Mongodb - 按文档状态查询和分组

Question

我有猫鼬模型 - 用户和工单

用户：

//Create schema
const userSchema = new Schema({
    title: String,
    f_name: {
        type: String,
        required: true
    },
    m_name: String,
    l_name: {
        type: String,
        required: true
    },
...
}

评论：

//Create schema
const commentSchema = new Schema({
    title: String,
    ticket_id: String,
    user: {
        type: Schema.Types.ObjectId,
        ref: 'User'
    },
    status: {
        type: String,
        enum: ['New', 'Open', 'Pending', 'Suspended', 'Solved']
    },
    ...
}

我必须根据状态获取用户列表以及 cmets 计数： 示例：

{
  'f_name': 'XYZ',
  ...,
  status_data: {
    [
      {
        'status': 'New',
        'count': 3
      },
      {
        'status': 'Solved',
        'count': 3
      },
      {
        'status': 'Suspended',
        'count': 3
      }
    ]
  }
}

目前我正在尝试：

User.aggregate([
        {
            $lookup: {
                from: 'tickettests',
                localField: '_id',
                foreignField: 'assigned_to',
                as: 'tickets_doc'
            }
        },
        {
            $unwind: {
                path: '$tickets_doc'
            }
        },
        {
            $group: {
                _id: {
                    _id: '$_id',
                    status: '$tickets_doc.status'
                },
                user_id: {$first: '$_id'},
                f_name: {$first: '$f_name'},
                l_name: {$first: '$l_name'},
                createdAt: {$first: '$createdAt'},
                updatedAt: {$first: '$updatedAt'},
                count: {
                    $sum: 1
                }
            }
        }
    ])
    .then(ticketPromisesRes => {
        res.status(200).json(ticketPromisesRes);
    })
    .catch(err => {
        logger.error(err);
        res.status(500).json({message: 'Cannot get contact list with tickets'})
    })

数据像往常一样聚合，有重复的用户，但它的状态和数量是唯一的，我试图让它像上面给出的响应一样，

目前的回应：

{
        "_id": {
            "_id": "xxxxx",
            "status": "New"
        },
        "user_id": "xxxxx",
        "f_name": "XYZ",
        "l_name": "ZXC",
        "createdAt": "2019-12-07T04:43:03.839Z",
        "updatedAt": "2019-12-07T04:45:59.322Z",
        "count": 2
    },
    {
        "_id": {
            "_id": "xxxxxx",
            "status": "Suspended"
        },
        "user_id": "xxxxxx",
        "f_name": "ASD",
        "l_name": "DSA",
        "createdAt": "2019-12-07T04:28:13.616Z",
        "updatedAt": "2019-12-07T04:37:03.737Z",
        "count": 1
    },
    {
        "_id": {
            "_id": "xxxxxxx",
            "status": "Suspended"
        },
        "user_id": "xxxxxxx",
        "f_name": "XYZ",
        "l_name": "ZXC",
        "createdAt": "2019-12-07T04:43:03.839Z",
        "updatedAt": "2019-12-07T04:45:59.322Z",
        "count": 1
    },

Answer 1

您可以使用以下 2 级组聚合。

Playground

db.users.aggregate([
  {
    $lookup: {
      from: "tickets",
      localField: "user_id",
      foreignField: "user",
      as: "tickets_doc"
    }
  },
  {
    $unwind: {
      path: "$tickets_doc"
    }
  },
  {
    $group: {
      _id: {
        user: "$user_id",
        ticket: "$tickets_doc.status"
      },
      user: {
        "$first": "$$ROOT"
      },
      statusTotal: {
        $sum: 1
      }
    }
  },
  {
    $group: {
      _id: {
        userId: "$_id.user",
        f_name: "$user.f_name",
        l_name: "$user.l_name"
      },
      status_data: {
        $push: {
          status: "$_id.ticket",
          count: "$statusTotal"
        }
      }
    }
  },
  {
    "$replaceRoot": {
      "newRoot": {
        $mergeObjects: [
          "$_id",
          {
            "status_data": "$status_data"
          }
        ]
      }
    }
  }
])

示例文件：

db={
  "users": [
    {
      "user_id": "user1",
      "f_name": "user1 firstname",
      "l_name": "user1 lastname"
    },
    {
      "user_id": "user2",
      "f_name": "user2 firstname",
      "l_name": "user2 lastname"
    }
  ],
  "tickets": [
    {
      "title": "comment1",
      "user": "user1",
      "status": "New"
    },
    {
      "title": "comment2",
      "user": "user1",
      "status": "New"
    },
    {
      "title": "comment3",
      "user": "user2",
      "status": "New"
    },
    {
      "title": "comment4",
      "user": "user1",
      "status": "Open"
    },
    {
      "title": "comment5",
      "user": "user2",
      "status": "Open"
    },
    {
      "title": "comment6",
      "user": "user2",
      "status": "Pending"
    },
    {
      "title": "comment7",
      "user": "user2",
      "status": "Pending"
    }
  ]
}

输出：

[
  {
    "f_name": "user2 firstname",
    "l_name": "user2 lastname",
    "status_data": [
      {
        "count": 2,
        "status": "Pending"
      },
      {
        "count": 1,
        "status": "Open"
      },
      {
        "count": 1,
        "status": "New"
      }
    ],
    "userId": "user2"
  },
  {
    "f_name": "user1 firstname",
    "l_name": "user1 lastname",
    "status_data": [
      {
        "count": 2,
        "status": "New"
      },
      {
        "count": 1,
        "status": "Open"
      }
    ],
    "userId": "user1"
  }
]

Answer 2

我认为您需要将 $lookup 与管道一起使用：

$lookup: {
  from: 'tickettest',
  let: { userId: '$_id' },
  pipeline: [{
    $match: {
      $expr: {
        $eq: ['$assignedTo', '$$userId']
      }
    },
    {
      $project: {
        status: 1,
      }
    },
    {
      $group: { 
        _id: '$status',
        count: {
          $sum: 1
        }
      }
    },
  }],
  as: 'status_data'
}