParser, DeserializationContext context) throws
IOException {
JsonNode node = jsonParser.readValueAsTree();
String firstName = null;
String lastName = null;
String age = null;
String address = null;
if(node.has("firstName") && !node.get("firstName").asText().isEmpty()) {
firstName = node.get("firstName").asText();
}
if(node.has("lastName") && !node.get("lastName").asText().isEmpty()) {
lastName = node.get("lastName").asText();
}
if(node.has("age") && !node.get("age").asText().isEmpty()) {
age = node.get("age").asText();
}
if(node.has("address") && !node.get("address").asText().isEmpty()) {
address = node.get("address").asText();
}
if(firstName == null && lastName == null && age == null && address == null) {
return null;
}
return new User(firstName, lastName, age, address);
}
}
现在，这可用于反序列化整个 User 对象：
示例输入：
{
"firstName" : "",
"lastName" : "Paul",
"age" : "31"
}
将被反序列化为：
User{firstName='null', lastName='Paul', age='31', address='null'}