mongoDB aggregation example

agg_example.txt

> db.students.find().limit(2).pretty()
{
	"_id" : 2,
	"name" : "Corliss Zuk",
	"scores" : [
		{
			"score" : 67.03077096065002,
			"type" : "exam"
		},
		{
			"score" : 6.301851677835235,
			"type" : "quiz"
		},
		{
			"score" : 20.18160621941858,
			"type" : "homework"
		}
	]
}
{
	"_id" : 3,
	"name" : "Bao Ziglar",
	"scores" : [
		{
			"score" : 71.64343899778332,
			"type" : "exam"
		},
		{
			"score" : 24.80221293650313,
			"type" : "quiz"
		},
		{
			"score" : 1.694720653897219,
			"type" : "homework"
		}
	]
}
> db.students.aggregate([
...   {$match:
...     {'name': {$in: ['Corliss Zuk', 'Bao Ziglar']}}
...   },
...   {$project:
...     {'_id': 0,
...      'name': 1,
...      'total_score': {$sum: '$scores.score'},
...      'avg_score': {$avg: '$scores.score'},
...      'max_score': {$max: '$scores.score'},
...      'min_score': {$min: '$scores.score'},
...      'count': {$size: '$scores.score'}
...     }
...   },
... ])
{ "name" : "Corliss Zuk", "total_score" : 93.51422885790383, "avg_score" : 31.171409619301276, "max_score" : 67.03077096065002, "min_score" : 6.301851677835235, "count" : 3 }
{ "name" : "Bao Ziglar", "total_score" : 98.14037258818367, "avg_score" : 32.71345752939455, "max_score" : 71.64343899778332, "min_score" : 1.694720653897219, "count" : 3 }