我有一个集合＆＃34; superpack＆＃34;，它有嵌套对象。示例文档如下所示。
{
"_id" : ObjectId("56038c8cca689261baca93eb"),
"name": "Test sub",
"packs": [
{
"id": "55fbc7f6b0ce97a309b3cead",
"name": "Classic",
"packDispVal": "PACK",
"billingPts": [
{
"id": "55fbc7f6b0ce97a309b3ceab",
"name": "Classic 1 month",
"expiryVal": 1,
"amount": 20,
"topUps": [
{
"id": "55fbc7f6b0ce97a309b3cea9",
"name": "1 extra",
"amount": 8
},
{
"id": "55fbc7f6b0ce97a309b3ceaa",
"name": "2 extra",
"amount": 12
}
]
},
{
"id": "55fbc7f6b0ce97a309b3ceac",
"name": "Classic 2 month",
"expiryVal": 1,
"amount": 30,
"topUps": [
{
"id": "55fbc7f6b0ce97a309b3cea8",
"name": "3 extra",
"amount": 16
}
]
}
]
}
]
}
我需要使用id字段查询嵌套对象topup，结果应该只有选定的topup对象及其关联的父对象。当我在topup id 55fbc7f6b0ce97a309b3cea9上查询它时，我期待输出如下所示。
{
"_id" : ObjectId("56038c8cca689261baca93eb"),
"name": "Test sub",
"packs": [
{
"id": "55fbc7f6b0ce97a309b3cead",
"name": "Classic",
"packDispVal": "PACK",
"billingPts": [
{
"id": "55fbc7f6b0ce97a309b3ceab",
"name": "Classic 1 month",
"expiryVal": 1,
"amount": 20,
"topUps": [
{
"id": "55fbc7f6b0ce97a309b3cea9",
"name": "1 extra",
"amount": 8
}
]
}
]
}
]
}
我尝试使用以下聚合查询。但是它没有返回任何结果。你能帮帮我，查询中有什么问题吗？
db.superpack.aggregate( [{ $match: { "id": "55fbc7f6b0ce97a309b3cea9" } }, { $redact: {$cond: { if: { $eq: [ "$id", "55fbc7f6b0ce97a309b3cea9" ] }, "then": "$$KEEP", else: "$$PRUNE" }}} ])
答案 0 :(得分：2)
不幸的是$redact不是一个可行的选择，因为使用递归$$DESCEND它基本上在文档的所有级别上寻找一个名为“id”的字段。你不可能只在特定的嵌入级别上要求这样做，因为它是全部或全部。
这意味着您需要使用其他方法来过滤内容，而不是$redact。所有“id”值都是唯一的，因此通过“set”操作过滤没有问题。
所以最有效的方法是通过以下方式：
db.docs.aggregate([
{ "$match": {
"packs.billingPts.topUps.id": "55fbc7f6b0ce97a309b3cea9"
}},
{ "$project": {
"packs": {
"$setDifference": [
{ "$map": {
"input": "$packs",
"as": "pack",
"in": {
"$let": {
"vars": {
"billingPts": {
"$setDifference": [
{ "$map": {
"input": "$$pack.billingPts",
"as": "billing",
"in": {
"$let": {
"vars": {
"topUps": {
"$setDifference": [
{ "$map": {
"input": "$$billing.topUps",
"as": "topUp",
"in": {
"$cond": [
{ "$eq": [ "$$topUp.id", "55fbc7f6b0ce97a309b3cea9" ] },
"$$topUp",
false
]
}
}},
[false]
]
}
},
"in": {
"$cond": [
{ "$ne": [{ "$size": "$$topUps"}, 0] },
{
"id": "$$billing.id",
"name": "$$billing.name",
"expiryVal": "$$billing.expiryVal",
"amount": "$$billing.amount",
"topUps": "$$topUps"
},
false
]
}
}
}
}},
[false]
]
}
},
"in": {
"$cond": [
{ "$ne": [{ "$size": "$$billingPts"}, 0 ] },
{
"id": "$$pack.id",
"name": "$$pack.name",
"packDispVal": "$$pack.packDispVal",
"billingPts": "$$billingPts"
},
false
]
}
}
}
}},
[false]
]
}
}}
])
在深入挖掘正在过滤的最内层数组之后，测试每个结果数组向外的大小是否为零，并从结果中省略。
这是一个很长的列表，但它是最有效的方式，因为每个数组首先在每个文档中被过滤掉。
一种不那么有效的方法是用$unwind和$group分开结果：
db.docs.aggregate([
{ "$match": {
"packs.billingPts.topUps.id": "55fbc7f6b0ce97a309b3cea9"
}},
{ "$unwind": "$packs" },
{ "$unwind": "$packs.billingPts" },
{ "$unwind": "$packs.billingPts.topUps"},
{ "$match": {
"packs.billingPts.topUps.id": "55fbc7f6b0ce97a309b3cea9"
}},
{ "$group": {
"_id": {
"_id": "$_id",
"packs": {
"id": "$packs.id",
"name": "$packs.name",
"packDispVal": "$packs.packDispVal",
"billingPts": {
"id": "$packs.billingPts.id",
"name": "$packs.billingPts.name",
"expiryVal": "$packs.billingPts.expiryVal",
"amount": "$packs.billingPts.amount"
}
}
},
"topUps": { "$push": "$packs.billingPts.topUps" }
}},
{ "$group": {
"_id": {
"_id": "$_id._id",
"packs": {
"id": "$_id.packs.id",
"name": "$_id.packs.name",
"packDispVal": "$_id.packs.packDispVal"
}
},
"billingPts": {
"$push": {
"id": "$_id.packs.billingPts.id",
"name": "$_id.packs.billingPts.name",
"expiryVal": "$_id.packs.billingPts.expiryVal",
"amount": "$_id.packs.billingPts.amount",
"topUps": "$topUps"
}
}
}},
{ "$group": {
"_id": "$_id._id",
"packs": {
"$push": {
"id": "$_id.packs.id",
"name": "$_id.packs.name",
"packDispVal": "$_id.packs.packDispVal",
"billingPts": "$billingPts"
}
}
}}
])
列表看起来更简单，但当然$unwind引入了很多开销。分组的过程基本上是保留正在重建的当前数组级别之外的所有内容的副本，然后在下一阶段将该内容推回到数组中，直到返回到根_id。
请注意，除非您打算将此类搜索与多个文档匹配，或者如果您希望通过从一个非常大的文档中有效减少响应大小来减少网络流量而获得显着收益，那么建议您不要做这些，而是遵循与第一个管道示例相同的设计，但在客户端代码中。
虽然第一个例子在性能方面仍然不错，但仍然只能发送到服务器并且作为一般列表，通常在客户端代码中以更干净的方式使用相同的操作来处理和过滤结果结构
{
"_id" : ObjectId("56038c8cca689261baca93eb"),
"packs" : [
{
"id" : "55fbc7f6b0ce97a309b3cead",
"name" : "Classic",
"packDispVal" : "PACK",
"billingPts" : [
{
"id" : "55fbc7f6b0ce97a309b3ceab",
"name" : "Classic 1 month",
"expiryVal" : 1,
"amount" : 20,
"topUps" : [
{
"id" : "55fbc7f6b0ce97a309b3cea9",
"name" : "1 extra",
"amount" : 8
}
]
}
]
}
]
}