我正在尝试单独获取所有匹配的元素,here是示例数据和查询。
// json
[
{
"name": "Mr Cool",
"ican": [
{
"subcategory": [
{
"id": "5bffdba824488b182ec86f8d", "name": "Cricket"
},
{
"id": "5bffdba824488b182ec86f8c", "name": "Footbal"
}
],
"category": "5bffdba824488b182ec86f88",
"name": "Sports"
}
]
}
]
// query
db.collection.aggregate([
{
"$match": {
"ican.subcategory.name": { $in: ["Cricket","Football"] }
}
},
{
"$project": { "_id": 1, "name": 1, }
}
])
我得到的是合并结果,我需要单独的比赛记录。我尝试了$all
和$elementMatch
,但得到了相同的响应。我如何获得如下结果。我使用$aggregate
是因为我将使用$geoNear
管道来获取附近的用户。
// current result
[
{
"_id": ObjectId("5a934e000102030405000000"),
"name": "Mr Cool"
}
]
// expected result
[
{
"_id": ObjectId("5a934e000102030405000000"),
"name": "Mr Cool",
"subcategory: "Cricket"
},
{
"_id": ObjectId("5a934e000102030405000000"),
"name": "Mr Cool",
"subcategory: "Footbal"
}
]
谢谢
答案 0 :(得分:1)
尝试这个Mongo Playground
db.col.aggregate([
{"$unwind" : "$ican"},
{"$unwind" : "$ican.subcategory"},
{"$match" : {"ican.subcategory.name": { "$in": ["Cricket","Football"] }}},
{"$group" : {"_id" : null,"data" : {"$push" : {"_id" : "$_id","name" : "$name","subcategory" : "$ican.subcategory.name"}}}},
{"$unwind" : "$data"},
{"$replaceRoot" : {"newRoot" : "$data"}}
])
答案 1 :(得分:1)
您可以在不使用$unwind
的情况下使用以下聚合,以提高性能
db.collection.aggregate([
{ "$match": { "ican.subcategory.name": { "$in": ["Cricket","Football"] }}},
{ "$project": {
"ican": {
"$reduce": {
"input": "$ican",
"initialValue": [],
"in": {
"$concatArrays": [
{ "$filter": {
"input": {
"$map": {
"input": "$$this.subcategory",
"as": "s",
"in": { "name": "$name", "subcategory": "$$s.name" }
}
},
"as": "fil",
"cond": { "$in": ["$$fil.subcategory", ["Football"]] }
}},
"$$value"
]
}
}
}
}},
{ "$unwind": "$ican" },
{ "$replaceRoot": { "newRoot": "$ican" }}
])