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# $covariancePop
<a name="covariancePop"></a>

8.0.2 版中的新内容。

Amazon DocumentDB 中的`$covariancePop`运算符返回两个数值表达式的总体协方差。它是一个仅在`$setWindowFields`阶段使用的窗口运算符；它在`$group`或`$bucket`阶段无效。您可以在舞台的`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。

**参数**
+ `$covariancePop`采用一个二元素数组`[ <expression1>, <expression2> ]`，其中每个元素都是一个数值表达式（字段路径`"$x"`，例如表达式或常量）。它返回窗口中文档中两个表达式的总体协方差。

## 示例（MongoDB Shell）
<a name="covariancePop-examples"></a>

以下示例按文档分区`series`，按分区排序`t`，并计算整个分区的`x`总体协方差。`y`

**创建示例文档 **

```
db.measurements.insertMany([
  { _id: 1, series: "A", t: 1, x: 1, y: 2 },
  { _id: 2, series: "A", t: 2, x: 2, y: 5 },
  { _id: 3, series: "A", t: 3, x: 3, y: 8 },
  { _id: 4, series: "B", t: 1, x: 1, y: 8 },
  { _id: 5, series: "B", t: 2, x: 2, y: 5 },
  { _id: 6, series: "B", t: 3, x: 3, y: 2 }
]);
```

**查询示例 **

```
db.measurements.aggregate([
  {
    $setWindowFields: {
      partitionBy: "$series",
      sortBy: { t: 1 },
      output: {
        covariance: {
          $covariancePop: [ "$x", "$y" ],
          window: { documents: ["unbounded", "unbounded"] }
        }
      }
    }
  }
]);
```

**输出**

```
[
  { "_id": 1, "series": "A", "t": 1, "x": 1, "y": 2, "covariance": 2 },
  { "_id": 2, "series": "A", "t": 2, "x": 2, "y": 5, "covariance": 2 },
  { "_id": 3, "series": "A", "t": 3, "x": 3, "y": 8, "covariance": 2 },
  { "_id": 4, "series": "B", "t": 1, "x": 1, "y": 8, "covariance": -2 },
  { "_id": 5, "series": "B", "t": 2, "x": 2, "y": 5, "covariance": -2 },
  { "_id": 6, "series": "B", "t": 3, "x": 3, "y": 2, "covariance": -2 }
]
```

分区中的每个文档收到的总协方差相同`covariance`，即该分区中`y`所有文档的`x`总体协方差：`2`对于系列`A`（x 和 y 一起增加），`-2`对于系列`B`（y 随着 x 的增加而减小）。

## 代码示例
<a name="covariancePop-code"></a>

要查看在`$setWindowFields`阶段中使用`$covariancePop`运算符的代码示例，请选择要使用的语言的选项卡：

------
#### [ Node.js ]

```
const { MongoClient } = require('mongodb');

async function example() {
  const client = new MongoClient('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 measurements = db.collection('measurements');

    await measurements.insertMany([
      { _id: 1, series: "A", t: 1, x: 1, y: 2 },
      { _id: 2, series: "A", t: 2, x: 2, y: 5 },
      { _id: 3, series: "A", t: 3, x: 3, y: 8 },
      { _id: 4, series: "B", t: 1, x: 1, y: 8 },
      { _id: 5, series: "B", t: 2, x: 2, y: 5 },
      { _id: 6, series: "B", t: 3, x: 3, y: 2 }
    ]);

    const result = await measurements.aggregate([
      {
        $setWindowFields: {
          partitionBy: "$series",
          sortBy: { t: 1 },
          output: {
            covariance: {
              $covariancePop: [ "$x", "$y" ],
              window: { documents: ["unbounded", "unbounded"] }
            }
          }
        }
      }
    ]).toArray();

    console.log(result);
  } 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']
        measurements = db['measurements']

        measurements.insert_many([
            { '_id': 1, 'series': 'A', 't': 1, 'x': 1, 'y': 2 },
            { '_id': 2, 'series': 'A', 't': 2, 'x': 2, 'y': 5 },
            { '_id': 3, 'series': 'A', 't': 3, 'x': 3, 'y': 8 },
            { '_id': 4, 'series': 'B', 't': 1, 'x': 1, 'y': 8 },
            { '_id': 5, 'series': 'B', 't': 2, 'x': 2, 'y': 5 },
            { '_id': 6, 'series': 'B', 't': 3, 'x': 3, 'y': 2 }
        ])

        result = list(measurements.aggregate([
            {
                '$setWindowFields': {
                    'partitionBy': '$series',
                    'sortBy': { 't': 1 },
                    'output': {
                        'covariance': {
                            '$covariancePop': [ '$x', '$y' ],
                            'window': { 'documents': ['unbounded', 'unbounded'] }
                        }
                    }
                }
            }
        ]))

        print(result)
    finally:
        client.close()

example()
```

------