MongoDB聚合运算符：$push
文章目录
$push聚合运算符返回表达式应用到文档后的值产生的数组。可以应用于 $bucket、 $bucketAuto、 $group、 $setWindowFields等阶段。
语法
js
{ $push: <expression> }$push可以用来比较任何类型的值，针对不同的类型使用特定的BSON比较顺序。
举例
sales集合有下列文档：
json
{ "_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("2014-02-15T09:05:00Z") }
{ "_id" : 6, "item" : "xyz", "price" : 5, "quantity" : 5, "date" : ISODate("2014-02-15T12:05:10Z") }
{ "_id" : 7, "item" : "xyz", "price" : 5, "quantity" : 10, "date" : ISODate("2014-02-15T14:12:12Z") }下面的聚合操作根据日期字段date的日和年对文档进行分组，使用$push累加器对分组内的条目销售量进行计算：
js
db.sales.aggregate(
[
{ $sort: { date: 1, item: 1 } },
{
$group:
{
_id: { day: { $dayOfYear: "$date"}, year: { $year: "$date" } },
itemsSold: { $push: { item: "$item", quantity: "$quantity" } }
}
}
]
)操作返回下面的结果：
json
{
"_id" : { "day" : 46, "year" : 2014 },
"itemsSold" : [
{ "item" : "abc", "quantity" : 10 },
{ "item" : "xyz", "quantity" : 10 },
{ "item" : "xyz", "quantity" : 5 },
{ "item" : "xyz", "quantity" : 10 }
]
}
{
"_id" : { "day" : 34, "year" : 2014 },
"itemsSold" : [
{ "item" : "jkl", "quantity" : 1 },
{ "item" : "xyz", "quantity" : 5 }
]
}
{
"_id" : { "day" : 1, "year" : 2014 },
"itemsSold" : [ { "item" : "abc", "quantity" : 2 } ]
}在$setWindowFields阶段使用
使用下面的脚本创建cakeSales集合，包含了在加利福尼亚（CA）和华盛顿（WA）的蛋糕销售记录：
js
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 }
] )下面的聚合在$setWindowFields阶段使用$push输出每个州的蛋糕销售量的数组：
js
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: "$state",
sortBy: { orderDate: 1 },
output: {
quantitiesForState: {
$push: "$quantity",
window: {
documents: [ "unbounded", "current" ]
}
}
}
}
}
] )在本例中：
partitionBy: "$state"根据state对集合中的文档进行分区，分为两个区CA和WA。sortBy: { orderDate: 1 }根据orderDate对分区内的文档由小到大进行排序，最早的orderDate排在最前面。output使用$push对窗口中的文档进行计算，得到销售量数组。
执行的结果如下：
json
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162, "quantitiesForState" : [ 162 ] }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120, "quantitiesForState" : [ 162, 120 ] }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145, "quantitiesForState" : [ 162, 120, 145 ] }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134, "quantitiesForState" : [ 134 ] }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104, "quantitiesForState" : [ 134, 104 ] }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140, "quantitiesForState" : [ 134, 104, 140 ] }