MongoDB aggregation operators were similar to SQL query terms, function, and concepts. Here, we want to show you an example of comparation with SQL queries. If you are getting used to SQL queries, you will see the difference and similarity by the examples.
The MongoDB aggregate syntax simple like this.
db.collection.aggregate(pipeline, options)
That syntax calculates the aggregate of a collection by pipeline and options. The aggregation pipeline is a sequence of data aggregation operations or stages. We can compare this aggregation pipeline with this SQL terms function and concepts.
We will use the popular and legendary Northwind database which is converted to the MongoDB database. You can clone or download it from our GitHub. After cloned or downloaded, restore the MongoRestore command and make sure your MongoDB server is running. We are running MongoDB daemon manually, so, we need to open a new Terminal tab to run it.
mongod
In the previous Terminal tab type this command to restore the Products collection from the Northwind MongoDB database.
mongorestore --db your-db-name -c products ~/northwind-mongo/dump/products.bson
Now, enter the Mongo console then check the Products collection.
mongo use your-db-name db.products.find()
Now, we are ready to practice using MongoDB aggregate method.
The below example will show you how to Group products by SupplierID then calculate a sum of UnitPrice for each SupplierID. The result will sort ascending by the SupplierID.
db.products.aggregate([ { $group: { _id: "$SupplierID", TotalPrice: { $sum: "$UnitPrice" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "TotalPrice" : 47 } { "_id" : 2, "TotalPrice" : 81.4 } { "_id" : 3, "TotalPrice" : 95 } { "_id" : 4, "TotalPrice" : 138 } { "_id" : 5, "TotalPrice" : 59 } { "_id" : 6, "TotalPrice" : 44.75 } { "_id" : 7, "TotalPrice" : 177.85 } { "_id" : 8, "TotalPrice" : 112.7 } { "_id" : 9, "TotalPrice" : 30 } { "_id" : 10, "TotalPrice" : 4.5 } { "_id" : 11, "TotalPrice" : 89.13 } { "_id" : 12, "TotalPrice" : 223.39000000000001 } { "_id" : 13, "TotalPrice" : 25.89 } { "_id" : 14, "TotalPrice" : 79.3 } { "_id" : 15, "TotalPrice" : 60 } { "_id" : 16, "TotalPrice" : 46 } { "_id" : 17, "TotalPrice" : 60 } { "_id" : 18, "TotalPrice" : 281.5 } { "_id" : 19, "TotalPrice" : 28.049999999999997 }
The below example will show you how to Group products by SupplierID then get the average of UnitPrice for each SupplierID. The result will sort ascending by the SupplierID.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $avg: "$UnitPrice" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 15.666666666666666 } { "_id" : 2, "AvgPrice" : 20.35 } { "_id" : 3, "AvgPrice" : 31.666666666666668 } { "_id" : 4, "AvgPrice" : 46 } { "_id" : 5, "AvgPrice" : 29.5 } { "_id" : 6, "AvgPrice" : 14.916666666666666 } { "_id" : 7, "AvgPrice" : 35.57 } { "_id" : 8, "AvgPrice" : 28.175 } { "_id" : 9, "AvgPrice" : 15 } { "_id" : 10, "AvgPrice" : 4.5 } { "_id" : 11, "AvgPrice" : 29.709999999999997 } { "_id" : 12, "AvgPrice" : 44.678000000000004 } { "_id" : 13, "AvgPrice" : 25.89 } { "_id" : 14, "AvgPrice" : 26.433333333333334 } { "_id" : 15, "AvgPrice" : 20 } { "_id" : 16, "AvgPrice" : 15.333333333333334 } { "_id" : 17, "AvgPrice" : 20 } { "_id" : 18, "AvgPrice" : 140.75 } { "_id" : 19, "AvgPrice" : 14.024999999999999 } { "_id" : 20, "AvgPrice" : 26.483333333333334 }
The below example will show you how to Group products by SupplierID then get the minimum values of UnitPrice for each SupplierID. The result will sort ascending by the SupplierID. This operation will use $min operator.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $min: "$UnitPrice" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 10 } { "_id" : 2, "AvgPrice" : 17 } { "_id" : 3, "AvgPrice" : 25 } { "_id" : 4, "AvgPrice" : 10 } { "_id" : 5, "AvgPrice" : 21 } { "_id" : 6, "AvgPrice" : 6 } { "_id" : 7, "AvgPrice" : 15 } { "_id" : 8, "AvgPrice" : 9.2 } { "_id" : 9, "AvgPrice" : 9 } { "_id" : 10, "AvgPrice" : 4.5 } { "_id" : 11, "AvgPrice" : 14 } { "_id" : 12, "AvgPrice" : 7.75 } { "_id" : 13, "AvgPrice" : 25.89 } { "_id" : 14, "AvgPrice" : 12.5 } { "_id" : 15, "AvgPrice" : 2.5 } { "_id" : 16, "AvgPrice" : 14 } { "_id" : 17, "AvgPrice" : 15 } { "_id" : 18, "AvgPrice" : 18 } { "_id" : 19, "AvgPrice" : 9.65 } { "_id" : 20, "AvgPrice" : 14 }
The below example will show you how to Group products by SupplierID then get the maximum values of UnitPrice for each SupplierID. The result will sort ascending by the SupplierID. This operation will use $max operator.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $max: "$UnitPrice" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 19 } { "_id" : 2, "AvgPrice" : 22 } { "_id" : 3, "AvgPrice" : 40 } { "_id" : 4, "AvgPrice" : 97 } { "_id" : 5, "AvgPrice" : 38 } { "_id" : 6, "AvgPrice" : 23.25 } { "_id" : 7, "AvgPrice" : 62.5 } { "_id" : 8, "AvgPrice" : 81 } { "_id" : 9, "AvgPrice" : 21 } { "_id" : 10, "AvgPrice" : 4.5 } { "_id" : 11, "AvgPrice" : 43.9 } { "_id" : 12, "AvgPrice" : 123.79 } { "_id" : 13, "AvgPrice" : 25.89 } { "_id" : 14, "AvgPrice" : 34.8 } { "_id" : 15, "AvgPrice" : 36 } { "_id" : 16, "AvgPrice" : 18 } { "_id" : 17, "AvgPrice" : 26 } { "_id" : 18, "AvgPrice" : 263.5 } { "_id" : 19, "AvgPrice" : 18.4 } { "_id" : 20, "AvgPrice" : 46 }
The below example will show you how to insert the array of the values from other fields for each SupplierID. The result will sort ascending by the SupplierID. This operation will use the $push operator.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $max: "$UnitPrice" }, ReorderLevel: { $push: "$ReorderLevel" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 19, "ReorderLevel" : [ 10, 25, 25 ] } { "_id" : 2, "AvgPrice" : 22, "ReorderLevel" : [ 0, 20, 0, 0 ] } { "_id" : 3, "AvgPrice" : 40, "ReorderLevel" : [ 25, 10, 0 ] } { "_id" : 4, "AvgPrice" : 97, "ReorderLevel" : [ 0, 0, 5 ] } { "_id" : 5, "AvgPrice" : 38, "ReorderLevel" : [ 30, 0 ] } { "_id" : 6, "AvgPrice" : 23.25, "ReorderLevel" : [ 5, 5, 0 ] } { "_id" : 7, "AvgPrice" : 62.5, "ReorderLevel" : [ 10, 0, 0, 5, 30 ] } { "_id" : 8, "AvgPrice" : 81, "ReorderLevel" : [ 5, 0, 5, 15 ] } { "_id" : 9, "AvgPrice" : 21, "ReorderLevel" : [ 25, 25 ] } { "_id" : 10, "AvgPrice" : 4.5, "ReorderLevel" : [ 0 ] } { "_id" : 11, "AvgPrice" : 43.9, "ReorderLevel" : [ 30, 30, 0 ] } { "_id" : 12, "AvgPrice" : 123.79, "ReorderLevel" : [ 0, 30, 25, 15, 0 ] } { "_id" : 13, "AvgPrice" : 25.89, "ReorderLevel" : [ 15 ] } { "_id" : 14, "AvgPrice" : 34.8, "ReorderLevel" : [ 20, 0, 25 ] } { "_id" : 15, "AvgPrice" : 36, "ReorderLevel" : [ 20, 0, 15 ] } { "_id" : 16, "AvgPrice" : 18, "ReorderLevel" : [ 15, 15, 10 ] } { "_id" : 17, "AvgPrice" : 26, "ReorderLevel" : [ 20, 25, 5 ] } { "_id" : 18, "AvgPrice" : 263.5, "ReorderLevel" : [ 15, 5 ] } { "_id" : 19, "AvgPrice" : 18.4, "ReorderLevel" : [ 30, 10 ] } { "_id" : 20, "AvgPrice" : 46, "ReorderLevel" : [ 15, 0, 25 ] }
The below example will show you how to insert the array of the unique values from other fields for each SupplierID. The result will sort ascending by the SupplierID. This operation will use $addToSet operator.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $max: "$UnitPrice" }, ReorderLevel: { $addToSet: "$ReorderLevel" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 19, "ReorderLevel" : [ 25, 10 ] } { "_id" : 2, "AvgPrice" : 22, "ReorderLevel" : [ 20, 0 ] } { "_id" : 3, "AvgPrice" : 40, "ReorderLevel" : [ 0, 10, 25 ] } { "_id" : 4, "AvgPrice" : 97, "ReorderLevel" : [ 5, 0 ] } { "_id" : 5, "AvgPrice" : 38, "ReorderLevel" : [ 0, 30 ] } { "_id" : 6, "AvgPrice" : 23.25, "ReorderLevel" : [ 0, 5 ] } { "_id" : 7, "AvgPrice" : 62.5, "ReorderLevel" : [ 30, 5, 0, 10 ] } { "_id" : 8, "AvgPrice" : 81, "ReorderLevel" : [ 15, 0, 5 ] } { "_id" : 9, "AvgPrice" : 21, "ReorderLevel" : [ 25 ] } { "_id" : 10, "AvgPrice" : 4.5, "ReorderLevel" : [ 0 ] } { "_id" : 11, "AvgPrice" : 43.9, "ReorderLevel" : [ 0, 30 ] } { "_id" : 12, "AvgPrice" : 123.79, "ReorderLevel" : [ 25, 30, 15, 0 ] } { "_id" : 13, "AvgPrice" : 25.89, "ReorderLevel" : [ 15 ] } { "_id" : 14, "AvgPrice" : 34.8, "ReorderLevel" : [ 0, 25, 20 ] } { "_id" : 15, "AvgPrice" : 36, "ReorderLevel" : [ 15, 0, 20 ] } { "_id" : 16, "AvgPrice" : 18, "ReorderLevel" : [ 10, 15 ] } { "_id" : 17, "AvgPrice" : 26, "ReorderLevel" : [ 5, 25, 20 ] } { "_id" : 18, "AvgPrice" : 263.5, "ReorderLevel" : [ 5, 15 ] } { "_id" : 19, "AvgPrice" : 18.4, "ReorderLevel" : [ 10, 30 ] } { "_id" : 20, "AvgPrice" : 46, "ReorderLevel" : [ 25, 0, 15 ] }
The below example will show you how to get the first value of ReorderLevel for each SupplierID. The result will sort ascending by the SupplierID. This operation will use $first operator.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $max: "$UnitPrice" }, ReorderLevel: { $first: "$ReorderLevel" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 19, "ReorderLevel" : 10 } { "_id" : 2, "AvgPrice" : 22, "ReorderLevel" : 0 } { "_id" : 3, "AvgPrice" : 40, "ReorderLevel" : 25 } { "_id" : 4, "AvgPrice" : 97, "ReorderLevel" : 0 } { "_id" : 5, "AvgPrice" : 38, "ReorderLevel" : 30 } { "_id" : 6, "AvgPrice" : 23.25, "ReorderLevel" : 5 } { "_id" : 7, "AvgPrice" : 62.5, "ReorderLevel" : 10 } { "_id" : 8, "AvgPrice" : 81, "ReorderLevel" : 5 } { "_id" : 9, "AvgPrice" : 21, "ReorderLevel" : 25 } { "_id" : 10, "AvgPrice" : 4.5, "ReorderLevel" : 0 } { "_id" : 11, "AvgPrice" : 43.9, "ReorderLevel" : 30 } { "_id" : 12, "AvgPrice" : 123.79, "ReorderLevel" : 0 } { "_id" : 13, "AvgPrice" : 25.89, "ReorderLevel" : 15 } { "_id" : 14, "AvgPrice" : 34.8, "ReorderLevel" : 20 } { "_id" : 15, "AvgPrice" : 36, "ReorderLevel" : 20 } { "_id" : 16, "AvgPrice" : 18, "ReorderLevel" : 15 } { "_id" : 17, "AvgPrice" : 26, "ReorderLevel" : 20 } { "_id" : 18, "AvgPrice" : 263.5, "ReorderLevel" : 15 } { "_id" : 19, "AvgPrice" : 18.4, "ReorderLevel" : 30 } { "_id" : 20, "AvgPrice" : 46, "ReorderLevel" : 15 }
The below example will show you how to get the last value of ReorderLevel for each SupplierID. The result will sort ascending by the SupplierID. This operation will use $last operator.
db.products.aggregate([ { $group: { _id: "$SupplierID", AvgPrice: { $max: "$UnitPrice" }, ReorderLevel: { $last: "$ReorderLevel" } } }, { $sort: { _id: 1 } } ])
Result:
{ "_id" : 1, "AvgPrice" : 19, "ReorderLevel" : 25 } { "_id" : 2, "AvgPrice" : 22, "ReorderLevel" : 0 } { "_id" : 3, "AvgPrice" : 40, "ReorderLevel" : 0 } { "_id" : 4, "AvgPrice" : 97, "ReorderLevel" : 5 } { "_id" : 5, "AvgPrice" : 38, "ReorderLevel" : 0 } { "_id" : 6, "AvgPrice" : 23.25, "ReorderLevel" : 0 } { "_id" : 7, "AvgPrice" : 62.5, "ReorderLevel" : 30 } { "_id" : 8, "AvgPrice" : 81, "ReorderLevel" : 15 } { "_id" : 9, "AvgPrice" : 21, "ReorderLevel" : 25 } { "_id" : 10, "AvgPrice" : 4.5, "ReorderLevel" : 0 } { "_id" : 11, "AvgPrice" : 43.9, "ReorderLevel" : 0 } { "_id" : 12, "AvgPrice" : 123.79, "ReorderLevel" : 0 } { "_id" : 13, "AvgPrice" : 25.89, "ReorderLevel" : 15 } { "_id" : 14, "AvgPrice" : 34.8, "ReorderLevel" : 25 } { "_id" : 15, "AvgPrice" : 36, "ReorderLevel" : 15 } { "_id" : 16, "AvgPrice" : 18, "ReorderLevel" : 10 } { "_id" : 17, "AvgPrice" : 26, "ReorderLevel" : 5 } { "_id" : 18, "AvgPrice" : 263.5, "ReorderLevel" : 5 } { "_id" : 19, "AvgPrice" : 18.4, "ReorderLevel" : 10 } { "_id" : 20, "AvgPrice" : 46, "ReorderLevel" : 25 }
The previous example of the aggregate method can describe with the detailed information using explain() method.
db.products.explain().aggregate([ { $group: { _id: "$SupplierID", $round: { TotalPrice: { $sum: "$UnitPrice" } } } }, { $sort: { _id: 1 } } ])
Result:
{ "waitedMS" : NumberLong(0), "stages" : [ { "$cursor" : { "query" : {},
“fields” : {
“SupplierID” : 1,
“UnitPrice” : 1,
“_id” : 0
},
“queryPlanner” : {
“plannerVersion” : 1,
“namespace” : “mongo-examples.products”,
“indexFilterSet” : false,
“parsedQuery” : {
“$and” : [ ]
},
“winningPlan” : {
“stage” : “COLLSCAN”,
“filter” : {
“$and” : [ ]
},
“direction” : “forward”
},
“rejectedPlans” : [ ]
}
}
},
{
“$group” : {
“_id” : “$SupplierID”,
“TotalPrice” : {
“$sum” : “$UnitPrice”
}
}
},
{
“$sort” : {
“sortKey” : {
“_id” : 1
}
}
}
],
“ok” : 1
}
That it’s, a few examples of the MongoDB Aggregate Methods.
Thanks for reading ❤
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