MongoDB聚合运算符:$avg
$avg运算符返回给定数值的平均值
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$avg可用于以下阶段:
- $addFields阶段(从MongoDB 3.4开始可用)
- $bucket阶段
- $bucketAuto阶段
- $group阶段
- 包含$expr表达式的$match阶段
- $project阶段
- $replaceRoot阶段(从MongoDB 3.4开始可用)
- $replaceWith阶段(从MongoDB 4.2开始可用)
- $set阶段(从MongoDB 4.2开始可用)
- $setWindowFields阶段(从MongoDB 5.0开始可用)
语法
{ $avg: }
或
{ $avg: [ , ... ] }
使用
非数值或缺失值
$avg会忽略非数值,包括缺失值。如果平均值的所有操作数都是非数值,则
返回空值。
数组操作
在$group阶段,如果表达式解析为一个数组,则会被认为是非数值类型。对于其他支持的阶段:
- 对于以单个表达式的情况,如果表达式解析为数组,则$avg会遍历数组对数字元素进行平均值运算。
- 对于以表达式列表为操作数,如果其中任何表达式被解析为数组,则$avg会将数组视为非数值。
举例
在$group阶段中使用$avg
sales集合有下列的文档:
{ "_id" : 1, "item" : "abc", "price" : 10, "quantity" : 2, "date" : ISODate("2014-01-01T08:00:00Z") } { "_id" : 2, "item" : "jkl", "price" : 20, "quantity" : 1, "date" : ISODate("2014-02-03T09:00:00Z") } { "_id" : 3, "item" : "xyz", "price" : 5, "quantity" : 5, "date" : ISODate("2014-02-03T09:05:00Z") } { "_id" : 4, "item" : "abc", "price" : 10, "quantity" : 10, "date" : ISODate("2014-02-15T08:00:00Z") } { "_id" : 5, "item" : "xyz", "price" : 5, "quantity" : 10, "date" : ISODate("2014-02-15T09:12:00Z") }
下面的聚合按照item字段对文档进行分组,使用$avg计算分组的平均价格和平均文档数量:
db.sales.aggregate( [ { $group: { _id: "$item", avgAmount: { $avg: { $multiply: [ "$price", "$quantity" ] } }, avgQuantity: { $avg: "$quantity" } } } ] )
操作返回下面的结果:
{ "_id" : "xyz", "avgAmount" : 37.5, "avgQuantity" : 7.5 } { "_id" : "jkl", "avgAmount" : 20, "avgQuantity" : 1 } { "_id" : "abc", "avgAmount" : 60, "avgQuantity" : 6 }
在$project阶段中使用$avg
students集合包含下列文档:
{ "_id": 1, "quizzes": [ 10, 6, 7 ], "labs": [ 5, 8 ], "final": 80, "midterm": 75 } { "_id": 2, "quizzes": [ 9, 10 ], "labs": [ 8, 8 ], "final": 95, "midterm": 80 } { "_id": 3, "quizzes": [ 4, 5, 5 ], "labs": [ 6, 5 ], "final": 78, "midterm": 70 }
下面的例子在$project阶段中使用$avg计算测验、实验室、其中和期末平均得分:
db.students.aggregate([ { $project: { quizAvg: { $avg: "$quizzes"}, labAvg: { $avg: "$labs" }, examAvg: { $avg: [ "$final", "$midterm" ] } } } ])
操作返回下面的结果:
{ "_id" : 1, "quizAvg" : 7.666666666666667, "labAvg" : 6.5, "examAvg" : 77.5 } { "_id" : 2, "quizAvg" : 9.5, "labAvg" : 8, "examAvg" : 87.5 } { "_id" : 3, "quizAvg" : 4.666666666666667, "labAvg" : 5.5, "examAvg" : 74 }
在$setWindowFields阶段使用$avg
从MongoDB5.0开始支持。
创建cakeSales集合包含了在加利福尼亚和华盛顿的蛋糕销售状态:
db.cakeSales.insertMany( [ { _id: 0, type: "chocolate", orderDate: new Date("2020-05-18T14:10:30Z"), state: "CA", price: 13, quantity: 120 }, { _id: 1, type: "chocolate", orderDate: new Date("2021-03-20T11:30:05Z"), state: "WA", price: 14, quantity: 140 }, { _id: 2, type: "vanilla", orderDate: new Date("2021-01-11T06:31:15Z"), state: "CA", price: 12, quantity: 145 }, { _id: 3, type: "vanilla", orderDate: new Date("2020-02-08T13:13:23Z"), state: "WA", price: 13, quantity: 104 }, { _id: 4, type: "strawberry", orderDate: new Date("2019-05-18T16:09:01Z"), state: "CA", price: 41, quantity: 162 }, { _id: 5, type: "strawberry", orderDate: new Date("2019-01-08T06:12:03Z"), state: "WA", price: 43, quantity: 134 } ] )
下面的例子在$setWindowFields阶段使用$avg运算符计算各州蛋糕销售数量的平均值:
db.cakeSales.aggregate( [ { $setWindowFields: { partitionBy: "$state", sortBy: { orderDate: 1 }, output: { averageQuantityForState: { $avg: "$quantity", window: { documents: [ "unbounded", "current" ] } } } } } ] )
在这个例子中:
- partitionBy: "$state"根据state州对文档进行分区,包括CA和WA两个分区
- sortBy: { orderDate: 1}按照orderDate对分区文档升序排序,最早的orderDate排在最前面
- output将文档窗口中文档中quantity的移动平均值设置给averageQuantityForState字段。窗口中包含的文档在unbounded下限和current文档之间,$avg返回从开始到当前文档quantity的移动平均值。
在下面的输出结果中,averageQuantityForState为CA和WA的quantity的移动平均值:
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"), "state" : "CA", "price" : 41, "quantity" : 162, "averageQuantityForState" : 162 } { "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"), "state" : "CA", "price" : 13, "quantity" : 120, "averageQuantityForState" : 141 } { "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"), "state" : "CA", "price" : 12, "quantity" : 145, "averageQuantityForState" : 142.33333333333334 } { "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"), "state" : "WA", "price" : 43, "quantity" : 134, "averageQuantityForState" : 134 } { "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"), "state" : "WA", "price" : 13, "quantity" : 104, "averageQuantityForState" : 119 } { "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"), "state" : "WA", "price" : 14, "quantity" : 140, "averageQuantityForState" : 126 }
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