Normalizing results from MongoDB

Question

I have a requirement to do the following operation on a MongoDB table. I need to filter documents based on some column values, I need to group by a column and find the count of values based on the aggregation. Further I want to normalize the count values (i.e., divide the count values of the result by the largest count value of that result).

I have accomplished the first two steps by using the $match and $group parameters of the aggregation pipeline. I'm not sure how to do the normalizing of the results part.

My current query looks something like this

db.list_input_file.aggregate([ 
 {$match:{ 'content.Year' : {$eq : '2006'} }}, 
 {$group:{'_id':'$content.Author', count:{$sum:1}}} 
])

Answer 1

I think it can be done by (with explanation among codes)

db.list_input_file.aggregate([ {
    $match : {
        'content.Year' : {
            $eq : '2006'
        }
    }
}, {
    $group : {
        '_id' : '$content.Author',
        count : {
            $sum : 1
        }
    }
}, {
    $group : {
        _id : 0,
        maxCount : {            // get the largest count value
            $max : "$count"
        },
        docs : {                // push all documents into one field to store as an array
            $push : "$$ROOT"
        }
    }
}, {
    $project : {
        _id : 0,
        docs : {
            $map : {
                "input" : "$docs",
                "as" : "e",
                "in" : {                    // retrieve each element
                    _id : "$$e._id",
                    count : "$$e.count",
                    rate : {                // add the normalized value here
                        $divide : [ "$$e.count", "$maxCount"]
                    }
                }
            }
        }
    }
}, {
    $unwind : "$docs"
}, {
    $project : {
        _id : "$docs._id",
        count : "$docs.count",
        rate : "$docs.rate"
    }
} ]);