MongoDB aggregation pipeline filtering two arrays - arrays

Question

Could you give me advise? I have a document like this:
{
"_id" : ObjectId("569620270d3ac01895316edb"),
"customerId" : NumberLong("2000900000000000022"),
"gender" : "MALE",
"birthDate" : ISODate("1976-01-06T23:00:00Z"),
"someArray" : [
{
"id" : 5411,
"firstDate" : ISODate("2014-08-05T16:17:50Z"),
"lastDate" : ISODate("2015-10-31T11:55:51Z"),
"sumOfAll" : 5677.35,
"minAmount" : 9.75,
"maxAmount" : 231.72,
"innerArray" : [
{
"count" : 4,
"amount" : 449.33
},
{
"count" : 3,
"amount" : 401.31
},
{
"count" : 7,
"amount" : 617.8000000000001
},
{
"count" : 4,
"amount" : 465.28999999999996
},
{
"count" : 2,
"amount" : 212.95999999999998
},
{
"count" : 4,
"amount" : 497.53999999999996
},
{
"count" : 3,
"amount" : 278.23
},
{
"count" : 3,
"amount" : 383.15999999999997
},
{
"count" : 6,
"amount" : 459.63
},
{
"count" : 9,
"amount" : 677.19
},
{
"count" : 4,
"amount" : 393.85
}
]
},
{
"id" : 5812,
"firstDate" : ISODate("2014-09-03T17:16:32Z"),
"lastDate" : ISODate("2015-11-04T22:59:59Z"),
"sumOfAll" : 275.6,
"minAmount" : 15,
"maxAmount" : 69,
"innerArray" : [
{
"count" : 1,
"amount" : 17
},
{
"count" : 1,
"amount" : 15.4
},
{
"count" : 1,
"amount" : 69
},
{
"count" : 1,
"amount" : 53.7
},
{
"count" : 2,
"amount" : 84
}
]
},
{
"id" : 7399,
"firstDate" : ISODate("2015-01-12T22:59:59Z"),
"lastDate" : ISODate("2015-03-16T22:59:59Z"),
"sumOfAll" : 144.73,
"minAmount" : 0.84,
"maxAmount" : 24.98,
"innerArray" : [
{
"count" : 5,
"amount" : 50.379999999999995
},
{
"count" : 5,
"amount" : 55.45
},
{
"count" : 10,
"amount" : 38.900000000000006
}
]
},
]
}
And I'd like to filter both inner arrays and also project them. I'm trying this query:
db.sandbox.aggregate([
{ $match: {
'gender': {$eq : 'MALE'},
$or: [
{ $and: [{'someArray.id': {$eq: 5411}}, {'someArray.innerArray.count': 4}, {'someArray.innerArray.amount': {$gte: 2}}]},
{ $and: [{'someArray.id': {$eq: 5812}}, {'someArray.innerArray.count': 5}, {'someArray.innerArray.amount': {$gte: 50}}]},
]
}
},
{ $project: {
gender: 1,
customerId: 1,
someArray: { $filter: {
input: '$someArray',
as: 'item',
cond: {
$and: [
{ $or: [
{$and: [{$eq: ['$$item.id', 5411]}, {$eq: ['$$item.innerArray.count', 4]}, {$gte: ['$$item.innerArray.amount', 2]}]},
{$and: [{$eq: ['$$item.id', 5812]}, {$eq: ['$$item.innerArray.count', 5]}, {$gte: ['$$item.innerArray.amount', 50]}]},
]},
]
}
}},
}}
]).pretty()
And I received result without data in someArray:
{
"_id" : ObjectId("569620270d3ac01895316edb"),
"customerId" : NumberLong("2000900000000000022"),
"gender" : "MALE",
"someArray" : [ ]
}
I want to receive:
{
"_id" : ObjectId("569620270d3ac01895316edb"),
"customerId" : NumberLong("2000900000000000022"),
"gender" : "MALE",
"birthDate" : ISODate("1976-01-06T23:00:00Z"),
"someArray" : [
{
"id" : 5411,
"firstDate" : ISODate("2014-08-05T16:17:50Z"),
"lastDate" : ISODate("2015-10-31T11:55:51Z"),
"sumOfAll" : 5677.35,
"minAmount" : 9.75,
"maxAmount" : 231.72,
"innerArray" : [
{
"count" : 4,
"amount" : 449.33
},
{
"count" : 4,
"amount" : 465.28999999999996
},
{
"count" : 4,
"amount" : 497.53999999999996
},
{
"count" : 4,
"amount" : 393.85
}
]
}
]
}
If I change $eq to $gte, I will receive receive result, but I want to project innerArray too. How can I implement this? Should I use my own MapReduce job or I will able to do this with Aggregation pipeline?
MongoDB version 3.2. Also I observe when I'm trying to use several predicates for array and project only one element, for example:
db.sandbox.find( {$and: [{'someArray.id': 7399}, {'someArray.sumOfAll': {$gte: 5000}}]}, {'customerId': 1, 'someArray.$': 1}).pretty()
But it returns me:
{
"_id" : ObjectId("569620270d3ac01895316edb"),
"customerId" : NumberLong("2000900000000000022"),
"someArray" : [
{
"id" : 5411,
"firstDate" : ISODate("2014-08-05T16:17:50Z"),
"lastDate" : ISODate("2015-10-31T11:55:51Z"),
"sumOfAll" : 5677.35,
"minAmount" : 9.75,
"maxAmount" : 231.72,
"innerArray" : [
{
"count" : 4,
"amount" : 449.33
},
{
"count" : 3,
"amount" : 401.31
},
{
"count" : 7,
"amount" : 617.8000000000001
},
{
"count" : 4,
"amount" : 465.28999999999996
},
{
"count" : 2,
"amount" : 212.95999999999998
},
{
"count" : 4,
"amount" : 497.53999999999996
},
{
"count" : 3,
"amount" : 278.23
},
{
"count" : 3,
"amount" : 383.15999999999997
},
{
"count" : 6,
"amount" : 459.63
},
{
"count" : 9,
"amount" : 677.19
},
{
"count" : 4,
"amount" : 393.85
}
]
}
]
}
Which is incorrect for my perspective. I expect nothing.

Answer 1

First, the way you're using conditions in $match will not result in what you want.
{ $and: [{'someArray.id': {$eq: 5411}}, {'someArray.innerArray.count': 4}, {'someArray.innerArray.amount': {$gte: 2}}]}
The line above will verify each condition separately, instead of checking the count and amount conditions together for each innerArray element. If that's what you want, you should look into the $elemMatch operator.
Second, I don't believe you can use $filter like that on a second-level array. You should unwind someArray first:
db.sandbox.aggregate(
{
$match:
{
gender: { $eq: 'MALE' },
"someArray.id":
{
$in: [5411, 5812]
}
}
},
{
$unwind: "$someArray",
},
{
$project:
{
gender: 1,
customerId: 1,
someArray:
{
id: 1,
firstDate: 1,
lastDate: 1,
sumOfAll: 1,
minAmount: 1,
maxAmount: 1,
innerArray:
{
$filter:
{
input: '$someArray.innerArray',
as: 'item',
cond:
{
$or:
[
{
$and:
[
{ $eq: ['$$item.count', 4] },
{ $gte: ['$$item.amount', 2] }
]
},
{
$and:
[
{ $eq: ['$$item.count', 5] },
{ $gte: ['$$item.amount', 50] }
]
}
]
}
}
}
},
}
})
You can also $group someArray elements back if you want.