如何在MongoDB中获取摘要报告

我有以下结构的文档

示例文档：

   {
        "location" : {
            "street" : {
                "number" : 9360,
                "name" : "Travessa dos Açorianos"
            },
            "coordinates" : {
                "latitude" : -69.3199,
                "longitude" : 154.0748
            },
            "timezone" : {
                "offset" : "-8:00",
                "description" : "Pacific Time (US & Canada)"
            },
            "city" : "Divinópolis",
            "state" : "Espírito Santo",
            "country" : "Brazil",
            "postcode" : "23089"
        },
        "gender" : "male",
        "login" : {
            "uuid" : "b932ef44-2afb-4b72-a1c5-47b2263bbab2",
            "username" : "goldenfish516",
            "password" : "sharks",
            "salt" : "O7UQElyh",
            "md5" : "9f217bf6d5d8576703dbd38e864f709f",
            "sha1" : "22a4dbba7eea9b47537ed9931b907ceae10f4de7",
            "sha256" : "2bcf93087fcd2ecc623702ad5727e5a24f33ee343c1871028a7950e770c53ee4"
        },
        "dob" : {
            "date" : ISODate("1983-09-10T18:56:41.614Z"),
            "age" : 37   // get report from  based on age of male and female using nat field
        },
        "registered" : {
            "date" : ISODate("2005-04-10T08:57:39.425Z"),
            "age" : 15
        },

        "nat" : "NL",
     }

我想生成总结报告，如何使用mongo获得基于年龄和国籍的男性和女性

所需输出：

   {
        "location" : {
            "street" : {
                "number" : 9360,
                "name" : "Travessa dos Açorianos"
            },
            "coordinates" : {
                "latitude" : -69.3199,
                "longitude" : 154.0748
            },
            "timezone" : {
                "offset" : "-8:00",
                "description" : "Pacific Time (US & Canada)"
            },
            "city" : "Divinópolis",
            "state" : "Espírito Santo",
            "country" : "Brazil",
            "postcode" : "23089"
        },
        "gender" : "male",
        "login" : {
            "uuid" : "b932ef44-2afb-4b72-a1c5-47b2263bbab2",
            "username" : "goldenfish516",
            "password" : "sharks",
            "salt" : "O7UQElyh",
            "md5" : "9f217bf6d5d8576703dbd38e864f709f",
            "sha1" : "22a4dbba7eea9b47537ed9931b907ceae10f4de7",
            "sha256" : "2bcf93087fcd2ecc623702ad5727e5a24f33ee343c1871028a7950e770c53ee4"
        },
        "dob" : {
            "date" : ISODate("1983-09-10T18:56:41.614Z"),
            "age" : 37   // get report from  based on age of male and female using nat field
        },
        "registered" : {
            "date" : ISODate("2005-04-10T08:57:39.425Z"),
            "age" : 15
        },

        "nat" : "NL",
     }

---

您可以尝试以下聚合查询：

db.collection.aggregate([
  /** Group on 'nat' field & sum no.of doc's based on age to specific category using conditional check */
  {
    $group: {
      _id: "$nat",
      "0-30": {
        $sum: {
          $cond: [
            { $and: [{ $gte: ["$dob.age", 0] }, { $lt: ["$dob.age", 30] }] },
            1,
            0
          ]
        }
      },
      "30-50": {
        $sum: {
          $cond: [
            { $and: [{ $gte: ["$dob.age", 30] }, { $lt: ["$dob.age", 50] }] },
            1,
            0
          ]
        }
      },
      "50plus": { $sum: { $cond: [{ $gte: ["$dob.age", 50] }, 1, 0] } }
    }
  },
  /** Group on nationality & push male & female objects into respective arrays */
  {
    $group: {
      _id: "$_id.nationality",
      male: {
        $push: {
          $cond: [
            { $eq: ["$_id.gender", "male"] },
            {
              "0-30": "$$ROOT.0-30",
              "30-50": "$$ROOT.30-50",
              "50plus": "$$ROOT.50plus"
            },
            "$$REMOVE"
          ]
        }
      },
      female: {
        $push: {
          $cond: [
            { $eq: ["$_id.gender", "female"] },
            {
              "0-30": "$$ROOT.0-30",
              "30-50": "$$ROOT.30-50",
              "50plus": "$$ROOT.50plus"
            },
            "$$REMOVE"
          ]
        }
      }
    }
  },
  {
    $project: {
      _id: 0,
      nationality: "$_id",
      female: { $arrayElemAt: ["$female", 0] }, // Get object from array
      male: { $arrayElemAt: ["$male", 0] }
    }
  }
]);

---

测试：

您可以尝试以下聚合查询：

db.collection.aggregate([
  /** Group on 'nat' field & sum no.of doc's based on age to specific category using conditional check */
  {
    $group: {
      _id: "$nat",
      "0-30": {
        $sum: {
          $cond: [
            { $and: [{ $gte: ["$dob.age", 0] }, { $lt: ["$dob.age", 30] }] },
            1,
            0
          ]
        }
      },
      "30-50": {
        $sum: {
          $cond: [
            { $and: [{ $gte: ["$dob.age", 30] }, { $lt: ["$dob.age", 50] }] },
            1,
            0
          ]
        }
      },
      "50plus": { $sum: { $cond: [{ $gte: ["$dob.age", 50] }, 1, 0] } }
    }
  },
  /** Group on nationality & push male & female objects into respective arrays */
  {
    $group: {
      _id: "$_id.nationality",
      male: {
        $push: {
          $cond: [
            { $eq: ["$_id.gender", "male"] },
            {
              "0-30": "$$ROOT.0-30",
              "30-50": "$$ROOT.30-50",
              "50plus": "$$ROOT.50plus"
            },
            "$$REMOVE"
          ]
        }
      },
      female: {
        $push: {
          $cond: [
            { $eq: ["$_id.gender", "female"] },
            {
              "0-30": "$$ROOT.0-30",
              "30-50": "$$ROOT.30-50",
              "50plus": "$$ROOT.50plus"
            },
            "$$REMOVE"
          ]
        }
      }
    }
  },
  {
    $project: {
      _id: 0,
      nationality: "$_id",
      female: { $arrayElemAt: ["$female", 0] }, // Get object from array
      male: { $arrayElemAt: ["$male", 0] }
    }
  }
]);

测试：