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$sample

Amazon DocumentDB 中的$sample聚合阶段用于从集合中随机选择指定数量的文档。这对于诸如数据分析、测试和生成样本以供进一步处理之类的任务非常有用。

参数

示例（MongoDB 外壳）

以下示例演示如何使用$sample舞台从temp集合中随机选择两个文档。

创建示例文档

db.temp.insertMany([
  { "_id": 1, "temperature": 97.1, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 2, "temperature": 98.2, "humidity": 0.59, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 3, "temperature": 96.8, "humidity": 0.61, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 4, "temperature": 97.9, "humidity": 0.61, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 5, "temperature": 97.5, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 6, "temperature": 98.0, "humidity": 0.59, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 7, "temperature": 97.2, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 8, "temperature": 98.1, "humidity": 0.59, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 9, "temperature": 96.9, "humidity": 0.62, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 10, "temperature": 97.7, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") }
]);

查询示例

db.temp.aggregate([
   { $sample: { size: 2 } }
])

输出

{ "_id" : 4, "temperature" : 97.9, "humidity" : 0.61, "timestamp" : ISODate("2019-03-21T21:17:22.425Z") }
{ "_id" : 9, "temperature" : 96.9, "humidity" : 0.62, "timestamp" : ISODate("2019-03-21T21:17:22.425Z") }

结果显示，10份文档中有2份是随机抽样的。现在，您可以使用这些文档来确定平均值或进行 min/max 计算。

代码示例

要查看使用该$sample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 sampleDocuments() {
  const client = await MongoClient.connect('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false');
  const db = client.db('test');
  const collection = db.collection('temp');

  const result = await collection.aggregate([
    { $sample: { size: 2 } }
  ]).toArray();

  console.log(result);
  await client.close();
}

sampleDocuments();

Python

from pymongo import MongoClient

def sample_documents():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client['test']
    collection = db['temp']

    result = list(collection.aggregate([
        { '$sample': { 'size': 2 } }
    ]))

    print(result)
    client.close()

sample_documents()