Let's say i have this 2 of huge documents:
[
{
_id: ....,
status: "A",
class: "DIP1A",
"created.user._id": ...,
"created.dt": ....,
"category": "private",
price: 100.00 //type double
},
{
_id: ....,
status: "A",
class: "DIP2A",
"created.user._id": ...
"created.dt": ...,
"category": "public",
price: 200.00 //type double
},
];
Query:
var pipeline = [
{
$match: {
"created.user._id": ....
}
},
{
$unwind: "$class"
},
{
$unwind: "$price"
},
{
$group: {
_id: "$class",
price: {
$sum: "$price"
},
count: {
$sum: 1
}
}
},
{
$project: {
_id: 0,
class: '$_id',
count: 1,
price: 1
}
}
];
db.myCollection.aggregate(pipeline);
Problem issue:
Indexes:
db.myCollection.ensureIndex({ 'created.user._id': -1 });
db.myCollection.ensureIndex({ 'created.user._id': -1, class: 1 });
db.myCollection.ensureIndex({ 'created.user._id': -1, price: 1});
Performance:
The one thing you really should do is move the $project stage to right after the $match stage (if the documents contain more data then stated in your question (huge documents)). You want as little data as possible through the pipeline. Also i see an $unwind on price and class but in your example they aren't array's. It could be a copy/paste issue ;-)
Like :
var pipeline = [
{
$match: {
"created.user._id": ....
}
},
{
$project: {
_id: 0,
class: '$_id',
count: 1,
price: 1
}
},
{
$unwind: "$class"
},
{
$unwind: "$price"
},
{
$group: {
_id: "$class",
price: {
$sum: "$price"
},
count: {
$sum: 1
}
}
},
];
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