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MongoDB - Aggregation

Aggregation operations in MongoDB process data records and return computed results. These operations group values from multiple documents together and can perform a variety of operations on the grouped data to return a single result.

The aggregate() Method​

For aggregation in MongoDB, you should use the aggregate() method.

Syntax​

The basic syntax of the aggregate() method is as follows:

>db.COLLECTION_NAME.aggregate(AGGREGATE_OPERATION)

Example​

In the collection, you have the following data:

[
    {
       "_id": ObjectId("7df78ad8902c"),
       "title": "MongoDB Overview",
       "description": "MongoDB is a NoSQL database",
       "by_user": "tutorials point",
       "url": "http://www.tutorialspoint.com",
       "tags": ["mongodb", "database", "NoSQL"],
       "likes": 100
    },
    {
       "_id": ObjectId("7df78ad8902d"),
       "title": "NoSQL Overview",
       "description": "NoSQL database is very fast",
       "by_user": "tutorials point",
       "url": "http://www.tutorialspoint.com",
       "tags": ["mongodb", "database", "NoSQL"],
       "likes": 10
    },
    {
       "_id": ObjectId("7df78ad8902e"),
       "title": "Neo4j Overview",
       "description": "Neo4j is a NoSQL database",
       "by_user": "Neo4j",
       "url": "http://www.neo4j.com",
       "tags": ["neo4j", "database", "NoSQL"],
       "likes": 750
    }
]

Now, from the above collection, if you want to display a list stating how many tutorials are written by each user, then you will use the following aggregate() method:

> db.mycol.aggregate([{$group : {_id : "$by_user", num_tutorial : {$sum : 1}}}])
{ "_id" : "tutorials point", "num_tutorial" : 2 }
{ "_id" : "Neo4j", "num_tutorial" : 1 }

In the above example, we have grouped documents by the field by_user and counted the number of tutorials written by each user.

Aggregation Expressions​

Here are some common aggregation expressions used with the aggregate() method:

ExpressionDescriptionExample
$sumSums up the defined value from all documents in the collection.db.mycol.aggregate([{$group : {_id : "$by_user", num_tutorial : {$sum : "$likes"}}}])
$avgCalculates the average of all given values from all documents in the collection.db.mycol.aggregate([{$group : {_id : "$by_user", num_tutorial : {$avg : "$likes"}}}])
$minGets the minimum of the corresponding values from all documents in the collection.db.mycol.aggregate([{$group : {_id : "$by_user", num_tutorial : {$min : "$likes"}}}])
$maxGets the maximum of the corresponding values from all documents in the collection.db.mycol.aggregate([{$group : {_id : "$by_user", num_tutorial : {$max : "$likes"}}}])
$pushInserts the value into an array in the resulting document.db.mycol.aggregate([{$group : {_id : "$by_user", url : {$push: "$url"}}}])
$addToSetInserts the value into an array in the resulting document but does not create duplicates.db.mycol.aggregate([{$group : {_id : "$by_user", url : {$addToSet : "$url"}}}])
$firstGets the first document from the source documents according to the grouping.db.mycol.aggregate([{$group : {_id : "$by_user", first_url : {$first : "$url"}}}])
$lastGets the last document from the source documents according to the grouping.db.mycol.aggregate([{$group : {_id : "$by_user", last_url : {$last : "$url"}}}])

Pipeline Concept​

MongoDB supports the pipeline concept in the aggregation framework, similar to UNIX command shell pipelines. The pipeline allows executing operations on input data