If You want a Date oject returned directly
Then instead of applying the Date Aggregation Operators, instead apply "Date Math" to round the date object. This can often be desirable as all drivers represent a BSON Date in a form that is commonly used for Date manipulation for all languages where that is possible:
db.datetest.aggregate([
{ "$group": {
"_id": {
"$add": [
{ "$subtract": [
{ "$subtract": [ "$date", new Date(0) ] },
{ "$mod": [
{ "$subtract": [ "$date", new Date(0) ] },
1000 * 60 * 60 * 24
]}
]},
new Date(0)
]
},
"click": { "$sum": 1 }
}}
])
Or if as is implied in the question that the grouping interval required is "buckets" of 15 days, then simply apply that to the numeric value in $mod:
db.datetest.aggregate([
{ "$group": {
"_id": {
"$add": [
{ "$subtract": [
{ "$subtract": [ "$date", new Date(0) ] },
{ "$mod": [
{ "$subtract": [ "$date", new Date(0) ] },
1000 * 60 * 60 * 24 * 15
]}
]},
new Date(0)
]
},
"click": { "$sum": 1 }
}}
])
The basic math applied is that when you $subtract two Date objects the result returned will be the milliseconds of differnce numerically. So epoch is represented by Date(0) as the base for conversion in whatever language constructor you have.
With a numeric value, the "modulo" ( $mod ) is applied to round the date ( subtract the remainder from the division ) to the required interval. Being either:
1000 milliseconds x 60 seconds * 60 minutes * 24 hours = 1 day
Or
1000 milliseconds x 60 seconds * 60 minutes * 24 hours * 15 days = 15 days
So it's flexible to whatever interval you require.
By the same token from above an $add operation between a "numeric" value and a Date object will return a Date object equivalent to the millseconds value of both objects combined ( epoch is 0, therefore 0 plus difference is the converted date ).
Easily represented and reproducible in the following listing:
var now = new Date();
var bulk = db.datetest.initializeOrderedBulkOp();
for ( var x = 0; x < 60; x++ ) {
bulk.insert({ "date": new Date( now.valueOf() + ( 1000 * 60 * 60 * 24 * x ))});
}
bulk.execute();
And running the second example with 15 day intervals:
{ "_id" : ISODate("2016-04-14T00:00:00Z"), "click" : 12 }
{ "_id" : ISODate("2016-03-30T00:00:00Z"), "click" : 15 }
{ "_id" : ISODate("2016-03-15T00:00:00Z"), "click" : 15 }
{ "_id" : ISODate("2016-02-29T00:00:00Z"), "click" : 15 }
{ "_id" : ISODate("2016-02-14T00:00:00Z"), "click" : 3 }
Or similar distribution depending on the current date when the listing is run, and of course the 15 day intervals will be consistent since the epoch date.
Using the "Math" method is a bit easier to tune, especially if you want to adjust time periods for different timezones in aggregation output where you can similarly numerically adjust by adding/subtracting the numeric difference from UTC.
