$sum

Amazon DocumentDB 中的$sum運算子會傳回群組中每個文件的指定表達式總和。這是一個群組累積器運算子，通常用於彙總管道的 $group 階段，以執行總和計算。

參數

• expression：要加總的數值表達式。這可以是欄位路徑、表達式或常數。

範例 (MongoDB Shell)

下列範例示範如何使用 $sum運算子來計算每個產品的總銷售額。

建立範例文件

db.sales.insertMany([
  { product: "abc", price: 10, quantity: 2 },
  { product: "abc", price: 10, quantity: 3 },
  { product: "xyz", price: 20, quantity: 1 },
  { product: "xyz", price: 20, quantity: 5 }
]);

查詢範例

db.sales.aggregate([
  { $group: {
      _id: "$product",
      totalSales: { $sum: { $multiply: [ "$price", "$quantity" ] } }
    }}
]);

輸出

[
  { "_id": "abc", "totalSales": 50 },
  { "_id": "xyz", "totalSales": 120 }
]

視窗運算子用量範例 (MongoDB Shell)

8.0.2 版的新功能。

該$sum運算子也可以用作$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指定表達式總和。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。

建立範例文件

db.dailySales.insertMany([
  { _id: 1, product: "abc", day: 1, amount: 10 },
  { _id: 2, product: "abc", day: 2, amount: 20 },
  { _id: 3, product: "abc", day: 3, amount: 15 },
  { _id: 4, product: "xyz", day: 1, amount: 30 },
  { _id: 5, product: "xyz", day: 2, amount: 25 }
]);

查詢範例

下列範例會依 分割文件product、依 排序每個分割區day，並傳回amount從分割區開始到目前文件的執行中總計 。

db.dailySales.aggregate([
  {
    $setWindowFields: {
      partitionBy: "$product",
      sortBy: { day: 1 },
      output: {
        runningTotal: {
          $sum: "$amount",
          window: { documents: ["unbounded", "current"] }
        }
      }
    }
  }
]);

輸出

[
  { "_id": 1, "product": "abc", "day": 1, "amount": 10, "runningTotal": 10 },
  { "_id": 2, "product": "abc", "day": 2, "amount": 20, "runningTotal": 30 },
  { "_id": 3, "product": "abc", "day": 3, "amount": 15, "runningTotal": 45 },
  { "_id": 4, "product": "xyz", "day": 1, "amount": 30, "runningTotal": 30 },
  { "_id": 5, "product": "xyz", "day": 2, "amount": 25, "runningTotal": 55 }
]

每個文件都會以 擴增runningTotal，即其分割區amount內累計的 總和，最多可達並包含目前的文件。

程式碼範例

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

Node.js

const { MongoClient } = require('mongodb');

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

  try {
    await client.connect();

    const db = client.db('test');

    // Accumulator usage: sum per group
    const sales = db.collection('sales');
    await sales.insertMany([
      { product: "abc", price: 10, quantity: 2 },
      { product: "abc", price: 10, quantity: 3 },
      { product: "xyz", price: 20, quantity: 1 },
      { product: "xyz", price: 20, quantity: 5 }
    ]);
    const accumulatorResult = await sales.aggregate([
      { $group: {
          _id: "$product",
          totalSales: { $sum: { $multiply: [ "$price", "$quantity" ] } }
        }}
    ]).toArray();
    console.log('Accumulator result:', accumulatorResult);

    // Window operator usage: running total within each partition
    const dailySales = db.collection('dailySales');
    await dailySales.insertMany([
      { _id: 1, product: "abc", day: 1, amount: 10 },
      { _id: 2, product: "abc", day: 2, amount: 20 },
      { _id: 3, product: "abc", day: 3, amount: 15 },
      { _id: 4, product: "xyz", day: 1, amount: 30 },
      { _id: 5, product: "xyz", day: 2, amount: 25 }
    ]);
    const windowResult = await dailySales.aggregate([
      {
        $setWindowFields: {
          partitionBy: "$product",
          sortBy: { day: 1 },
          output: {
            runningTotal: {
              $sum: "$amount",
              window: { documents: ["unbounded", "current"] }
            }
          }
        }
      }
    ]).toArray();
    console.log('Window result:', windowResult);

  } catch (error) {
    console.error('Error:', error);
  } finally {
    await client.close();
  }
}

example();

Python

from pymongo import MongoClient
from pprint import pprint

def example():
    client = None
    try:
        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: sum per group
        sales = db.sales
        sales.insert_many([
            { 'product': 'abc', 'price': 10, 'quantity': 2 },
            { 'product': 'abc', 'price': 10, 'quantity': 3 },
            { 'product': 'xyz', 'price': 20, 'quantity': 1 },
            { 'product': 'xyz', 'price': 20, 'quantity': 5 }
        ])
        accumulator_result = list(sales.aggregate([
            { '$group': {
                '_id': '$product',
                'totalSales': { '$sum': { '$multiply': [ '$price', '$quantity' ] } }
            }}
        ]))
        pprint(accumulator_result)

        # Window operator usage: running total within each partition
        daily_sales = db.dailySales
        daily_sales.insert_many([
            { '_id': 1, 'product': 'abc', 'day': 1, 'amount': 10 },
            { '_id': 2, 'product': 'abc', 'day': 2, 'amount': 20 },
            { '_id': 3, 'product': 'abc', 'day': 3, 'amount': 15 },
            { '_id': 4, 'product': 'xyz', 'day': 1, 'amount': 30 },
            { '_id': 5, 'product': 'xyz', 'day': 2, 'amount': 25 }
        ])
        window_result = list(daily_sales.aggregate([
            {
                '$setWindowFields': {
                    'partitionBy': '$product',
                    'sortBy': { 'day': 1 },
                    'output': {
                        'runningTotal': {
                            '$sum': '$amount',
                            'window': { 'documents': ['unbounded', 'current'] }
                        }
                    }
                }
            }
        ]))
        pprint(window_result)

    except Exception as e:
        print(f"An error occurred: {e}")

    finally:
        if client:
            client.close()

example()