Map/reduce mongodb using two attributes - mongodb

Question

I'm practicing with mongo using the sample db restaurants.
The db has the following structure:
{
"_id" : ObjectId("6035397d0076410d79b29bde"),
"address" : {
"building" : "522",
"coord" : [
-73.95171,
40.767461
],
"street" : "East 74 Street",
"zipcode" : "10021"
},
"borough" : "Manhattan",
"cuisine" : "American ",
"grades" : [
{
"date" : ISODate("2014-09-02T00:00:00Z"),
"grade" : "A",
"score" : 12
},
{
"date" : ISODate("2013-12-19T00:00:00Z"),
"grade" : "B",
"score" : 16
},
{
"date" : ISODate("2013-05-28T00:00:00Z"),
"grade" : "A",
"score" : 9
},
{
"date" : ISODate("2012-12-07T00:00:00Z"),
"grade" : "A",
"score" : 13
},
{
"date" : ISODate("2012-03-29T00:00:00Z"),
"grade" : "A",
"score" : 11
}
],
"name" : "Glorious Food",
"restaurant_id" : "40361521"
}
{
"_id" : ObjectId("6035397d0076410d79b29bdf"),
"address" : {
"building" : "284",
"coord" : [
-73.9829239,
40.6580753
],
"street" : "Prospect Park West",
"zipcode" : "11215"
},
"borough" : "Brooklyn",
"cuisine" : "American ",
"grades" : [
{
"date" : ISODate("2014-11-19T00:00:00Z"),
"grade" : "A",
"score" : 11
},
{
"date" : ISODate("2013-11-14T00:00:00Z"),
"grade" : "A",
"score" : 2
},
{
"date" : ISODate("2012-12-05T00:00:00Z"),
"grade" : "A",
"score" : 13
},
{
"date" : ISODate("2012-05-17T00:00:00Z"),
"grade" : "A",
"score" : 11
}
],
"name" : "The Movable Feast",
"restaurant_id" : "40361606"
}
What I'm trying to do is to get the total of cuisines per borought. So, if a borought has 5 resturants, but in this restaurants, 2 serve the same kind of food, my total should be 4.
I'm suposed to use map/reduce/finalize functions, but I can't figure out how.
All exemples I saw, in the map you have just one attribute to filter de data, but I need to group the restaurants of the same borough and then group e count by cuisine.
Can anyone help me? I've been tryng for a long time, didn't get enyware. The best I manage was to count the total of restaurants per borough.
Thank you.

Answer 1

Try this:
db.restaurants.aggregate([
// First group by "borough" and "cousine".
{
$group: {
_id: {
"borough": "$borough",
"cuisine": "$cuisine"
},
count: { $first: 1 }
}
},
// Second group by only "borough".
{
$group: {
_id: "$_id.borough",
count: { $sum: "$count" }
}
}
]);
Output:
/* 1 */
{
"_id" : "Brooklyn",
"count" : 1
},
/* 2 */
{
"_id" : "Manhattan",
"count" : 2
}
My test data:
/* 1 createdAt:2/24/2021, 11:35:10 PM*/
{
"_id" : ObjectId("6036955624f3423874ac9540"),
"borough" : "Manhattan",
"cuisine" : "Indian",
"restaurant_id" : "40361605"
},
/* 2 createdAt:2/24/2021, 11:35:10 PM*/
{
"_id" : ObjectId("6036955624f3423874ac953f"),
"borough" : "Brooklyn",
"cuisine" : "American",
"restaurant_id" : "40361606"
},
/* 3 createdAt:2/24/2021, 11:35:10 PM*/
{
"_id" : ObjectId("6036955624f3423874ac953e"),
"borough" : "Manhattan",
"cuisine" : "American",
"restaurant_id" : "40361522"
},
/* 4 createdAt:2/24/2021, 11:35:10 PM*/
{
"_id" : ObjectId("6036955624f3423874ac953d"),
"borough" : "Manhattan",
"cuisine" : "American",
"restaurant_id" : "40361521"
}