這是路線模型的貓鼬模式
const routeSchema = new mongoose.Schema({
route: {
type: [{
stationCode: {
type: String,
required: true,
uppercase: true,
validate: {
validator: async function(val) {
const doc = await Station.findOne({
code: val,
});
if (!doc) return false;
return true;
},
message: `A Station with code {VALUE} not found`,
},
},
distanceFromOrigin: {
type: Number,
required: [
true,
'A station must have distance from origin, 0 for origin',
],
},
}, ],
validate: {
validator: function(val) {
return val.length >= 2;
},
message: 'A Route must have at least two stops',
},
},
}, {
toJSON: {
virtuals: true
},
toObject: {
virtuals: true
},
});
這個模式有一個欄位路由作為檔案陣列，每個檔案都有一個 stationCode，
我想按指定順序查詢所有具有“KMME”和“ASN”stationCode 的檔案。以下是使用此架構創建的檔案示例
{
"_id": {
"$oid": "636957ce994af955df472ebc"
},
"route": [{
"stationCode": "DHN",
"distanceFromOrigin": 0,
"_id": {
"$oid": "636957ce994af955df472ebd"
}
},
{
"stationCode": "KMME",
"distanceFromOrigin": 38,
"_id": {
"$oid": "636957ce994af955df472ebe"
}
},
{
"stationCode": "ASN",
"distanceFromOrigin": 54,
"_id": {
"$oid": "636957ce994af955df472ebf"
}
}
],
"__v": 0
}
請針對此問題提出查詢或針對此問題提出其他架構定義
uj5u.com熱心網友回復：
一個簡單的選擇是：
db.collection.aggregate([
{$match: {$expr: {$setIsSubset: [["ASN", "KMME"], "$route.stationCode"]}}},
{$set: {
wanted: {$first:{
$filter: {
input: "$route",
cond: {$in: ["$$this.stationCode", ["ASN", "KMME"]]}
}
}}
}},
{$match: {"wanted.stationCode": "KMME"}},
{$unset: "wanted"}
])
看看它在操場上的例子是如何作業的
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