对于您的情况，您可以直接将csv反序列化为JsonNode，而无需创建POJO类。然后使用JSON库 Josson 通过函数group()转换JSON。

String csv = "user_id,nickname,joinDate,product_id,price\n" +
        "1,kmh,2023-07-24,P131,3000\n" +
        "1,kmh,2023-07-24,P132,4000\n" +
        "1,kmh,2023-07-24,P133,7000\n" +
        "1,kmh,2023-07-24,P134,9000\n" +
        "2,john,2023-07-24,P135,2500\n" +
        "2,john,2023-07-24,P136,6000\n" +
        "3,alice,2023-07-25,P137,4500\n" +
        "3,alice,2023-07-25,P138,8000";
ArrayNode arrayNode = Josson.createArrayNode();
CsvSchema schema = CsvSchema.emptySchema().withHeader();
try (MappingIterator<JsonNode> it = new CsvMapper().readerFor(JsonNode.class).with(schema).readValues(csv)) {
    arrayNode.addAll(it.readAll());
}
Josson josson = Josson.create(arrayNode);
JsonNode grouped = josson.getNode(
        "group(map(user_id, nickname, joinDate), map(product_id, price))" +
        ".map(**:key, orders:elements)");
System.out.println(grouped.toPrettyString());

字符串

函数group()

1.按{user_id，nickname，joinDate}的“key”分组
1.具有{product_id，price}的“元素”

函数map()

1.提取对象“key”内部的值
1.添加从“元素”复制的字段“订单”

输出

[ {
  "user_id" : "1",
  "nickname" : "kmh",
  "joinDate" : "2023-07-24",
  "orders" : [ {
    "product_id" : "P131",
    "price" : "3000"
  }, {
    "product_id" : "P132",
    "price" : "4000"
  }, {
    "product_id" : "P133",
    "price" : "7000"
  }, {
    "product_id" : "P134",
    "price" : "9000"
  } ]
}, {
  "user_id" : "2",
  "nickname" : "john",
  "joinDate" : "2023-07-24",
  "orders" : [ {
    "product_id" : "P135",
    "price" : "2500"
  }, {
    "product_id" : "P136",
    "price" : "6000"
  } ]
}, {
  "user_id" : "3",
  "nickname" : "alice",
  "joinDate" : "2023-07-25",
  "orders" : [ {
    "product_id" : "P137",
    "price" : "4500"
  }, {
    "product_id" : "P138",
    "price" : "8000"
  } ]
} ]

型

您所需要的只是一种将CSV解析为Java对象的方法。您可以手动执行此操作，也可以使用现有库。
例如，您可以将Jackson与CSV数据格式一起使用，如下所示：

class MyRecord {

    @JsonProperty("user_id")
    private int userId;
    
    private String nickname;
    
    private LocalDate joinDate;

    @JsonProperty("product_id")
    private String productId;

    // getters and setters

    // a meaningful toString method

}

public class Main {

    public static void main(String[] args) throws IOException {
        String csv = "user_id,nickname,joinDate,product_id,price\n" +
                "1,kmh,2023-07-24,P131,3000\n" +
                "1,kmh,2023-07-24,P132,4000\n" +
                "1,kmh,2023-07-24,P133,7000\n" +
                "1,kmh,2023-07-24,P134,9000\n" +
                "2,john,2023-07-24,P135,2500\n" +
                "2,john,2023-07-24,P136,6000\n" +
                "3,alice,2023-07-25,P137,4500\n" +
                "3,alice,2023-07-25,P138,8000";

        CsvSchema schema = CsvSchema.emptySchema().withHeader(); // uses CSV header to read the schema
        ObjectMapper mapper = new CsvMapper().registerModule(new JavaTimeModule()); // to deserialise Java 8 LocalDate
        MappingIterator<MyRecord> resultIterator = mapper.readerFor(MyRecord.class).with(schema).readValues(csv);
        while (resultIterator.hasNext()) {
            System.out.println(resultIterator.next());
        }
        resultIterator.close();
    }
}

字符串
哪些打印：

MyRecord[userId=1, nickname='kmh', joinDate=2023-07-24, productId='P131', price=3000]
MyRecord[userId=1, nickname='kmh', joinDate=2023-07-24, productId='P132', price=4000]
MyRecord[userId=1, nickname='kmh', joinDate=2023-07-24, productId='P133', price=7000]
MyRecord[userId=1, nickname='kmh', joinDate=2023-07-24, productId='P134', price=9000]
MyRecord[userId=2, nickname='john', joinDate=2023-07-24, productId='P135', price=2500]
MyRecord[userId=2, nickname='john', joinDate=2023-07-24, productId='P136', price=6000]
MyRecord[userId=3, nickname='alice', joinDate=2023-07-25, productId='P137', price=4500]
MyRecord[userId=3, nickname='alice', joinDate=2023-07-25, productId='P138', price=8000]

型