如何通过_id匹配categories与count数组并合并为含name和count的对象

我有两个数组categories和count，均包含_id字段。需求是根据_id匹配两个数组中的对象，合并为仅包含name和count的新对象，同时排除_id为null的项。尝试用map方法实现但结果不符合预期，相关数据及代码如下：

原始数据 #

{
  "count": [
    {
      "_id": "63d18ade150a09494a7922ba",
      "count": 1
    },
    {
      "_id": "63d18ab8150a09494a792298",
      "count": 1
    },
    {
      "_id": null,
      "count": 1
    },
    {
      "_id": "63d18ab8150a09494a79229a",
      "count": 2
    },
    {
      "_id": "63d18ab8150a09494a792299",
      "count": 2
    }
  ],
  "categories": [
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a792298",
      "name": "Agriculter & Food",
      "enabled": false,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a792299",
      "name": "Animals & Pets",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a79229a",
      "name": "Babies & Kids",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a79229b",
      "name": "Commercial & Equipment & Tools",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a79229e",
      "name": "Health & Beauty",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a79229f",
      "name": "Home, Furniture & Appliances",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a0",
      "name": "Jobs",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a1",
      "name": "Mobile Phones & Tablets",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a2",
      "name": "Property",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a3",
      "name": "Repair & Construction",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a4",
      "name": "Services",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a5",
      "name": "Sports, Arts & Outdoors",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a7922a6",
      "name": "Vehicles",
      "enabled": true,
      "isDeleted": false,
      "__v": 0,
      "mobile_image": "imgName-1675366698075.png",
      "image": "imgName-1675367702205.png"
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a79229c",
      "name": "Electronics",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "image": "",
      "mobile_image": "",
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63d18ab8150a09494a79229d",
      "name": "Faishon",
      "enabled": true,
      "isDeleted": false,
      "__v": 0
    },
    {
      "createdDate": "2023-03-13T15:29:11.104Z",
      "_id": "63ed51eb047ccbe75d91a982",
      "name": "Example",
      "enabled": true,
      "isDeleted": false,
      "image": "",
      "mobile_image": "",
      "__v": 0
    }
  ]
}

尝试的代码 #

const result = categorycount.map(obj1 => {
  const matchingObj2 = categories.find(obj2 => obj2._id === obj1._id);
  if (matchingObj2) {
    return {
      matchingObj2                              
    };
  } else {
    return null;
  }
}).filter(obj => obj !== null);

问题分析与解决方案 #

原代码存在三个问题：

1. 未排除count数组中_id为null的项
2. 返回的对象结构错误，直接将匹配到的matchingObj2作为属性值，而非提取name与count合并
3. 未处理count中存在但categories里没有的_id（比如63d18ade150a09494a7922ba）

修正后的代码步骤：

1. 先过滤count数组，移除_id为null的项
2. 将categories转为Map提升查找效率（数组规模较大时效果更明显）
3. 遍历过滤后的count，匹配对应分类名称，生成仅包含name和count的新对象
4. 过滤掉无匹配分类的项

修正代码 #

// 构建分类ID到名称的映射表
const categoryMap = new Map(categories.map(cat => [cat._id, cat.name]));

const result = count
  // 过滤_id为null的无效项
  .filter(item => item._id !== null)
  .map(item => {
    const name = categoryMap.get(item._id);
    // 仅保留有匹配名称的项
    return name ? { name, count: item.count } : null;
  })
  // 移除无匹配的null项
  .filter(item => item !== null);

最终结果示例 #

result的输出内容为：

[
  { "name": "Agriculter & Food", "count": 1 },
  { "name": "Babies & Kids", "count": 2 },
  { "name": "Animals & Pets", "count": 2 }
]

内容的提问来源于stack exchange，提问作者Smitty's