Aggregations operations
process data records and return computed results. Aggregation operations group
values from multiple documents together, and can perform a variety of
operations on the grouped data to return a single result. In sql count(*) and
with group by is an equivalent of mongodb aggregation.
Creating new collections for MongoDB
Aggregation
Here I’m inserting documents(rows) into Student collection(Table)
db.Student.insert ({Student_Name:"Kalki", Class: "2", Mark_Scored:100,
Subject: ["Telugu", "English", "Maths"]})
db.Student.insert ({Student_Name:"Matsya", Class:
"1", Mark_Scored:10, Subject:
["Telugu", "English"]})
db.Student.insert ({Student_Name:"Krishna",Class:
"1", Mark_Scored:50, Subject:
["Telugu"]})
db.Student.insert ({Student_Name:"Buddha", Class:
"2", Mark_Scored:60, Subject:
["Telugu"]})
db.Student.insert ({Student_Name:"Rama", Class: "2", Mark_Scored:80, Subject: ["Telugu"]})
db.Student.insert ({Student_Name:"Krishna",Class:
"1", Mark_Scored:50, Subject:
["English"]})
db.Student.insert ({Student_Name:"Buddha", Class:
"2", Mark_Scored:60, Subject:
["English"]})
db.Student.insert ({Student_Name:"Rama", Class: "2", Mark_Scored:80, Subject: ["English"]})
db.Student.insert ({Student_Name:"Matsya", Class:
"1", Mark_Scored:67, Subject:
["Maths"]})
db.Student.insert ({Student_Name:"Krishna",Class:
"1", Mark_Scored:95, Subject:
["Maths"]})
db.Student.insert ({Student_Name:"Buddha", Class:
"2", Mark_Scored:88, Subject:
["Maths"]})
db.Student.insert ({Student_Name:"Rama", Class: "2", Mark_Scored:40, Subject: ["Maths"]})
Inserting and finding
documents from collection
$sum:-
Sums up the defined
value from all documents in the collection.
>db.Student.aggregate([{$group
: {_id : "$item", num_tutorial : {$sum : "$Mark_Scored"
}}}])
Ex: Lets try and get the sum of all the marks
scored by each and every student, in Class "2"
db.Student.aggregate
([
{
"$match":
{
"Class": "2"
}
},
{
"$unwind": "$Subject"
},
{
"$group":
{
"_id":
{
"Student_Name" :
"$Student_Name"
},
"Total_Marks":
{
"$sum":
"$Mark_Scored"
}
}
}
])
$avg:-
> db.Student.aggregate([{$group : {_id :
"$item", num_tutorial : {$avg : "$Mark_Scored" }}}])
Ex:
db.Student.aggregate
([
{
"$match":
{
"Class": "2"
}
},
{
"$unwind": "$Subject"
},
{
"$group":
{
"_id":
{
"Student_Name" :
"$Student_Name"
},
"Total_Marks":
{
"$sum":
"$Mark_Scored"
}
}
}
])
$match
Example:We want
to consider only the marks of the students who study in Class "2"
db.Student.aggregate ([
{
"$match":
{
"Class":"2"
}
}
])
And results is
Let us say, we want to consider only the marks of the
students who study in Class "2" and whose marks are more than or
equal to 80
db.Student.aggregate ([
{
"$match":
{
"Class":"2",
"Mark_Scored":
{
"$gte": 80
}
}
}
])
And results is
$unwind
This will be very useful when the data is stored as list.
When the unwind operator is applied on a list data field, it will generate a
new record for each and every element of the list data field on which unwind is
applied. It basically flattens the data. Lets see an example to understand this
better
Note: The field name, on which unwind is applied, should be
prefixed with $ (dollar sign)
Example:Lets apply unwind over "Kalki"'s data.
db.Student.aggregate ([
{
"$match":
{
"Student_Name": "Kalki",
}
}
])
Storing aggregate
values into another collection:-
db.newStudent.insert( db.Student.aggregate ([
{
"$match":
{
"Class":"2"
}
}
]) )
