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$min - Amazon DocumentDB
範例 (MongoDB Shell)視窗運算子用量範例 (MongoDB Shell)程式碼範例

本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

$min

$min 彙總運算子會傳回一組文件中指定欄位的最小值。此運算子有助於尋找一組文件中的最低值。

參數

  • expression：要評估的表達式。這可以是欄位路徑、變數或任何解析為值的表達式。

範例 (MongoDB Shell)

下列範例示範 $min運算子的使用情況，以尋找跨多個文件之 age 欄位的最小值。

建立範例文件

db.users.insertMany([
  { name: "John", age: 35 },
  { name: "Jane", age: 28 },
  { name: "Bob", age: 42 },
  { name: "Alice", age: 31 }
]);

查詢範例

db.users.aggregate([
  { $group: { _id: null, minAge: { $min: "$age" } } },
  { $project: { _id: 0, minAge: 1 } }
])

輸出

[ { minAge: 28 } ]

視窗運算子用量範例 (MongoDB Shell)

8.0.2 版的新功能。

該$min運算子也可以用作$setWindowFields階段中的視窗運算子。在這種情況下，它會傳回每個視窗中文件的最小值。您可以在 output 欄位下指定運算子，並選擇性地使用window文件定義視窗邊界。

注意

在 中用作視窗運算子時$setWindowFields， 限制$min為 100 MB 的中繼資料。超過此限制的操作會傳回錯誤。

建立範例文件

db.stockPrices.insertMany([
  { _id: 1, ticker: "ABC", hour: 1, price: 50 },
  { _id: 2, ticker: "ABC", hour: 2, price: 45 },
  { _id: 3, ticker: "ABC", hour: 3, price: 60 },
  { _id: 4, ticker: "ABC", hour: 4, price: 40 },
  { _id: 5, ticker: "XYZ", hour: 1, price: 30 },
  { _id: 6, ticker: "XYZ", hour: 2, price: 35 },
  { _id: 7, ticker: "XYZ", hour: 3, price: 25 }
]);

查詢範例

下列範例會依 分割文件ticker、依 排序每個分割區hour，並傳回從分割區開始到目前文件的最低價格。

db.stockPrices.aggregate([
  {
    $setWindowFields: {
      partitionBy: "$ticker",
      sortBy: { hour: 1 },
      output: {
        lowestSoFar: {
          $min: "$price",
          window: { documents: ["unbounded", "current"] }
        }
      }
    }
  }
]);

輸出

[
  { "_id": 1, "ticker": "ABC", "hour": 1, "price": 50, "lowestSoFar": 50 },
  { "_id": 2, "ticker": "ABC", "hour": 2, "price": 45, "lowestSoFar": 45 },
  { "_id": 3, "ticker": "ABC", "hour": 3, "price": 60, "lowestSoFar": 45 },
  { "_id": 4, "ticker": "ABC", "hour": 4, "price": 40, "lowestSoFar": 40 },
  { "_id": 5, "ticker": "XYZ", "hour": 1, "price": 30, "lowestSoFar": 30 },
  { "_id": 6, "ticker": "XYZ", "hour": 2, "price": 35, "lowestSoFar": 30 },
  { "_id": 7, "ticker": "XYZ", "hour": 3, "price": 25, "lowestSoFar": 25 }
]

每個文件都會使用 擴增lowestSoFar，其分割區price內執行的最小值為 ，直到並包含目前的文件。

程式碼範例

若要檢視使用 $min 運算子的程式碼範例，請選擇您要使用的語言標籤。下列範例顯示累積器用量 （在 中$group) 和視窗運算子用量 （在 中$setWindowFields)：

Node.js
const { MongoClient } = require('mongodb');

async function example() {
  const client = await MongoClient.connect('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false');
  const db = client.db('test');

  // Accumulator usage: minimum value across a group
  const users = db.collection('users');
  await users.insertMany([
    { name: "John", age: 35 },
    { name: "Jane", age: 28 },
    { name: "Bob", age: 42 },
    { name: "Alice", age: 31 }
  ]);
  const accumulatorResult = await users.aggregate([
    { $group: { _id: null, minAge: { $min: "$age" } } }
  ]).toArray();
  console.log('Accumulator result:', accumulatorResult);

  // Window operator usage: running minimum within each partition
  const stockPrices = db.collection('stockPrices');
  await stockPrices.insertMany([
    { _id: 1, ticker: "ABC", hour: 1, price: 50 },
    { _id: 2, ticker: "ABC", hour: 2, price: 45 },
    { _id: 3, ticker: "ABC", hour: 3, price: 60 },
    { _id: 4, ticker: "ABC", hour: 4, price: 40 },
    { _id: 5, ticker: "XYZ", hour: 1, price: 30 },
    { _id: 6, ticker: "XYZ", hour: 2, price: 35 },
    { _id: 7, ticker: "XYZ", hour: 3, price: 25 }
  ]);
  const windowResult = await stockPrices.aggregate([
    {
      $setWindowFields: {
        partitionBy: "$ticker",
        sortBy: { hour: 1 },
        output: {
          lowestSoFar: {
            $min: "$price",
            window: { documents: ["unbounded", "current"] }
          }
        }
      }
    }
  ]).toArray();
  console.log('Window result:', windowResult);

  client.close();
}

example();
Python
from pymongo import MongoClient

def example():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client['test']

    # Accumulator usage: minimum value across a group
    users = db.users
    users.insert_many([
        { "name": "John", "age": 35 },
        { "name": "Jane", "age": 28 },
        { "name": "Bob", "age": 42 },
        { "name": "Alice", "age": 31 }
    ])
    accumulator_result = list(users.aggregate([
        { "$group": { "_id": None, "minAge": { "$min": "$age" } } }
    ]))
    print('Accumulator result:', accumulator_result)

    # Window operator usage: running minimum within each partition
    stock_prices = db.stockPrices
    stock_prices.insert_many([
        { "_id": 1, "ticker": "ABC", "hour": 1, "price": 50 },
        { "_id": 2, "ticker": "ABC", "hour": 2, "price": 45 },
        { "_id": 3, "ticker": "ABC", "hour": 3, "price": 60 },
        { "_id": 4, "ticker": "ABC", "hour": 4, "price": 40 },
        { "_id": 5, "ticker": "XYZ", "hour": 1, "price": 30 },
        { "_id": 6, "ticker": "XYZ", "hour": 2, "price": 35 },
        { "_id": 7, "ticker": "XYZ", "hour": 3, "price": 25 }
    ])
    window_result = list(stock_prices.aggregate([
        {
            "$setWindowFields": {
                "partitionBy": "$ticker",
                "sortBy": { "hour": 1 },
                "output": {
                    "lowestSoFar": {
                        "$min": "$price",
                        "window": { "documents": ["unbounded", "current"] }
                    }
                }
            }
        }
    ]))
    print('Window result:', window_result)

    client.close()

example()