New answer using Mongo aggregation framework

After this question was asked and answered, 10gen released Mongodb version 2.2 with an aggregation framework, which is now the better way to do this sort of query. This query is a little challenging because you want to group by date and the values stored are timestamps, so you have to do something to convert the timestamps to dates that match. For the purposes of example I will just write a query that gets the right counts.

db.col.aggregate(
   { $group: { _id: { $dayOfYear: "$date"},
               click: { $sum: 1 } } }
   )

This will return something like:

[
    {
        "_id" : 144,
        "click" : 165
    },
    {
        "_id" : 275,
        "click" : 12
    }
]

You need to use $match to limit the query to the date range you are interested in and $project to rename _id to date. How you convert the day of year back to a date is left as an exercise for the reader. 🙂

10gen has a handy SQL to Mongo Aggregation conversion chart worth bookmarking. There is also a specific article on date aggregation operators.

Getting a little fancier, you can use:

db.col.aggregate([
  { $group: {
      _id: {
        $add: [
         { $dayOfYear: "$date"}, 
         { $multiply: 
           [400, {$year: "$date"}]
         }
      ]},   
      click: { $sum: 1 },
      first: {$min: "$date"}
    }
  },
  { $sort: {_id: -1} },
  { $limit: 15 },
  { $project: { date: "$first", click: 1, _id: 0} }
])

which will get you the latest 15 days and return some datetime within each day in the date field. For example:

[
    {
        "click" : 431,
        "date" : ISODate("2013-05-11T02:33:45.526Z")
    },
    {
        "click" : 702,
        "date" : ISODate("2013-05-08T02:11:00.503Z")
    },
            ...
    {
        "click" : 814,
        "date" : ISODate("2013-04-25T00:41:45.046Z")
    }
]