有下面这两个合集
orders: [
{
"_id": "64355c928dcce8cdf4b9c7d2",
"destinations": [
{
"ship_to_id": "64355c92af10d37993473e12", // mongoose id from locations collection
"sold_to_id": "64355c92a57d8b29412a1cc2" // mongoose id from locations collection
},
{
"ship_to_id": "64355c92a57d8b29412a1cc2",
"sold_to_id": "64355c92ed8af3f7cd7199b2"
},
{
"ship_to_id": "64355c92256aa652e6c3fdc5",
"sold_to_id": "64355c924f9a2fcafa90daed"
}
],
"contact_details": [
{
"ship_to_ref": "aaa",
"sold_to_ref": "bbb",
"contact_email": "[email protected]",
},
{
"ship_to_ref": "bbb",
"sold_to_ref": "ccc",
"contact_email": "[email protected]"
},
{
"ship_to_ref": "ddd",
"sold_to_ref": "eee",
"contact_email": "[email protected]",
}
]
},
{
"_id": "64355c92bf25e54cf901be39",
"destinations": [
{
"ship_to_id": "64355c92af10d37993473e12",
"sold_to_id": "64355c92a57d8b29412a1cc2"
},
{
"ship_to_id": "64355c92a57d8b29412a1cc2",
"sold_to_id": "64355c92ed8af3f7cd7199b2"
},
{
"ship_to_id": "64355c92af10d37993473e12",
"sold_to_id": "64355c92256aa652e6c3fdc5"
}
],
"contact_details": [
{
"ship_to_ref": "aaa",
"sold_to_ref": "bbb",
"contact_email": "[email protected]",
},
{
"ship_to_ref": "bbb",
"sold_to_ref": "ccc",
"contact_email": "[email protected]",
},
{
"ship_to_ref": "aaa",
"sold_to_ref": "ddd",
"contact_email": "[email protected]",
}
]
},
{
"_id": "64355c921445785f4b50040e",
"destinations": [
{
"ship_to_id": "64355c92af10d37993473e12",
"sold_to_id": "64355c92a57d8b29412a1cc2"
},
{
"ship_to_id": "64355c92af10d37993473e12",
"sold_to_id": "64355c92ed8af3f7cd7199b2"
}
],
"contact_details": [
{
"ship_to_ref": "aaa",
"sold_to_ref": "bbb",
"contact_email": "[email protected]",
},
{
"ship_to_ref": "aaa",
"sold_to_ref": "ccc",
"contact_email": "[email protected]",
},
]
}
]
和
locations: [
{
"_id": "64355c92af10d37993473e12",
"reference_id": "aaa"
},
{
"_id": "64355c92a57d8b29412a1cc2",
"reference_id": "bbb"
},
{
"_id": "64355c92ed8af3f7cd7199b2",
"reference_id": "ccc"
},
{
"_id": "64355c92256aa652e6c3fdc5",
"reference_id": "ddd"
},
{
"_id": "64355c924f9a2fcafa90daed",
"reference_id": "eee"
},
]
现在我想要实现的是编写一个聚合查询,根据相同的 ship_to、sold_to 和 contact_email 对我的所有缩进进行分组(Note:要验证这是否是有效的 ship_to 和 sold_to,我们需要从
locations
集合中查找使用ship_to_id
和sold_to_id
,检索各自的reference_id 's
,然后将其与联系人详细信息中可用的ship_to_ref
和sold_to_ref
进行比较)这样查询结果就像
[{
_id: {
ship_to_ref: "aaa",
sold_to_ref: "bbb",
ship_to_id:"64355c92af10d37993473e12"
sold_to_id:"64355c92a57d8b29412a1cc2"
contact_email: "[email protected]"
},
orders: [
{ "_id": "64355c928dcce8cdf4b9c7d2", ... },
{ "_id": "64355c92bf25e54cf901be39", ... },
{ "_id" : "64355c921445785f4b50040e", ...}
],
},
{
_id: {
ship_to_ref: "bbb",
sold_to_ref: "ccc",
ship_to_id:"64355c92a57d8b29412a1cc2",
sold_to_id:"64355c92ed8af3f7cd7199b2",
contact_email: "[email protected]"
},
orders: [
{ "_id": "64355c928dcce8cdf4b9c7d2", ... },
{ "_id": "64355c92bf25e54cf901be39", ... },
],
},
{
_id: {
ship_to_ref: "ddd",
sold_to_ref: "eee",
ship_to_id: "64355c92256aa652e6c3fdc5",
sold_to_id: "64355c924f9a2fcafa90daed",
"contact_email": "[email protected]",
},
orders: [
{ "_id": "64355c928dcce8cdf4b9c7d2", ... }
],
},
{
_id: {
ship_to_ref: "aaa",
sold_to_ref: "ddd",
ship_to_id: "64355c92af10d37993473e12",
sold_to_id: "64355c92256aa652e6c3fdc5",
contact_email: "[email protected]",
},
orders: [
{ "_id": "64355c92bf25e54cf901be39", ... }
],
},
{
_id: {
ship_to_ref: "aaa",
sold_to_ref: "ccc",
ship_to_id: "64355c92af10d37993473e12",
sold_to_id: "64355c92ed8af3f7cd7199b2",
contact_email: "[email protected]",
},
orders: [
{ "_id": "64355c921445785f4b50040e", ... }
],
},
]
下面是我试过的聚合查询
[{
$match: {
contact_details: { $exists: true },
},
},
{ $unwind: '$destinations' },
{ $unwind: '$contact_details'},
{
$group: {
_id: {
sold_to_id: '$destinations.sold_to_id',
ship_to_id: '$destinations.ship_to_id',
}
orders: {
$push: {
id: '$order_no', // order_no is an attribute from an order object
contact_details: '$contact_details',
},
},
type: { $first: { type: '$destinations.type' } },
},
}]
但不确定如何合并查找并进行参考比较和电子邮件检查。 需要帮助。
提前致谢
一个选项是
$map
在你unwind
之前,所以你只能unwind
一次并使用$indexOfArray
以匹配$lookup
之后的引用:
db.orders.aggregate([
{$match: {contact_details: {$exists: true}}},
{$project: {
del: {$map: {
input: {$range: [0, {$size: "$contact_details"}]},
in: {
destination: {$arrayElemAt: ["$destinations", "$$this"]},
contact: {$arrayElemAt: ["$contact_details", "$$this"]}
}
}}
}},
{$unwind: "$del"},
{$group: {
_id: {
sold_to_id: "$del.destination.sold_to_id",
ship_to_id: "$del.destination.ship_to_id"
},
contact_email: {$first: "$del.contact.contact_email"},
orders: {$push: {contact_details: "$del.contact"}}
}},
{$set: {locations: ["$_id.sold_to_id", "$_id.ship_to_id"]}},
{$lookup: {
from: "locations",
localField: "locations",
foreignField: "_id",
as: "locations"
}},
{$project: {
"_id.ship_to_id": "$_id.ship_to_id",
"_id.sold_to_id": "$_id.sold_to_id",
"_id.contact_email": "$contact_email",
"_id.ship_to_ref": {$getField: {
input: {$arrayElemAt: [
"$locations",
{$indexOfArray: ["$locations._id", "$_id.ship_to_id"]}
]},
field: "reference_id"
}},
"_id.sold_to_ref": {$getField: {
input: {$arrayElemAt: [
"$locations",
{$indexOfArray: ["$locations._id", "$_id.sold_to_id"]}
]},
field: "reference_id"
}},
orders: 1
}}
])