I have a collection full of documents with a created_date attribute. I'd like to send these documents through an aggregation pipeline to do some work on them. Ideally I would like to filter them using a $match before I do any other work on them so that I can take advantage of indexes however I can't figure out how to use the new $year/$month/$dayOfMonth operators in my $match expression.
There are a few examples floating around of how to use the operators in a $project operation but I'm concerned that by placing a $project as the first step in my pipeline then I've lost access to my indexes (MongoDB documentation indicates that the first expression must be a $match to take advantage of indexes).
Sample data:
{
post_body: 'This is the body of test post 1',
created_date: ISODate('2012-09-29T05:23:41Z')
comments: 48
}
{
post_body: 'This is the body of test post 2',
created_date: ISODate('2012-09-24T12:34:13Z')
comments: 10
}
{
post_body: 'This is the body of test post 3',
created_date: ISODate('2012-08-16T12:34:13Z')
comments: 10
}
I'd like to run this through an aggregation pipeline to get the total comments on all posts made in September
{
aggregate: 'posts',
pipeline: [
{$match:
/*Can I use the $year/$month operators here to match Sept 2012?
$year:created_date : 2012,
$month:created_date : 9
*/
/*or does this have to be
created_date :
{$gte:{$date:'2012-09-01T04:00:00Z'},
$lt: {$date:'2012-10-01T04:00:00Z'} }
*/
},
{$group:
{_id: '0',
totalComments:{$sum:'$comments'}
}
}
]
}
This works but the match loses access to any indexes for more complicated queries:
{
aggregate: 'posts',
pipeline: [
{$project:
{
month : {$month:'$created_date'},
year : {$year:'$created_date'}
}
},
{$match:
{
month:9,
year: 2012
}
},
{$group:
{_id: '0',
totalComments:{$sum:'$comments'}
}
}
]
}
As you already found, you cannot $match on fields that are not in the document (it works exactly the same way that find works) and if you use $project first then you will lose the ability to use indexes.
What you can do instead is combine your efforts as follows:
{
aggregate: 'posts',
pipeline: [
{$match: {
created_date :
{$gte:{$date:'2012-09-01T04:00:00Z'},
$lt: {date:'2012-10-01T04:00:00Z'}
}}
}
},
{$group:
{_id: '0',
totalComments:{$sum:'$comments'}
}
}
]
}
The above only gives you aggregation for September, if you wanted to aggregate for multiple months, you can for example:
{
aggregate: 'posts',
pipeline: [
{$match: {
created_date :
{ $gte:'2012-07-01T04:00:00Z',
$lt: '2012-10-01T04:00:00Z'
}
},
{$project: {
comments: 1,
new_created: {
"yr" : {"$year" : "$created_date"},
"mo" : {"$month" : "$created_date"}
}
}
},
{$group:
{_id: "$new_created",
totalComments:{$sum:'$comments'}
}
}
]
}
and you'll get back something like:
{
"result" : [
{
"_id" : {
"yr" : 2012,
"mo" : 7
},
"totalComments" : 5
},
{
"_id" : {
"yr" : 2012,
"mo" : 8
},
"totalComments" : 19
},
{
"_id" : {
"yr" : 2012,
"mo" : 9
},
"totalComments" : 21
}
],
"ok" : 1
}
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