这是我的MongoDB集合架构:
company: String
model: String
cons: [String] // array of tags that were marked as "cons"
pros: [String] // array of tags that were marked as "pros"
我需要聚合它,以便得到以下输出:
[{
"_id": {
"company": "Lenovo",
"model": "T400"
},
"tags": {
tag: "SomeTag"
pros: 124 // number of times, "SomeTag" tag was found in "pros" array in `Lenovo T400`
cons: 345 // number of times, "SomeTag" tag was found in "cons" array in `Lenovo T400`
}
}...]
我尝试执行以下操作:
var aggParams = {};
aggParams.push({ $unwind: '$cons' });
aggParams.push({ $unwind: '$pros' });
aggParams.push({$group: {
_id: {
company: '$company',
model: '$model',
consTag: '$cons'
},
consTagCount: { $sum: 1 }
}});
aggParams.push({$group: {
_id: {
company: '$_id.company',
model: '$_id.model',
prosTag: '$pros'
},
prosTagCount: { $sum: 1 }
}});
aggParams.push({$group: {
_id: {
company:'$_id.company',
model: '$_id.model'
},
tags: { $push: { tag: { $or: ['$_id.consTag', '$_id.prosTag'] }, cons: '$consTagCount', pros: '$prosTagCount'} }
}});
但我得到了以下结果:
{
"_id": {
"company": "Lenovo",
"model": "T400"
},
"tags": [
{
"tag": false,
"pros": 7
}
]
}
使用aggregation
执行此操作的正确方法是什么?
答案 0 :(得分:2)
是的,考虑到有多个阵列,这有点困难,如果你同时尝试两个阵列,你最终得到一个“笛卡尔条件”,其中一个arrray乘以另一个的内容。
因此,只需在开头组合数组内容,这可能表明您应该如何存储数据:
Model.aggregate(
[
{ "$project": {
"company": 1,
"model": 1,
"data": {
"$setUnion": [
{ "$map": {
"input": "$pros",
"as": "pro",
"in": {
"type": { "$literal": "pro" },
"value": "$$pro"
}
}},
{ "$map": {
"input": "$cons",
"as": "con",
"in": {
"type": { "$literal": "con" },
"value": "$$con"
}
}}
]
}
}},
{ "$unwind": "$data" }
{ "$group": {
"_id": {
"company": "$company",
"model": "$model",
"tag": "$data.value"
},
"pros": {
"$sum": {
"$cond": [
{ "$eq": [ "$data.type", "pro" ] },
1,
0
]
}
},
"cons": {
"$sum": {
"$cond": [
{ "$eq": [ "$data.type", "con" ] },
1,
0
]
}
}
}
],
function(err,result) {
}
)
因此,通过第一个$project
阶段,$map
运算符将“type”值添加到每个数组的每个项目。这并不重要,因为所有项目都应该处理“唯一”,$setUnion
运算符将每个数组“连接”成一个单数组。
如前所述,您可能应该首先以这种方式存储。
然后处理$unwind
后跟$group
,其中每个“专业”和“利弊”然后通过$cond
进行评估,以匹配“类型”,返回{{1} }或1
其中匹配分别为0
到$sum
聚合累加器。
这为您提供了一个“逻辑匹配”,可以根据指定的分组键计算聚合操作中的每个“类型”。