Java FasterXML JSON 库 : How to parse a nested JSON structure

Question

下面是一个 Java 程序，我正在尝试使用 org.fasterxml.jackson.core 和 jackson-databind 库以流方式测试 JSON 处理。

目标是学习如何处理JSON并捕获我想要的信息。目前，我想要完成的任务如下:
1)我在此处发布的 JSON 有大量数据。此 JSON 后面的 Java 程序是我处理此 JSON 的尝试，特别是捕获“part1/myAnalysis/matches”下的 "name": US SSN"元素。以及 "name": MasterCard 信用卡号"，这两个元素都属于“part1/myAnalysis/matches”的范围。 仅。

好吧，现在我的目标是:我只是希望我的程序能够编译并至少打印出我感兴趣的这两个元素(前面提到的那些)。

我的编译尝试产生了以下结果:

Unprocessed property: type
Unprocessed property: incidentTimestamp
Unprocessed property: numOfMatches
Unprocessed property: myReport
Unprocessed property: whatSetItOffEntry
Unprocessed property: seeRestrictedIds
Unprocessed property: status
Unprocessed property: timeStamps
Unprocessed property: count

<小时/>

因此，程序尝试处理的 JSON 如下所示。如果有人可以指出如何使这个程序编译然后打印出我想要的元素。这将是一个很棒的两步流程任务。

{
    "type": "ImportantIncidentInfo",
    "incidentTimestamp": "2014-05-15T10:09:27.989-05:00",
    "numOfMatches": 4,
    "myReport": {
        "docReports": {
            "part1/.": {
                "path": [
                    "unknown"
                ],
                "myAnalysis": {
                    "matches": [
                        {
                            "id": {
                                "major": 1,
                                "minor": 0
                            },
                            "name": "US SSN",
                            "position": 13,
                            "string": " 636-12-4567 "
                        },
                        {
                            "id": {
                                "major": 3,
                                "minor": 0
                            },
                            "name": "MasterCard Credit Card Number",
                            "position": 35,
                            "string": " 5424-1813-6924-3685 "
                        }
                    ]
                },
                "cleanedUpData": [
                    {
                        "startPosition": 0,
                        "endPosition": 65,
                        "frameContent": ""
                    }
                ],
                "minedMetadata": {
                    "Content-Encoding": "ISO-8859-1",
                    "Content-Type": "text/html; charset=iso-8859-1"
                },
                "deducedMetadata": {
                    "Content-Type": "text/html; iso-8859-1"
                }
            },
            "part2/.": {
                "path": [
                    "unknown"
                ],
                "patternAnalysis": {
                    "matches": [
                        {
                            "id": {
                                "major": 1,
                                "minor": 0
                            },
                            "name": "SSN",
                            "position": 3,
                            "string": " 636-12-4567\r"
                        },
                        {
                            "id": {
                                "major": 3,
                                "minor": 0
                            },
                            "name": "MasterCard Credit Card Number",
                            "position": 18,
                            "string": "\n5424-1813-6924-3685\r"
                        }
                    ]
                },
                "cleanedUpData": [
                    {
                        "startPosition": 0,
                        "endPosition": 44,
                        "frameContent": ""
                    }
                ],
                "minedMetadata": {
                    "Content-Encoding": "windows-1252",
                    "Content-Type": "text/plain; charset=windows-1252"
                },
                "deducedMetadata": {
                    "Content-Type": "text/plain; iso-8859-1"
                }
            }
        }
    },
    "whatSetItOffEntry": {
        "action": "Log",
        "component": {
            "type": "aComponent",
            "components": [
                {
                    "type": "PatternComponent",
                    "patterns": [
                        1
                    ],
                    "not": false
                }
            ],
            "not": false
        },
        "ticketInfo": {
            "createIncident": true,
            "tags": [],
            "seeRestrictedIds": [
                {
                    "type": "userGroup",
                    "name": "SiteMasters",
                    "description": "Group for SiteMasters",
                    "masters": [
                        "04fb02a2bc0fba"
                    ],
                    "members": [],
                    "id": "04fade"
                }
            ]
        },
        "letmeknowInfo": {
            "createNotification": true,
            "contactNames": [
                "someguy@gmail.com"
            ]
        }
    },
    "seeRestrictedIds": [
        "04fade66c0"
    ],
    "status": "New",
    "timeStamps": [
        "2014-03-15T10:09:27.989-05:00"
    ],
    "count": 1
}

任务#2
2)为了处理这个JSON，我编写了以下Java程序。

import com.fasterxml.jackson.databind.*;
import com.fasterxml.jackson.core.*;

import java.io.*;

public class ParseJson {

    public static void main(String[] args) {

        try{

                // TODO Auto-generated method stub
                JsonFactory f = new MappingJsonFactory();
                //JsonParser jp = f.createJsonParser(new File(args[0]));
                JsonParser jp = f.createParser(new File("C:/somepath /in/my/eclipse/project/jsonFormattedModified.json"));


                JsonToken current;

                current = jp.nextToken();
                if (current != JsonToken.START_OBJECT) {
                  System.out.println("Error: root should be object: quiting.");
                  return;
                }

                while (jp.nextToken() != JsonToken.END_OBJECT) {
                  String fieldName = jp.getCurrentName();
                  // move from field name to field value
                  current = jp.nextToken();
                  if (fieldName.equals("matches")) {
                    if (current == JsonToken.START_ARRAY) {
                      // For each of the records in the array
                      while (jp.nextToken() != JsonToken.END_ARRAY) {
                        // read the record into a tree model,
                        // this moves the parsing position to the end of it
                        JsonNode node = jp.readValueAsTree();
                        // And now we have random access to everything in the object
                        System.out.println("Name: " + node.get("name").asText());
                        System.out.println("POS: " + node.get("pos").asText());
                      }
                    } else {
                      System.out.println("Error: records should be an array: skipping.");
                      jp.skipChildren();
                    }
                  } else {
                    System.out.println("Unprocessed property: " + fieldName);
                    jp.skipChildren();
                  }
                }                
              } catch(IOException ie) {
                  ie.printStackTrace();

              } 

        }
}

<小时/>

感谢您的帮助。

Answer 1

我建议您使用非常有用的 Google API Gson轻松处理序列化和反序列化。因此，首先，创建以下所有与您的 json 结构匹配的类。

帮助类:

class Helper {
    String type;
    String incidentTimestamp;
    int numOfMatches;
    Report myReport;
    WhatSetItOffEntry whatSetItOffEntry;
    List<String> seeRestrictedIds;
    String status;
    List<String> timeStamps;
    int count;
    //getters and setters
}

报告类别:

class Report {
    DocsReport docReports;
    //getters and setters
}

DocsReport 类:

class DocsReport {
    @SerializedName("part1/.")
    Part1 part1;
    Part2 part2;
    //getters and setters
}

第 1 部分类(class):

class Part1 {
    List<String> path;
    Analysis myAnalysis;
    List<CleanedUpData> cleanedUpData;
    MinedMetadata minedMetadata;
    DeducedMetadata deducedMetadata;
    //getters and setters
}

分析类:

class Analysis {
    List<Information> matches;
    //getters and setters
}

信息类:

class Information {
    Identifying id;
    String name;
    int position;
    String string;
    //getters and setters
}

识别类别:

class Identifying {
    int major;
    int minor;
    //getters and setters
}

CleanedUpData 类:

class CleanedUpData {
    int startPosition;
    int endPosition;
    String frameContent;
    //getters and setters
}

MinedMetadata 类:

class MinedMetadata {
    @SerializedName("Content-Encoding")
    String contentEncoding;
    @SerializedName("Content-Type")
    String contentType;
    //getters and setters
}

推导元数据类:

class DeducedMetadata {
    @SerializedName("Content-Type")
    String contentType;
    //getters and setters
}

第 2 部分类(class):

class Part2 {
    List<String> path;
    Analysis patternAnalysis;
    CleanedUpData cleanedUpData;
    MinedMetadata minedMetadata;
    DeducedMetadata deducedMetadata;
    //getters and setters
}

WhatSetItOffEntry 类:

class WhatSetItOffEntry {
    String action;
    Component component;
    TicketInfo ticketInfo;
    LetmeknowInfo letmeknowInfo;
    //getters and setters
}

组件类:

class Component {
    String type;
    List<ComponentData> components;
    Boolean not;
    //getters and setters
}

ComponentData 类:

class ComponentData {
    String type;
    List<Integer> patterns;
    Boolean not;
    //getters and setters
}

TicketInfo 类:

class TicketInfo {
    Boolean createIncident;
    List<Object> tags;
    List<RestrictedIds> seeRestrictedIds;
    //getters and setters
}

RestrictedIds 类:

class RestrictedIds {
    String type;
    String name;
    String description;
    List<String> masters;
    List<Object> members;
    String id;
    //getters and setters
}

LetmeknowInfo 类:

class LetmeknowInfo {
    Boolean createNotification;
    List<String> contactNames;
    //getters and setters
}

然后按如下方式获取您的两个名字

Gson gson = new Gson();
Helper data = gson
        .fromJson(
               new BufferedReader(
                        new FileReader(
                                "C:/somepath/in/my/eclipse/project/jsonFormattedModified.json")),
                new TypeToken<Helper>() {
                }.getType());

String name1 = data.getMyReport().getDocReports().getPart1()
        .getMyAnalysis().getMatches().get(0).getName();
String name2 = data.getMyReport().getDocReports().getPart1()
        .getMyAnalysis().getMatches().get(1).getName();

System.out.println(name1+"\n"+name2);

输出:

US SSN
MasterCard Credit Card Number