Alternative query for MongoDB aggregate function - mongodb

Question

Here is the sample data that I am working on:
{
"_id": 1,
"user": A,
"nums":[1,2,3,4]
}
{
"_id": 2,
"user": B,
"nums":[1,2,4]
}
{
"_id": 3,
"user": B,
"nums":[4,5,7]
}
What I am trying to get is the number of logs for each user and the distinct "nums" list for each user. So the result is something like this:
[
{
"user": A,
"total": 1,
"nums" : [1,2,3,4]
},
{
"user": B,
"total": 2,
"nums" : [1,2,4,5,7]
}
]
Is that possible to achieve in one aggregate query? I am now using two.
db.test.aggregate([{ $group: { _id:"$user", total:{$sum:1}}}])
db.test.aggregate([{$unwind:"$nums"}, { $group: { _id:"$user", nums:{$addToSet:"$nums"}}}])
Also, should one query be faster than two separate queries on large data set or I should just stay with two queries?

Answer 1

You can do this by assembling a list of the original _id values from the docs in the $group after the $unwind to provide a way to get the total count in a final $project:
db.test.aggregate([
{$unwind: '$nums'},
{$group: {
_id: '$user',
ids: {$addToSet: '$_id'},
nums: {$addToSet: '$nums'}
}},
{$project: {
_id: 0,
user: '$_id',
total: {$size: '$ids'},
nums: 1
}}
])
Result:
[
{
"nums": [
7,
5,
4,
2,
1
],
"user": "B",
"total": 2
},
{
"nums": [
4,
3,
2,
1
],
"user": "A",
"total": 1
}
]
I would expect that doing it all in one aggregate pipeline instead of two will be faster, but it's always best to test it in your own environment to be sure.