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$month
Amazon DocumentDB 中的$month运算符以 1 到 12 之间的数字返回日期的月份。此运算符对于从日期字段中提取月份组成部分以及执行基于日期的聚合和分析非常有用。
参数
示例（MongoDB 外壳）
以下示例演示如何使用$month运算符从日期字段中提取月份并按月对数据进行分组。
创建示例文档
db.sales.insert([
{ product: "abc123", price: 10.99, date: new Date("2022-01-15") },
{ product: "def456", price: 15.50, date: new Date("2022-02-28") },
{ product: "ghi789", price: 8.25, date: new Date("2022-03-10") },
{ product: "jkl012", price: 12.75, date: new Date("2022-04-05") },
{ product: "mno345", price: 18.99, date: new Date("2022-05-20") }
]);
查询示例
db.sales.aggregate([
{ $group: {
_id: { month: { $month: "$date" } },
totalSales: { $sum: "$price" }
}},
{ $sort: { "_id.month": 1 } }
]);
输出
[
{ _id: { month: 1 }, totalSales: 10.99 },
{ _id: { month: 2 }, totalSales: 15.5 },
{ _id: { month: 3 }, totalSales: 8.25 },
{ _id: { month: 4 }, totalSales: 12.75 },
{ _id: { month: 5 }, totalSales: 18.99 }
]
代码示例
要查看使用该$month命令的代码示例，请选择要使用的语言的选项卡：
- Node.js
-
const { MongoClient } = require('mongodb');
async function groupSalesByMonth() {
const client = await MongoClient.connect('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false');
try {
await client.connect();
const db = client.db('test');
const collection = db.collection('sales');
const pipeline = [
{
$group: {
_id: { month: { $month: "$date" } },
totalSales: { $sum: "$price" }
}
},
{
$sort: { "_id.month": 1 }
}
];
const results = await collection.aggregate(pipeline).toArray();
console.dir(results, { depth: null });
} finally {
await client.close();
}
}
groupSalesByMonth().catch(console.error);
- Python
-
from pymongo import MongoClient
def group_sales_by_month():
client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
try:
db = client.test
collection = db.sales
pipeline = [
{
"$group": {
"_id": { "$month": "$date" },
"totalSales": { "$sum": "$price" }
}
},
{
"$sort": { "_id": 1 }
}
]
results = collection.aggregate(pipeline)
for doc in results:
print(doc)
except Exception as e:
print(f"An error occurred: {e}")
finally:
client.close()
group_sales_by_month()
