mongdb 中的聚合集合



如何在monogdb中填充聚合查询的结果 Array of followedId

var followeduserId = ["abc","efg","xyz","pqr","acd","rts"];

推荐的饲料

[
{
"feedsId": "feed1",
"userId": "abc"
},
{
"feedsId": "feed1",
"userId": "efg"
}
]

源集合

[
{
"link": "www.yodo.com",
"recommended": [
"abc",
"efg"
],
"title": "This is my feed7",
"topics": [
"topi1",
"topi2",
"topi3",
"topi4"
]
},
{
"link": "www.yodo.com",
"recommended": [
"abc",
"efg",
"das",
"asd",
"eqw",
"weq"
],
"title": "This is my feed8",
"topics": [
"topi1",
"topi2",
"topi3",
"topi4"
]
}
]

运行聚合查询

feedsrecommended.aggregate([
{ $match: { userId: { $in: "followersId" }}},
{ $lookup: {
from: "feeds",
localField: "feedsId",
foreignField: "_id",
as: "feedsId"
}},
{ $group: {
"_id": { "feedsId": "$feedsId" },
"count": { "$sum": 1 }
}},
{ $sort: { count: -1 }}
])

结果 聚合后

var resultfeeds = [
{
"count": 7,
"id": {
"_id": "feed1",
"link": "www.yodo.com",
"recommended": [
"abc",
"efg",
"xyz",
"pqr",
"acd",
"rts"
],
"title": "This is my feed1",
"topics": [
"topi1",
"topi8",
"topi6",
"topi5"
]
}
},
{
"count": 3,
"id": {
"_id": "feed5",
"link": "www.yodo.com",
"recommended": [
"abc",
"efg",
"acd",
"rts"
],
"title": "This is my feed1",
"topics": [
"topi1",
"topi2",
"topi3",
"topi4"
]
}
},
{
"count": 3,
"id": {
"_id": "feed6",
"link": "www.yodo.com",
"recommended": [
"abc",
"efg",
"xyz",
"pqr"
],
"title": "This is my feed1",
"topics": [
"topi7",
"topi1",
"topi4",
"topi8"
]
}
},
{
"count": 2,
"id": {
"_id": "feed2",
"link": "www.yodo.com",
"recommended": [
"abc",
"acd",
"rts"
],
"title": "This is my feed1",
"topics": [
"topi7",
"topi6",
"topi8"
]
}
},
{
"count": 2,
"id": {
"_id": "feed7",
"link": "www.yodo.com",
"recommended": [
"abc",
"efg"
],
"title": "This is my feed1",
"topics": [
"topi1",
"topi5",
"topi6",
"topi4"
]
}
},
{
"count": 1,
"id": {
"_id": "feed3",
"link": "www.yodo.com",
"recommended": [
"abc",
"asd",
"eqw",
"weq"
],
"title": "This is my feed1",
"topics": [
"topi1",
"topi7",
"topi6",
"topi4"
]
}
},
{
"count": 1,
"id": {
"_id": "feed8",
"link": "www.yodo.com",
"recommended": [
"abc",
"das",
"asd",
"eqw",
"weq"
],
"title": "This is my feed1",
"topics": [
"topi1",
"topi2",
"topi5",
"topi4"
]
}
}
]

我想在结果中填充主题并推荐用户名和图像

主题集合

[
{
"topic_name": "tiger"
},
{
"topic_name": "loin"
}
]

用户集合

[
{
"name": "deepa",
"profileImg": "www.com/facebook.jpg"
},
{
"name": "nisa",
"profileImg": "www.com/facebook.jpg"
}
]

我最后的结果应该是这样的

[
{
"count": 2,
"id": {
"_id": "feed2",
"link": "www.yodo.com",
"recommended": [
{
"_id": "abc",
"name": "deepa",
"profileImg": "www.com/facebook.jpg"
},
{
"_id": "acd",
"name": "sigger",
"profileImg": "www.com/facebook.jpg"
},
{
"_id": "rts",
"name": "buster",
"profileImg": "www.com/facebook.jpg"
}
],
"title": "This is my feed1",
"topics": [
{
"_id": "topi6",
"topic_name": "boolena"
},
{
"_id": "topi7",
"topic_name": "mika"
},
{
"_id": "topi8",
"topic_name": "tika"
}
]
}
}
]

您可以在 mongodb3.6及更高版本中尝试以下聚合

Feedsrecommended.aggregate([
{ "$match": { "userId":{ "$in": followersId }}},
{ "$group": {
"_id": "$feedsId",
"count": { "$sum": 1 }
}},
{ "$lookup": {
"from": "feeds",
"let": { "feedsId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$_id", "$$feedsId" ] }}},
{ "$lookup": {
"from": "topics",
"let": { "topics": "$topics" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$topics" ] } } }
],
"as": "topics"
}},
{ "$lookup": {
"from": "users",
"let": { "recommended": "$recommended" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$recommended" ] } } }
],
"as": "recommended"
}}
],
"as": "feedsId"
}}
])

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