无法识别的表达式＆＃x27; $ getfield＆＃x27;

Question

我正在尝试使用对象中的值添加新字段：

db.requests.aggregate([
  {
    "$match": {
      "$and": [
        {
          tag: "prod",
          status: "OK",
          created_at: {
            $gte: ISODate("2021-01-01"),
            $lt: ISODate("2022-01-01")
          }
        },
        
      ]
    }
  },
  {
    "$addFields": { "fields": {"$objectToArray": "$fields"} }
  },
  {
    "$unwind": "$fields"
  },
  {
    "$addFields": { "fname": {"$getField": { "field": "k", "input": "$fields" }}, <---- HERE
                    "fconf": {"$getField": { "field": "confidence", "input": {"$getField": { "field": "v", "input": "$fields" }}}}
    }
  },
  {
    $group: {
      _id: "$document",
      "fname": {"$sum": {
        "$cond": {
          "if": {"$gte": [ "$fconf", 0.99 ]},
          "then": 1,
          "else": 0 }
      }},
    }
  }
])

但出现错误：

"ok" : 0,
"errmsg" : "Invalid $addFields :: caused by :: Unrecognized expression '$getField'",
"code" : 168,
"codeName" : "InvalidPipelineOperator"

我的 mongo 版本是 5.0.4，$getField 是在 5.0.0 中引入的，那么出了什么问题？

更新： 样本数据

{ "_id" : ObjectId("610bcecea7f31aaa40b08186"), "tag" : "prod", "document" : "RUT", "fields" : { "9-1-1-1" : { "text" : "1018462101", "confidence" : 1 }, "9-1-1-2" : { "text" : "32", "confidence" : 1 }, "9-1-1-3" : { "text" : "*******", "confidence" : 0.99 }, "9-1-1-4" : { "text" : "*******", "confidence" : 0.99 }, "9-1-1-5" : { "text" : "*******", "confidence" : 0.99 }, "9-1-1-6" : { "text" : "CATALINA", "confidence" : 0.99 }, "9-1-1-7" : { "text" : "8299", "confidence" : 1 } }, "status" : "OK", "created_at" : ISODate("2021-08-05T11:43:10.110Z") }
{ "_id" : ObjectId("610bced6a7f31aaa40b08187"), "tag" : "prod", "document" : "FNA", "fields" : { "20-20-4-4-1-1-1-1-2-1" : { "text" : "", "confidence" : 0 }, "20-20-4-4-1-1-1-1-3-1" : { "text" : "", "confidence" : 0 }, "20-20-4-4-1-1-1-1-4-1" : { "text" : "", "confidence" : 0 }, "20-20-4-4-1-1-1-1-5-1" : { "text" : "", "confidence" : 0 } }, "status" : "OK", "created_at" : ISODate("2021-08-05T11:43:18.706Z") }
{ "_id" : ObjectId("610bcef70b1451dacf81bf32"), "tag" : "prod", "document" : "TAX", "fields" : { "20-19-5-1-2-1-1-1-2-1" : { "text" : "6729000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-3-1" : { "text" : "7443000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-4-1" : { "text" : "54895000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-5-1" : { "text" : "16582000", "confidence" : 0.99 }, "20-19-5-1-2-1-1-1-6-1" : { "text" : "16582000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-7-1" : { "text" : "36083000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-8-1" : { "text" : "2000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-9-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-10-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-11-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-12-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-13-1" : { "text" : "2000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-14-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-15-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-16-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-17-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-18-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-19-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-20-1" : { "text" : "52667000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-21-1" : { "text" : "16582000", "confidence" : 1 }, "20-19-5-1-2-1-1-1-22-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-23-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-24-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-25-1" : { "text" : "36085000", "confidence" : 0.99 }, "20-19-5-1-2-1-1-1-26-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-27-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-28-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-29-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-30-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-31-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-32-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-33-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-34-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-35-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-36-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-37-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-38-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-39-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-40-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-41-1" : { "text" : "0", "confidence" : 1 }, "20-19-5-1-2-1-1-1-42-1" : { "text" : "0", "confidence" : 0.7 }, "20-19-5-1-2-1-1-1-43-1" : { "text" : "0", "confidence" : 1 } }, "status" : "OK", "created_at" : ISODate("2021-08-05T11:43:51.466Z") }

预期结果： 我需要像 {_id: "RUT", fields: {9-1-1-1: 10, 9-1-1-2: 5}} 因此，我需要聚合所有内容，并按置信度大于 0.99 的每个字段的名称进行计数。可以有许多文档，每个文档都有不同的字段集，我需要首先按 document 对它们进行分组，然后按照我上面描述的过程在这种类型的许多文档之间进行计数

Answer 1

在前三个步骤之后，我们可以在 $group 之前使用 $match 这使事情变得更简单，并将 $addFields 步骤移到它后面（此处为 $project）。然后只需再次 $group 和 $project 即可获得想要的结果：

    db.collection.aggregate([
  {
    "$match": {
      "$and": [
        {
          tag: "prod",
          status: "OK",
          created_at: {
            $gte: ISODate("2021-01-01"),
            $lt: ISODate("2022-01-01")
          }
        },
        
      ]
    }
  },
  {
    "$addFields": {"fields": {"$objectToArray": "$fields"}}
  },
  {
    "$unwind": "$fields"
  },
  {
    $match: {"fields.v.confidence": {$gte: 0.99}}
  },
  {
    $group: {
      _id: {
        doc: "$document",
        fname: "$fields.k"
      },
      "dataK": {
        $first: "$fields.k"
      },
      "dataV": {
        $sum: 1
      }
    }
  },
  {
    $project: {"data.k": "$dataK", "data.v": "$dataV"}
  },
  {
    $group: {
      _id: "$_id.doc",
      fields: {$push: "$data"}
    }
  },
  {
    $project: {"fields": {"$arrayToObject": "$fields"}}
  }
])

可以看到 这里在操场上，有一个额外的文档，演示了字段的计数。