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$first
5.0 版中的新增内容。
弹性集群不支持。
Amazon DocumentDB 中的$first操作员从一组分组的文档中返回第一个文档。它通常在聚合管道中用于检索符合特定条件的第一个文档。
参数
示例(MongoDB Shell)
以下示例演示如何使用$first运算符检索聚合期间每个类别遇到的第一个项目值。
注意:根据管道中文档的当前顺序$first返回第一个文档。为确保特定的订单(例如,按日期、价格等),应在$sort阶段之前使用$group阶段。
创建示例文档
db.products.insertMany([
{ _id: 1, item: "abc", price: 10, category: "food" },
{ _id: 2, item: "jkl", price: 20, category: "food" },
{ _id: 3, item: "xyz", price: 5, category: "toy" },
{ _id: 4, item: "abc", price: 5, category: "toy" }
]);
查询示例
db.products.aggregate([
{ $group: { _id: "$category", firstItem: { $first: "$item" } } }
]);
输出
[
{ "_id" : "food", "firstItem" : "abc" },
{ "_id" : "toy", "firstItem" : "xyz" }
]
窗口运算符用法示例(MongoDB Shell)
8.0.2 版中的新内容。
该$first操作员还可以在$setWindowFields舞台中用作窗口操作员。在这种情况下,它返回每个窗口expression中第一个文档的值。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。
在中用作窗口运算符时$setWindowFields,中间数据限制$first为 100 MB。超过此限制的操作会返回错误。
创建示例文档
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 }
]);
查询示例
以下示例按文档分区ticker,按分区排序hour,并返回每个分区中记录的第一个(最早)价格。
db.stockPrices.aggregate([
{
$setWindowFields: {
partitionBy: "$ticker",
sortBy: { hour: 1 },
output: {
firstPrice: {
$first: "$price",
window: { documents: ["unbounded", "current"] }
}
}
}
}
]);
输出
[
{ "_id": 1, "ticker": "ABC", "hour": 1, "price": 50, "firstPrice": 50 },
{ "_id": 2, "ticker": "ABC", "hour": 2, "price": 45, "firstPrice": 50 },
{ "_id": 3, "ticker": "ABC", "hour": 3, "price": 60, "firstPrice": 50 },
{ "_id": 4, "ticker": "ABC", "hour": 4, "price": 40, "firstPrice": 50 },
{ "_id": 5, "ticker": "XYZ", "hour": 1, "price": 30, "firstPrice": 30 },
{ "_id": 6, "ticker": "XYZ", "hour": 2, "price": 35, "firstPrice": 30 },
{ "_id": 7, "ticker": "XYZ", "hour": 3, "price": 25, "firstPrice": 30 }
]
每个文档都以firstPrice其窗口中第一个文档(分区hour中最早的文档)的价格为增值。
代码示例
要查看使用$first运算符的代码示例,请选择要使用的语言的选项卡。以下示例显示了累加器的用法(输入$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: first value per group
const products = db.collection('products');
await products.insertMany([
{ _id: 1, item: "abc", price: 10, category: "food" },
{ _id: 2, item: "jkl", price: 20, category: "food" },
{ _id: 3, item: "xyz", price: 5, category: "toy" },
{ _id: 4, item: "abc", price: 5, category: "toy" }
]);
const accumulatorResult = await products.aggregate([
{ $group: { _id: "$category", firstItem: { $first: "$item" } } }
]).toArray();
console.log('Accumulator result:', accumulatorResult);
// Window operator usage: first value 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: {
firstPrice: {
$first: "$price",
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: first value per group
products = db['products']
products.insert_many([
{ '_id': 1, 'item': 'abc', 'price': 10, 'category': 'food' },
{ '_id': 2, 'item': 'jkl', 'price': 20, 'category': 'food' },
{ '_id': 3, 'item': 'xyz', 'price': 5, 'category': 'toy' },
{ '_id': 4, 'item': 'abc', 'price': 5, 'category': 'toy' }
])
accumulator_result = list(products.aggregate([
{ '$group': { '_id': '$category', 'firstItem': { '$first': '$item' } } }
]))
pprint(accumulator_result)
# Window operator usage: first value 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': {
'firstPrice': {
'$first': '$price',
'window': { 'documents': ['unbounded', 'current'] }
}
}
}
}
]))
pprint(window_result)
except Exception as e:
print(f"An error occurred: {e}")
finally:
if client:
client.close()
example()