ทดลองเขียน Aggregation ใน MongoDB

db.COLLECTION_NAME.aggregate(AGGREGATE_OPERATION)

mongoimport --db ahoy_aggregate_example --collection zipcodes --drop --file /path/to/file/zips.json

2016-06-25T20:45:47.637+0700  connected to: localhost
2016-06-25T20:45:47.637+0700  dropping: ahoy_aggregate_example.zipcodes
2016-06-25T20:45:48.194+0700  imported 29353 documents

mongo
> show dbs
ahoy_aggregate_example     0.078GB

> use ahoy_aggregate_example
switched to db ahoy_aggregate_example

> db.zipcodes.find().count()
29353

> db.zipcodes.findOne()
{
  "_id" : "01001",
  "city" : "AGAWAM",
  "loc" : [
    -72.622739,
    42.070206
  ],
  "pop" : 15338,
  "state" : "MA"
}

'use strict'

const mongoose = require('mongoose')
const Schema = mongoose.Schema

let Zipcodes = new Schema({
  _id: {
    type: String,
    unique: true,
    index: true
  },
  city: String,
  loc: {
    type: [Number],
    index: '2d'
  },
  pop: Number,
  state: String
})

module.exports = mongoose.model('Zipcodes', Zipcodes)

db.zipcodes.aggregate([
  {
    $match: { state: 'NY' }
  }
])

db.zipcodes.aggregate([
  {
    $match: { pop: {$gte: 100000} }
  }
])

[
  {
    "_id": "10025",
    "city": "NEW YORK",
    "loc": [-73.9683119999999974, 40.797466],
    "pop": 100027,
    "state": "NY"
  },
  {
    "_id": "10021",
    "city": "NEW YORK",
    "loc": [-73.9588049999999981, 40.7684759999999997],
    "pop": 106564,
    "state": "NY"
  },
  {
    "_id": "11226",
    "city": "BROOKLYN",
    "loc": [-73.9569850000000031, 40.6466939999999965],
    "pop": 111396,
    "state": "NY"
  },
  {
    "_id": "60623",
    "city": "CHICAGO",
    "loc": [-87.7156999999999982, 41.8490150000000014],
    "pop": 112047,
    "state": "IL"
  }
]

db.zipcodes.aggregate([
  {
    $project: { _id: 0, city: 1, pop: 1 }
  }
])

[
    {
        "city" : "AGAWAM",
        "pop" : 15338
    },
    {
        "city" : "BLANDFORD",
        "pop" : 1240
    },
    {
        "city" : "BELCHERTOWN",
        "pop" : 10579
    },
    {
        "city" : "CUSHMAN",
        "pop" : 36963
    },
    ...
]

db.zipcodes.aggregate([
  {
    $project: {
      info: {
        state: "$state",
        city: "$city"
      }
    }
  }
])

[
  {
    "_id": "01001",
    "info": {
      "state": "MA",
      "city": "AGAWAM"
    }
  },
  {
    "_id": "01008",
    "info": {
      "state": "MA",
      "city": "BLANDFORD"
    }
  },
  {
    "_id": "01007",
    "info": {
      "state": "MA",
      "city": "BELCHERTOWN"
    }
  }
]

db.zipcodes.aggregate([
  {
    $group: {
      _id: "$state",
      totalPop: { $sum: "$pop"}
    }
  }
])

[
    {
        "_id" : "NV",
        "totalPop" : 1.20183e+06
    },
    {
        "_id" : "ID",
        "totalPop" : 1.00675e+06
    },
    {
        "_id" : "CO",
        "totalPop" : 3.29376e+06
    },
    ...
]

db.zipcodes.aggregate([
  {
    $group: {
      _id: "$state",
      totalCities: { $sum: 1}
    }
  }
])

[
    {
        "_id" : "NV",
        "totalCities" : 104.0000000000000000
    },
    {
        "_id" : "ID",
        "totalCities" : 244.0000000000000000
    },
    {
        "_id" : "CO",
        "totalCities" : 414.0000000000000000
    },
    ...
]

db.zipcodes.aggregate([
  {
    $group: {
      _id: "$state",
      cities: { $addToSet: "$city"}
    }
  }
])

[
    {
        "_id" : "NV",
        "cities" : [
            "BEOWAWE",
            "OASIS",
            "MOUNTAIN CITY",
            ...
        ]
    },
    {...},
    {...}
]

db.zipcodes.aggregate([
  {
    $group: {
      _id: "$state",
      totalCities: { $sum: 1}
    }
  },
  {
    $sort: {
      totalCities: 1
    }
  }
])

[
    {
        "_id" : "DC",
        "totalCities" : 24.0000000000000000
    },
    {
        "_id" : "DE",
        "totalCities" : 53.0000000000000000
    },
    {
        "_id" : "RI",
        "totalCities" : 69.0000000000000000
    },
    {
        "_id" : "HI",
        "totalCities" : 80.0000000000000000
    },
    {
        "_id" : "NV",
        "totalCities" : 104.0000000000000000
    },
    ...
]