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。
8.0.1 版的新功能。
Amazon DocumentDB 中的$median運算子會計算數值資料的中位數值。作為累積器，它會計算彙總管道$group階段中群組內文件的數值中位數。做為表達式，它會計算數字陣列的中位數。
參數
"approximate" 方法使用 t-digest 演算法來計算近似中位數。結果是來自資料集的現有值，而不是值之間的插補。精確度會隨著資料點數量的增加而提高。
下列範例示範如何使用 $median 運算子來計算每個類別的中位數測試分數。
建立範例文件
db.students.insertMany([
{ class: "A", score: 72 },
{ class: "A", score: 85 },
{ class: "A", score: 90 },
{ class: "A", score: 68 },
{ class: "A", score: 95 },
{ class: "B", score: 80 },
{ class: "B", score: 75 },
{ class: "B", score: 92 },
{ class: "B", score: 88 },
{ class: "B", score: 70 }
]);
查詢範例
db.students.aggregate([
{ $group: {
_id: "$class",
medianScore: { $median: { input: "$score", method: "approximate" } }
}}
]);
輸出
[
{ "_id": "A", "medianScore": 85 },
{ "_id": "B", "medianScore": 80 }
]
$median 運算子也可以用作$project階段內的表達式，以計算陣列欄位的中位數。
建立範例文件
db.surveys.insertMany([
{ _id: 1, ratings: [3, 5, 7, 9, 2] },
{ _id: 2, ratings: [10, 20, 30, 40, 50] },
{ _id: 3, ratings: [1, 1, 2, 3, 5] }
]);
查詢範例
db.surveys.aggregate([
{ $project: {
medianRating: { $median: { input: "$ratings", method: "approximate" } }
}}
]);
輸出
[
{ "_id": 1, "medianRating": 5 },
{ "_id": 2, "medianRating": 30 },
{ "_id": 3, "medianRating": 2 }
]
若要檢視使用 $median 運算子的程式碼範例，請選擇您要使用的語言標籤。下列範例顯示累積器用量 （在 中$group) 和表達式用量 （在 中$project)：
- 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: median across grouped documents
const students = db.collection('students');
const accumulatorResult = await students.aggregate([
{ $group: {
_id: "$class",
medianScore: { $median: { input: "$score", method: "approximate" } }
}}
]).toArray();
console.log('Accumulator result:', accumulatorResult);
// Expression usage: median of an array field
const surveys = db.collection('surveys');
const expressionResult = await surveys.aggregate([
{ $project: {
medianRating: { $median: { input: "$ratings", method: "approximate" } }
}}
]).toArray();
console.log('Expression result:', expressionResult);
} finally {
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')
try:
db = client['test']
# Accumulator usage: median across grouped documents
students = db['students']
accumulator_result = list(students.aggregate([
{ '$group': {
'_id': '$class',
'medianScore': { '$median': { 'input': '$score', 'method': 'approximate' } }
}}
]))
print('Accumulator result:', accumulator_result)
# Expression usage: median of an array field
surveys = db['surveys']
expression_result = list(surveys.aggregate([
{ '$project': {
'medianRating': { '$median': { 'input': '$ratings', 'method': 'approximate' } }
}}
]))
print('Expression result:', expression_result)
finally:
client.close()
example()
