使用下面的脚本创建grades
集合:
db.grades.insertMany( [
{ quizzes: [ 5, 6, 7 ] },
{ quizzes: [ ] },
{ quizzes: [ 3, 8, 9 ] }
] )
下面的聚合操作使用$map
和$add
对数组quizzes
的每个元素加2:
db.grades.aggregate( [
{
$project: {
adjustedGrades: {
$map: {
input: "$quizzes",
as: "grade",
in: { $add: [ "$$grade", 2 ] }
}
}
}
}
] )
操作返回下面的结果:
[
{
_id: ObjectId("6390b8f7237da390c6869a62"),
adjustedGrades: [ 7, 8, 9 ]
},
{
_id: ObjectId("6390b8f7237da390c6869a63"),
adjustedGrades: []
},
{
_id: ObjectId("6390b8f7237da390c6869a64"),
adjustedGrades: [ 5, 10, 11 ]
}
]
对数组元素取整
使用下面的脚本创建deliveries
集合:
db.deliveries.insertMany( [
{
"city" : "Bakersfield",
"distances" : [ 34.57, 81.96, 44.24 ]
},
{
"city" : "Barstow",
"distances" : [ 73.28, 9.67, 124.36 ]
},
{
"city" : "San Bernadino",
"distances" : [ 16.04, 3.25, 6.82 ]
}
] )
下面的聚合操作使用$map
和truncate
对数组distances
的每个元素进行取整:
db.deliveries.aggregate( [
{
$project: {
city: "$city",
integerValues: {
$map: {
input: "$distances",
as: "decimalValue",
in: { $trunc: "$$decimalValue" }
}
}
}
}
] )
操作返回下面的结果:
[
{
_id: ObjectId("6390b9b1237da390c6869a65"),
city: 'Bakersfield',
integerValues: [ 34, 81, 44 ]
},
{
_id: ObjectId("6390b9b1237da390c6869a66"),
city: 'Barstow',
integerValues: [ 73, 9, 124 ]
},
{
_id: ObjectId("6390b9b1237da390c6869a67"),
city: 'San Bernadino',
integerValues: [ 16, 3, 6 ]
}
]
将摄氏度转为华氏度
使用下面的脚本创建temperatures
集合:
db.temperatures.insertMany( [
{
"date" : ISODate("2019-06-23"),
"tempsC" : [ 4, 12, 17 ]
},
{
"date" : ISODate("2019-07-07"),
"tempsC" : [ 14, 24, 11 ]
},
{
"date" : ISODate("2019-10-30"),
"tempsC" : [ 18, 6, 8 ]
}
] )
下面的聚合操作使用$addFields
阶段向tempsF
文档添加一个新字段,其中包含tempsC
数组中元素的华氏度等效值,为了将摄氏温度转换为华氏温度,使用$map
和$multiply
将摄氏度乘以9/5
然后使用$add
加上32
:
db.temperatures.aggregate( [
{
$addFields: {
"tempsF": {
$map: {
input: "$tempsC",
as: "tempInCelsius",
in: {
$add: [ { $multiply: [ "$$tempInCelsius", 9/5 ] }, 32 ]
}
}
}
}
}
] )
操作返回下面的结果:
[
{
_id: ObjectId("6390ba11237da390c6869a68"),
date: ISODate("2019-06-23T00:00:00.000Z"),
tempsC: [ 4, 12, 17 ],
tempsF: [ 39.2, 53.6, 62.6 ]
},
{
_id: ObjectId("6390ba11237da390c6869a69"),
date: ISODate("2019-07-07T00:00:00.000Z"),
tempsC: [ 14, 24, 11 ],
tempsF: [ 57.2, 75.2, 51.8 ]
},
{
_id: ObjectId("6390ba11237da390c6869a6a"),
date: ISODate("2019-10-30T00:00:00.000Z"),
tempsC: [ 18, 6, 8 ],
tempsF: [ 64.4, 42.8, 46.4 ]
}
]