定义
版本 5.0 中的新增功能。
返回在 $setWindowFields 阶段定义的分区中应用于文档的数字表达式的指数移动平均值。
$expMovingAvg is only available in the $setWindowFields stage.
$expMovingAvg 事务语法:
{ $expMovingAvg: { input: <input expression>, N: <integer>, alpha: <float> } }
$expMovingAvg 接受包含以下字段的文档:
字段 | 说明 |
|---|---|
指定要评估的表达式。非数字表达式将被忽略。 | |
行为
$expMovingAvg ignores non-numeric values, null values, and missing fields.
示例
创建一个 stockPrices 集合,其中包含名为 "MDB" 和 "MSFT" 的股票的价格:
db.stockPrices.insertMany( [ { stock: "MDB", date: new Date( "2020-05-18T20:00:00Z" ), price: 13 }, { stock: "MDB", date: new Date( "2020-05-19T20:00:00Z" ), price: 15.4 }, { stock: "MDB", date: new Date( "2020-05-20T20:00:00Z" ), price: 12 }, { stock: "MDB", date: new Date( "2020-05-21T20:00:00Z" ), price: 11.7 }, { stock: "MSFT", date: new Date( "2020-05-18T20:00:00Z" ), price: 82 }, { stock: "MSFT", date: new Date( "2020-05-19T20:00:00Z" ), price: 94 }, { stock: "MSFT", date: new Date( "2020-05-20T20:00:00Z" ), price: 112 }, { stock: "MSFT", date: new Date( "2020-05-21T20:00:00Z" ), price: 97.3 } ] )
指数移动平均线使用 N
This example uses $expMovingAvg in the $setWindowFields stage to output the exponential moving average for the stock prices weighted for two historical documents (two days for the example documents) using N set to 2:
db.stockPrices.aggregate( [ { $setWindowFields: { partitionBy: "$stock", sortBy: { date: 1 }, output: { expMovingAvgForStock: { $expMovingAvg: { input: "$price", N: 2 } } } } } ] )
在示例中:
partitionBy: "$stock"按stock对集合中的文档分区。"MDB"和"MSFT"都有分区。sortBy: { date: 1 }按date以升序 (1) 对每个分区中的文档进行排序,因此最早的date位于最前面。outputreturns the exponential moving average for the stockpricefield with N set to2:In the input documents, there is one document for each day and the documents are ordered by
date. Therefore, with N is set to2, thepricein the current document and thepricein the previous document, if available, are allocated the highest weight in the exponential moving average formula.price字段的指数移动平均值存储在名为expMovingAvgForStocks的新字段中,如以下结果所示。
{ "_id" : ObjectId("60d11fef833dfeadc8e6286b"), "stock" : "MDB", "date" : ISODate("2020-05-18T20:00:00Z"), "price" : 13, "expMovingAvgForStock" : 13 } { "_id" : ObjectId("60d11fef833dfeadc8e6286c"), "stock" : "MDB", "date" : ISODate("2020-05-19T20:00:00Z"), "price" : 15.4, "expMovingAvgForStock" : 14.6 } { "_id" : ObjectId("60d11fef833dfeadc8e6286d"), "stock" : "MDB", "date" : ISODate("2020-05-20T20:00:00Z"), "price" : 12, "expMovingAvgForStock" : 12.866666666666667 } { "_id" : ObjectId("60d11fef833dfeadc8e6286e"), "stock" : "MDB", "date" : ISODate("2020-05-21T20:00:00Z"), "price" : 11.7, "expMovingAvgForStock" : 12.088888888888889 } { "_id" : ObjectId("60d11fef833dfeadc8e6286f"), "stock" : "MSFT", "date" : ISODate("2020-05-18T20:00:00Z"), "price" : 82, "expMovingAvgForStock" : 82 } { "_id" : ObjectId("60d11fef833dfeadc8e62870"), "stock" : "MSFT", "date" : ISODate("2020-05-19T20:00:00Z"), "price" : 94, "expMovingAvgForStock" : 90 } { "_id" : ObjectId("60d11fef833dfeadc8e62871"), "stock" : "MSFT", "date" : ISODate("2020-05-20T20:00:00Z"), "price" : 112, "expMovingAvgForStock" : 104.66666666666667 } { "_id" : ObjectId("60d11fef833dfeadc8e62872"), "stock" : "MSFT", "date" : ISODate("2020-05-21T20:00:00Z"), "price" : 97.3, "expMovingAvgForStock" : 99.75555555555556 }
指数移动平均线使用 alpha
This example uses $expMovingAvg in the $setWindowFields stage to output the exponential moving average for the stock prices using alpha set to 0.75:
db.stockPrices.aggregate( [ { $setWindowFields: { partitionBy: "$stock", sortBy: { date: 1 }, output: { expMovingAvgForStock: { $expMovingAvg: { input: "$price", alpha: 0.75 } } } } } ] )
在示例中:
partitionBy: "$stock"按stock对集合中的文档分区。"MDB"和"MSFT"都有分区。sortBy: { date: 1 }按date以升序 (1) 对每个分区中的文档进行排序,因此最早的date位于最前面。outputsets the exponential moving average for the stock prices in a new field calledexpMovingAvgForStock, as shown in the following results. The value for alpha is set to0.75in the exponential moving average formula.
{ "_id" : ObjectId("60d11fef833dfeadc8e6286b"), "stock" : "MDB", "date" : ISODate("2020-05-18T20:00:00Z"), "price" : 13, "expMovingAvgForStock" : 13 } { "_id" : ObjectId("60d11fef833dfeadc8e6286c"), "stock" : "MDB", "date" : ISODate("2020-05-19T20:00:00Z"), "price" : 15.4, "expMovingAvgForStock" : 14.8 } { "_id" : ObjectId("60d11fef833dfeadc8e6286d"), "stock" : "MDB", "date" : ISODate("2020-05-20T20:00:00Z"), "price" : 12, "expMovingAvgForStock" : 12.7 } { "_id" : ObjectId("60d11fef833dfeadc8e6286e"), "stock" : "MDB", "date" : ISODate("2020-05-21T20:00:00Z"), "price" : 11.7, "expMovingAvgForStock" : 11.95 } { "_id" : ObjectId("60d11fef833dfeadc8e6286f"), "stock" : "MSFT", "date" : ISODate("2020-05-18T20:00:00Z"), "price" : 82, "expMovingAvgForStock" : 82 } { "_id" : ObjectId("60d11fef833dfeadc8e62870"), "stock" : "MSFT", "date" : ISODate("2020-05-19T20:00:00Z"), "price" : 94, "expMovingAvgForStock" : 91 } { "_id" : ObjectId("60d11fef833dfeadc8e62871"), "stock" : "MSFT", "date" : ISODate("2020-05-20T20:00:00Z"), "price" : 112, "expMovingAvgForStock" : 106.75 } { "_id" : ObjectId("60d11fef833dfeadc8e62872"), "stock" : "MSFT", "date" : ISODate("2020-05-21T20:00:00Z"), "price" : 97.3, "expMovingAvgForStock" : 99.6625 }