Vel*_*aga 8 java json jackson gson
我正在使用spring-boot开发后端服务。有一种方案可以比较2个bean（一个是DB对象，另一个是客户请求的对象），然后返回“新元素”，“修改后的元素”，如果没有变化，则返回false。2豆格式如下
"sampleList":{
"timeStamp":"Thu, 21 Jun 2018 07:57:00 +0000",
"id":"5b19441ac9e77c000189b991",
"sampleListTypeId":"type001",
"friendlyName":"sample",
"contacts":[
{
"id":"5b05329cc9e77c000189b950",
"priorityOrder":1,
"name":"sample1",
"relation":"Friend",
"sampleInfo":{
"countryCode":"91",
"numberType":"MOBILE",
"numberRegion":"IN"
}
},
{
"id":"5b05329cc9e77c000189b950",
"priorityOrder":1,
"name":"sample2",
"relation":"Friend",
"sampleInfo":{
"countryCode":"91",
"numberType":"MOBILE",
"numberRegion":"IN"
}
}
]
}
我已经在Java上浏览了有关此方案的bean比较的Internet，但是找不到任何更简单的解决方案，但是找到了一些很酷的JSON解决方案。我可以看到GSON的一些解决方案，但它不会返回包含“新元素”和“变更元素”的客户端对象。有什么方法可以用JSON或JAVA返回更新和修改的元素？您的帮助应该是可观的。对于我来说，即使是提示也将是一个很好的开始。
cas*_*lin 11
Maps 读取JSON文档并进行比较您可以将两个JSON文档读为Map<K, V>。请参阅以下有关Jackson和Gson的示例：
ObjectMapper mapper = new ObjectMapper();
TypeReference<HashMap<String, Object>> type =
new TypeReference<HashMap<String, Object>>() {};
Map<String, Object> leftMap = mapper.readValue(leftJson, type);
Map<String, Object> rightMap = mapper.readValue(rightJson, type);
Gson gson = new Gson();
Type type = new TypeToken<Map<String, Object>>(){}.getType();
Map<String, Object> leftMap = gson.fromJson(leftJson, type);
Map<String, Object> rightMap = gson.fromJson(rightJson, type);
然后使用番石榴Maps.difference(Map<K, V>, Map<K, V>)来比较它们。它返回一个MapDifference<K, V>实例：
MapDifference<String, Object> difference = Maps.difference(leftMap, rightMap);
如果您对结果不满意，可以考虑展平地图，然后进行比较。它将提供更好的比较结果，尤其是对于嵌套对象和数组。
Map进行比较要平整地图，可以使用：
public final class FlatMapUtil {
private FlatMapUtil() {
throw new AssertionError("No instances for you!");
}
public static Map<String, Object> flatten(Map<String, Object> map) {
return map.entrySet().stream()
.flatMap(FlatMapUtil::flatten)
.collect(LinkedHashMap::new, (m, e) -> m.put("/" + e.getKey(), e.getValue()), LinkedHashMap::putAll);
}
private static Stream<Map.Entry<String, Object>> flatten(Map.Entry<String, Object> entry) {
if (entry == null) {
return Stream.empty();
}
if (entry.getValue() instanceof Map<?, ?>) {
return ((Map<?, ?>) entry.getValue()).entrySet().stream()
.flatMap(e -> flatten(new AbstractMap.SimpleEntry<>(entry.getKey() + "/" + e.getKey(), e.getValue())));
}
if (entry.getValue() instanceof List<?>) {
List<?> list = (List<?>) entry.getValue();
return IntStream.range(0, list.size())
.mapToObj(i -> new AbstractMap.SimpleEntry<String, Object>(entry.getKey() + "/" + i, list.get(i)))
.flatMap(FlatMapUtil::flatten);
}
return Stream.of(entry);
}
}
它对密钥使用RFC 6901中定义的JSON指针符号，因此您可以轻松地找到值。
考虑以下JSON文档：
{
"name": {
"first": "John",
"last": "Doe"
},
"address": null,
"birthday": "1980-01-01",
"company": "Acme",
"occupation": "Software engineer",
"phones": [
{
"number": "000000000",
"type": "home"
},
{
"number": "999999999",
"type": "mobile"
}
]
}
{
"name": {
"first": "Jane",
"last": "Doe",
"nickname": "Jenny"
},
"birthday": "1990-01-01",
"occupation": null,
"phones": [
{
"number": "111111111",
"type": "mobile"
}
],
"favorite": true,
"groups": [
"close-friends",
"gym"
]
}
并使用以下代码对其进行比较并显示差异：
Map<String, Object> leftFlatMap = FlatMapUtil.flatten(leftMap);
Map<String, Object> rightFlatMap = FlatMapUtil.flatten(rightMap);
MapDifference<String, Object> difference = Maps.difference(leftFlatMap, rightFlatMap);
System.out.println("Entries only on the left\n--------------------------");
difference.entriesOnlyOnLeft()
.forEach((key, value) -> System.out.println(key + ": " + value));
System.out.println("\n\nEntries only on the right\n--------------------------");
difference.entriesOnlyOnRight()
.forEach((key, value) -> System.out.println(key + ": " + value));
System.out.println("\n\nEntries differing\n--------------------------");
difference.entriesDiffering()
.forEach((key, value) -> System.out.println(key + ": " + value));
它将产生以下输出：
Entries only on the left
--------------------------
/address: null
/phones/1/number: 999999999
/phones/1/type: mobile
/company: Acme
Entries only on the right
--------------------------
/name/nickname: Jenny
/groups/0: close-friends
/groups/1: gym
/favorite: true
Entries differing
--------------------------
/birthday: (1980-01-01, 1990-01-01)
/occupation: (Software engineer, null)
/name/first: (John, Jane)
/phones/0/number: (000000000, 111111111)
/phones/0/type: (home, mobile)
cas*_*lin 10
除了其他答案中描述的方法之外，您还可以使用JSR 374中定义的Java API进行JSON处理（在Gson或Jackson上不使用）。需要以下依赖项：
<!-- Java API for JSON Processing (API) -->
<dependency>
<groupId>javax.json</groupId>
<artifactId>javax.json-api</artifactId>
<version>1.1.2</version>
</dependency>
<!-- Java API for JSON Processing (implementation) -->
<dependency>
<groupId>org.glassfish</groupId>
<artifactId>javax.json</artifactId>
<version>1.1.2</version>
</dependency>
然后，您可以根据JSON文档创建JSON差异。它将生成RFC 6902中定义的JSON Patch文档：
JsonPatch diff = Json.createDiff(source, target);
当应用于源文档时，JSON补丁会生成目标文档。可以使用以下命令将JSON补丁应用于源文档：
JsonObject patched = diff.apply(source);
根据您的需求，您可以创建RFC 7396中定义的JSON合并补丁文件：
JsonMergePatch mergeDiff = Json.createMergeDiff(source, target);
当应用于源文档时，JSON合并补丁程序将产生目标文档。要修补源，请使用：
JsonValue patched = mergeDiff.apply(source);
要漂亮地打印JSON文档，可以使用：
System.out.println(format(diff.toJsonArray()));
System.out.println(format(mergeDiff.toJsonValue()));
public static String format(JsonValue json) {
StringWriter stringWriter = new StringWriter();
prettyPrint(json, stringWriter);
return stringWriter.toString();
}
public static void prettyPrint(JsonValue json, Writer writer) {
Map<String, Object> config =
Collections.singletonMap(JsonGenerator.PRETTY_PRINTING, true);
JsonWriterFactory writerFactory = Json.createWriterFactory(config);
try (JsonWriter jsonWriter = writerFactory.createWriter(writer)) {
jsonWriter.write(json);
}
}
考虑以下JSON文档：
{
"name": {
"first": "John",
"last": "Doe"
},
"address": null,
"birthday": "1980-01-01",
"company": "Acme",
"occupation": "Software engineer",
"phones": [
{
"number": "000000000",
"type": "home"
},
{
"number": "999999999",
"type": "mobile"
}
]
}
{
"name": {
"first": "Jane",
"last": "Doe",
"nickname": "Jenny"
},
"birthday": "1990-01-01",
"occupation": null,
"phones": [
{
"number": "111111111",
"type": "mobile"
}
],
"favorite": true,
"groups": [
"close-friends",
"gym"
]
}
下面的代码生成一个JSON补丁：
JsonValue source = Json.createReader(new StringReader(leftJson)).readValue();
JsonValue target = Json.createReader(new StringReader(rightJson)).readValue();
JsonPatch diff = Json.createDiff(source.asJsonObject(), target.asJsonObject());
System.out.println(format(diff.toJsonArray()));
它将产生以下输出：
[
{
"op": "replace",
"path": "/name/first",
"value": "Jane"
},
{
"op": "add",
"path": "/name/nickname",
"value": "Jenny"
},
{
"op": "remove",
"path": "/address"
},
{
"op": "replace",
"path": "/birthday",
"value": "1990-01-01"
},
{
"op": "remove",
"path": "/company"
},
{
"op": "replace",
"path": "/occupation",
"value": null
},
{
"op": "replace",
"path": "/phones/1/number",
"value": "111111111"
},
{
"op": "remove",
"path": "/phones/0"
},
{
"op": "add",
"path": "/favorite",
"value": true
},
{
"op": "add",
"path": "/groups",
"value": [
"close-friends",
"gym"
]
}
]
现在考虑以下代码来生成JSON合并补丁：
JsonValue source = Json.createReader(new StringReader(leftJson)).readValue();
JsonValue target = Json.createReader(new StringReader(rightJson)).readValue();
JsonMergePatch mergeDiff = Json.createMergeDiff(source, target);
System.out.println(format(mergeDiff.toJsonValue()));
它将产生以下输出：
{
"name": {
"first": "Jane",
"nickname": "Jenny"
},
"address": null,
"birthday": "1990-01-01",
"company": null,
"occupation": null,
"phones": [
{
"number": "111111111",
"type": "mobile"
}
],
"favorite": true,
"groups": [
"close-friends",
"gym"
]
}
应用补丁程序文档时，上述方法的结果略有不同。考虑以下将JSON Patch应用于文档的代码：
JsonPatch diff = ...
JsonValue patched = diff.apply(source.asJsonObject());
System.out.println(format(patched));
它产生：
{
"name": {
"first": "Jane",
"last": "Doe",
"nickname": "Jenny"
},
"birthday": "1990-01-01",
"occupation": null,
"phones": [
{
"number": "111111111",
"type": "mobile"
}
],
"favorite": true,
"groups": [
"close-friends",
"gym"
]
}
现在考虑以下将JSON Merge Patch应用于文档的代码：
JsonMergePatch mergeDiff = ...
JsonValue patched = mergeDiff.apply(source);
System.out.println(format(patched));
它产生：
{
"name": {
"first": "Jane",
"last": "Doe",
"nickname": "Jenny"
},
"birthday": "1990-01-01",
"phones": [
{
"number": "111111111",
"type": "mobile"
}
],
"favorite": true,
"groups": [
"close-friends",
"gym"
]
}
在第一个示例中，occupation属性为null。在第二个示例中，将其省略。这是由于nullJSON Merge Patch 的语义所致。从RFC 7396中：
如果目标确实包含该成员，则将替换该值。合并补丁中的空值具有特殊含义，以指示已删除目标中的现有值。[...]
这种设计意味着合并补丁文档适用于描述对JSON文档的修改，这些修改主要是将对象用于其结构，而不使用显式的空值。合并补丁程序格式不适用于所有JSON语法。
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