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$max - 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。

$max

$max 彙總運算子會傳回一組文件中指定欄位的最大值。此運算子適用於尋找一組文件中的最高值。

參數

  • expression：用來計算最大值的表達式。

範例 (MongoDB Shell)

下列範例示範如何使用 $max運算子在學生文件集合中尋找最高分數。$group 階段將所有文件分組在一起，而$max運算子用於計算所有文件中 score 欄位的最大值。

建立範例文件

db.students.insertMany([
  { name: "John", score: 85 },
  { name: "Jane", score: 92 },
  { name: "Bob", score: 78 },
  { name: "Alice", score: 90 }
])

查詢範例

db.students.aggregate([
  { $group: { _id: null, maxScore: { $max: "$score" } } },
  { $project: { _id: 0, maxScore: 1 } }
])

輸出

[ { maxScore: 92 } ]

視窗運算子用量範例 (MongoDB Shell)

8.0.2 版的新功能。

該$max運算子也可以用作$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大值。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$setWindowFields， 限制$max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，並傳回從分割區開頭到目前文件的最高價格。

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

輸出

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

每個文件都會以 擴增highestSoFar，其分割區price內執行的最大值為 ，最多可達並包含目前的文件。

程式碼範例

若要檢視使用 $max 運算子的程式碼範例，請選擇您要使用的語言標籤。下列範例顯示累積器用量 （在 中$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: maximum value across a group
  const students = db.collection('students');
  await students.insertMany([
    { name: "John", score: 85 },
    { name: "Jane", score: 92 },
    { name: "Bob", score: 78 },
    { name: "Alice", score: 90 }
  ]);
  const accumulatorResult = await students.aggregate([
    { $group: { _id: null, maxScore: { $max: "$score" } } }
  ]).toArray();
  console.log('Accumulator result:', accumulatorResult);

  // Window operator usage: running maximum 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: {
          highestSoFar: {
            $max: "$price",
            window: { documents: ["unbounded", "current"] }
          }
        }
      }
    }
  ]).toArray();
  console.log('Window result:', windowResult);

  await 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: maximum value across a group
    students = db.students
    students.insert_many([
        { "name": "John", "score": 85 },
        { "name": "Jane", "score": 92 },
        { "name": "Bob", "score": 78 },
        { "name": "Alice", "score": 90 }
    ])
    accumulator_result = list(students.aggregate([
        { "$group": { "_id": None, "maxScore": { "$max": "$score" } } }
    ]))
    print('Accumulator result:', accumulator_result)

    # Window operator usage: running maximum 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": {
                    "highestSoFar": {
                        "$max": "$price",
                        "window": { "documents": ["unbounded", "current"] }
                    }
                }
            }
        }
    ]))
    print('Window result:', window_result)

    client.close()

example()