java - 如何使用 Jackson 反序列化混合类型的匿名数组

Question

在我的 Java 程序中，我试图解析从 Strava.com 获得的数据。的 API。我从那里收到的 JSON 有效负载之一如下所示:

[
  {"type": "altitude","data": [519.1,519.3,519.3,519.4,519.5],"series_type": "distance","original_size": 5,"resolution": "high"},
  {"type": "latlng","data": [[46.01234,6.01234],[46.11234,6.11234],[46.21234,6.21234],[46.31234,6.31234],[46.41234,6.41234]],"series_type": "distance","original_size": 5,"resolution": "high"},
  {"type": "velocity_smooth","data": [0.0,0.0,0.0,5.5,5.2],"series_type": "distance","original_size": 5,"resolution": "high"},
  {"type": "distance","data": [0.0,8.6,11.8,16.6,20.8],"series_type": "distance","original_size": 5,"resolution": "high"},
  {"type": "time","data": [0,1,2,3,4],"series_type": "distance","original_size": 5,"resolution": "high"}
]

基本上，其中四个条目(高度、速度平滑、距离和时间)具有相同的结构(它们的 data 字段是 double 组(或可以解析为 double 的整数))，但第二个条目 (latlng) 的 data 字段结构略有不同(它是一个 double 数组的数组)。

如果所有内容都已命名，我熟悉 Jackson 库，可以在 JSON 和 POJO 之间进行转换，但不知道如何进行转换我可以对上述数据结构进行建模以将其反序列化。

假设它不是上面的数据，而是如下所示:

{
  "altitude": {"data": [519.1,519.3,519.3,519.4,519.5],"series_type": "distance","original_size": 5,"resolution": "high"},
  "latlng":  {"data": [[46.01234,6.01234],[46.11234,6.11234],[46.21234,6.21234],[46.31234,6.31234],[46.41234,6.41234]],"series_type": "distance","original_size": 5,"resolution": "high"},
  "velocity_smooth": {"data": [0.0,0.0,0.0,5.5,5.2],"series_type": "distance","original_size": 5,"resolution": "high"},
  "distance":  {"data": [0.0,8.6,11.8,16.6,20.8],"series_type": "distance","original_size": 5,"resolution": "high"},
  "time": {"data": [0,1,2,3,4],"series_type": "distance","original_size": 5,"resolution": "high"}
}

然后我可以定义以下三个类

import com.fasterxml.jackson.annotation.JsonProperty;
import lombok.AllArgsConstructor;
import lombok.Value;
import java.util.List;

@Getter
@NoArgsConstructor
public class Holder {
  DoubleData altitude;
  CoordinateData latlng;
  @JsonProperty("velocity_smooth") DoubleData velocitySmooth;
  DoubleData distance;
  DoubleData time;
}

@Getter
@NoArgsConstructor
public class DoubleData {
  List<Double> data;
  @JsonProperty("series_type")   String seriesType;
  @JsonProperty("original_size") Integer originalSize;
  String resolution;
}

@Getter
@NoArgsConstructor
public class CoordinateData {
  List<List<Double>> data;
  @JsonProperty("series_type")   String seriesType;
  @JsonProperty("original_size") Integer originalSize;
  String resolution;
}

然后使用

objectMapper.readValue(jsonString, Holder.class);

读取该对象。然而，由于从 Strava 收到的数据是一个数组而不是一个对象，所以我失败了。我已阅读Baeldung's article on how to unmarshal to collections/arrays但这假设数组/集合中的所有类都是相同的。

我想定义一个接口(interface)，该接口(interface)将由可以在数组中找到的两个类扩展，然后使用该机制:

public interface Data {
}

@Getter
@NoArgsConstructor
public class DoubleData implements Data {
  String type;
  List<Double> data;
  @JsonProperty("series_type")   String seriesType;
  @JsonProperty("original_size") Integer originalSize;
  String resolution;
}

@Getter
@NoArgsConstructor
public class CoordinateData implements Data {
  String type;
  List<List<Double>> data;
  @JsonProperty("series_type")   String seriesType;
  @JsonProperty("original_size") Integer originalSize;
  String resolution;
}

Data[] array = objectMapper.readValue(jsonString, Data[].class);

但这不起作用，因为我需要找到某种方法让它找出何时使用 DoubleData 类以及何时使用 CooperativeData 类.

我确信，我不是第一个尝试在 Java 中使用 Strava 数据的人。这可以吗？

Answer 1

如果可能的话，你绝对应该使用他们的客户端。 Strava API v3展示了如何将此 API 与其模型一起使用的许多示例。

如果您想实现自己的模型，您应该考虑继承和 com.fasterxml.jackson.annotation.JsonTypeInfo、com.fasterxml.jackson.annotation.JsonSubTypes 注释。此外，类型为latlng的JSON对象包含以数组形式表示的对象列表。我们可以使用 com.fasterxml.jackson.annotation.JsonFormat 注释来处理这个问题。总共给出:

import com.fasterxml.jackson.annotation.JsonFormat;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonSubTypes;
import com.fasterxml.jackson.annotation.JsonTypeInfo;
import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper;

import java.io.File;
import java.io.IOException;
import java.util.List;
import java.util.StringJoiner;

public class StravaApp {
    public static void main(String[] args) throws IOException {
        File jsonFile = new File("./resource/test.json").getAbsoluteFile();

        ObjectMapper mapper = new ObjectMapper();
        mapper.readValue(jsonFile, new TypeReference<List<Data>>() {}).forEach(System.out::println);
    }
}

@JsonTypeInfo(use = JsonTypeInfo.Id.NAME,
        include = JsonTypeInfo.As.EXISTING_PROPERTY,
        visible = true,
        property = "type")
@JsonSubTypes({
        @JsonSubTypes.Type(name = "altitude", value = DoubleData.class),
        @JsonSubTypes.Type(name = "latlng", value = CoordinateData.class),
        @JsonSubTypes.Type(name = "velocity_smooth", value = DoubleData.class),
        @JsonSubTypes.Type(name = "distance", value = DoubleData.class),
        @JsonSubTypes.Type(name = "time", value = DoubleData.class)
})
abstract class Data<T> {

    private String type;

    @JsonProperty("series_type")
    private String seriesType;

    @JsonProperty("original_size")
    private Integer originalSize;

    private String resolution;

    private List<T> data;

    // getters, setters, toString
}


class DoubleData extends Data<Double> {

}

class CoordinateData extends Data<Coordinates> {

}

@JsonFormat(shape = JsonFormat.Shape.ARRAY)
class Coordinates {
    private double lat;
    private double lng;

        // getters, setters, toString
}

上面的代码打印:

Data[type='altitude', seriesType='distance', originalSize=5, resolution='high', data=[519.1, 519.3, 519.3, 519.4, 519.5]]
Data[type='latlng', seriesType='distance', originalSize=5, resolution='high', data=[Coordinates[lat=46.01234, lng=6.01234], Coordinates[lat=46.11234, lng=6.11234], Coordinates[lat=46.21234, lng=6.21234], Coordinates[lat=46.31234, lng=6.31234], Coordinates[lat=46.41234, lng=6.41234]]]
Data[type='velocity_smooth', seriesType='distance', originalSize=5, resolution='high', data=[0.0, 0.0, 0.0, 5.5, 5.2]]
Data[type='distance', seriesType='distance', originalSize=5, resolution='high', data=[0.0, 8.6, 11.8, 16.6, 20.8]]
Data[type='time', seriesType='distance', originalSize=5, resolution='high', data=[0.0, 1.0, 2.0, 3.0, 4.0]]

您还应该看看 Google Dev Group并查阅此解决方案。