Below is the sample MongoDB Data Model for a user collection:
{
"_id": ObjectId('58842568c706f50f5c1de662'),
"userId": "123455",
"user_name":"Bob"
"interestedTags": [
"music",
"cricket",
"hiking",
"F1",
"Mobile",
"racing"
],
"listFriends": [
"123456",
"123457",
"123458"
]
}
listFriends is an array of userId for other users
For a particular userId I need to extract the listFriends (userId's) and for those userId's I need to aggregate the interestedTags and their count.
I would be able to achieve this by splitting the query into two parts:
1.) Extract the listFriends for a particular userId,
2.) Use this list in an aggregate() function, something like this
db.user.aggregate([
{ $match: { userId: { $in: [ "123456","123457","123458" ] } } },
{ $unwind: '$interestedTags' },
{ $group: { _id: '$interestedTags', countTags: { $sum : 1 } } }
])
I am trying to solve the question: Is there a way to achieve the above functionality (both steps 1 and 2) in a single aggregate function?
You could use $lookup to look for friend documents. This stage is usually used to join two different collection, but it can also do join upon one single collection, in your case I think it should be fine:
db.user.aggregate([{
$match: {
_id: 'user1',
}
}, {
$unwind: '$listFriends',
}, {
$lookup: {
from: 'user',
localField: 'listFriends',
foreignField: '_id',
as: 'friend',
}
}, {
$project: {
friend: {
$arrayElemAt: ['$friend', 0]
}
}
}, {
$unwind: '$friend.interestedTags'
}, {
$group: {
_id: '$friend.interestedTags',
count: {
$sum: 1
}
}
}]);
Note: I use $lookup and $arrayElemAt which are only available in Mongo 3.2 or newer version, so check your Mongo version before using this pipeline.