Aggregation on the basis of the set of nested docs - mongodb

Question

Let's say I have the next 5 docs:
{ "_id" : "1", "student" : "Oscar", "courses" : [ "A", "B" ] }
{ "_id" : "2", "student" : "Alan", "courses" : [ "A", "B", "C" ] }
{ "_id" : "3", "student" : "Kate", "courses" : [ "A", "B", "D" ] }
{ "_id" : "4", "student" : "John", "courses" : [ "A", "B", "C" ] }
{ "_id" : "5", "student" : "Bema", "courses" : [ "A", "B" ] }
I want to manipulate the collection so that it will return a group of students (with their _id) by set (combination) of courses they take and calculate how many students in each set.
In the example above I have 3 set (combination) of courses and number of students as below:
1 - [ "A", "B" ] <- 2 students take this combination
2 - [ "A", "B", "C" ] <- 2 students
3 - [ "A", "B", "D" ] <- 1 student
I feel like this is more like MapReduce task rather than Aggregation...not sure...
UPDATE 1
Thanks a lot to #ExplosionPills
So the following aggregation command:
db.students.aggregate([{
$group: {
_id: "$courses",
count: {$sum: 1},
students: {$push: "$_id"}
}
}])
gives me the following output:
{ "_id" : [ "A", "B", "D" ], "count" : 1, "students" : [ "3" ] }
{ "_id" : [ "A", "B", "C" ], "count" : 2, "students" : [ "2", "4" ] }
{ "_id" : [ "A", "B" ], "count" : 2, "students" : [ "1", "5" ] }
It groups by set of courses, counts number of students belong to it and their _ids.
UPDATE 2
I found out, the aggregation above treats combination [ "C", "A", "B" ] as different from [ "A", "B", "C" ]. But I need these 2 count as same.
So let's look at the following documents:
{ "_id" : "1", "student" : "Oscar", "courses" : [ "A", "B" ] }
{ "_id" : "2", "student" : "Alan", "courses" : [ "A", "B", "C" ] }
{ "_id" : "3", "student" : "Kate", "courses" : [ "A", "B", "D" ] }
{ "_id" : "4", "student" : "John", "courses" : [ "A", "B", "C" ] }
{ "_id" : "5", "student" : "Bema", "courses" : [ "A", "B" ] }
{ "_id" : "6", "student" : "Alex", "courses" : [ "C", "A", "B" ] }
Let's see this in output:
{ "_id" : [ "C", "A", "B" ], "count" : 1, "students" : [ "6" ] }
{ "_id" : [ "A", "B", "D" ], "count" : 1, "students" : [ "3" ] }
{ "_id" : [ "A", "B", "C" ], "count" : 2, "students" : [ "2", "4" ] }
{ "_id" : [ "A", "B" ], "count" : 2, "students" : [ "1", "5" ] }
See the lines 1 and 3 - this is not what I wanted.
So, to treat [ "C", "A", "B" ] and [ "A", "B", "C" ] as same combination I changed the aggregation as follows:
db.students.aggregate([
{$unwind: "$courses" },
{$sort : {"courses": 1}},
{$group: {_id: "$_id", courses: {$push: "$courses"}}},
{$group: {_id: "$courses", count: {$sum:1}, students: {$push: "$_id"}}}
])
Output:
{ "_id" : [ "A", "B", "D" ], "count" : 1, "students" : [ "3" ] }
{ "_id" : [ "A", "B" ], "count" : 2, "students" : [ "5", "1" ] }
{ "_id" : [ "A", "B", "C" ], "count" : 3, "students" : [ "6", "4", "2" ] }

Answer 1

This is an aggregate operation using grouping.
db.students.aggregate([{
$group: {
// Uniquely identify the document.
// The $ syntax queries on this field
_id: "$courses",
// Add 1 for each field found (effectively a counter)
count: {$sum: 1}
}
}]);
EDIT:
If the courses can be in any order, you can $unwind, $sort, and $group again as suggested in the edited question. It's also possible to do this via mapReduce, but I'm not sure which is faster.
db.students.mapReduce(
function () {
// Use the sorted courses as the key
emit(this.courses.sort(), this._id);
},
function (key, values) {
return {"students": values, count: values.length};
},
{out: {inline: 1}}
)