本文属于机器翻译版本。若本译文内容与英语原文存在差异，则一律以英文原文为准。
$sum
Amazon DocumentDB 中的$sum运算符返回组中每个文档的指定表达式的总和。它是一个分组累加器运算符，通常在聚合管道的 $group 阶段用于执行求和计算。
参数
示例（MongoDB Shell）
以下示例演示如何使用运$sum算符计算每种产品的总销售额。
创建示例文档
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 }
]);
查询示例
db.sales.aggregate([
{ $group: {
_id: "$product",
totalSales: { $sum: { $multiply: [ "$price", "$quantity" ] } }
}}
]);
输出
[
{ "_id": "abc", "totalSales": 50 },
{ "_id": "xyz", "totalSales": 120 }
]
窗口运算符用法示例（MongoDB Shell）
8.0.2 版中的新内容。
该$sum操作员还可以在$setWindowFields舞台中用作窗口操作员。在此上下文中，它返回每个窗口中文档的指定表达式的总和。您可以在output字段下指定运算符，也可以选择使用window文档定义窗口边界。
创建示例文档
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 }
]);
查询示例
以下示例按对文档进行分区product，按分区排序day，并返回amount从分区开始到当前文档的运行总数。
db.dailySales.aggregate([
{
$setWindowFields: {
partitionBy: "$product",
sortBy: { day: 1 },
output: {
runningTotal: {
$sum: "$amount",
window: { documents: ["unbounded", "current"] }
}
}
}
}
]);
输出
[
{ "_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 }
]
每个文档都添加了runningTotal其分区amount内直到包括当前文档在内的累积总和。
代码示例
要查看使用$sum运算符的代码示例，请选择要使用的语言的选项卡。以下示例显示了累加器的用法（输入$group）和窗口运算符的用法（输入$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()
