MongoDB Basic Shell Commands (part-6)

MongoDB Basic Shell Commands (part-5)

Array Operators

$elemMatch

$elemMatch allows us to have access to the sub-document of an array field. We have a database sample_training, where one of the documents of the grades collection looks like this:

{
        "_id" : ObjectId("56d5f7eb604eb380b0d8d8d0"),
        "student_id" : 0,
        "scores" : [
                {
                        "type" : "exam",
                        "score" : 84.72636832669608
                },
                {
                        "type" : "quiz",
                        "score" : 7.8865616909793435
                },
                {
                        "type" : "homework",
                        "score" : 22.860114572528147
                },
                {
                        "type" : "homework",
                        "score" : 80.85669686147487
                }
        ],
        "class_id" : 149
}

Now let us find all documents where the student in class 431 received a grade higher than 85 for any type of assignment:

db.grades.find({ "class_id": 431 },
               { "scores": { "$elemMatch": { "score": { "$gt": 85 } } }
             }).pretty()

Or, find all documents where the student had an extra credit score:

db.grades.find({ "scores": { "$elemMatch": { "type": "extra credit" } }
               }).pretty()

In a nutshell:

Array Operators and Sub-Documents

dot(.) Notation

Let us look at the document structure of the trips collection:

{
        "_id" : ObjectId("572bb8222b288919b68abf5b"),
        "tripduration" : 889,
        "start station id" : 268,
        "start station name" : "Howard St & Centre St",
        "end station id" : 3002,
        "end station name" : "South End Ave & Liberty St",
        "bikeid" : 22794,
        "usertype" : "Subscriber",
        "birth year" : 1961,
        "gender" : 2,
        "start station location" : {
                "type" : "Point",
                "coordinates" : [
                        -73.99973337,
                        40.71910537
                ]
        },
        "end station location" : {
                "type" : "Point",
                "coordinates" : [
                        -74.015756,
                        40.711512
                ]
        },
        "start time" : ISODate("2016-01-01T00:01:06Z"),
        "stop time" : ISODate("2016-01-01T00:15:56Z")
}

We can use dot notation to access the field of subdocuments and we can go as deep as we want to access the field of a nested document just like a javascript object and array. Now look at the following query:

db.trips.findOne({ "start station location.type": "Point" })

Top-level subdocument field name is bold in the following picture:

This subdocument has two fields:

We can access those fields like this:

So the general rule is :

Look at the following query:

db.companies.find({ "relationships.0.person.last_name": "Zuckerberg" },
                  { "name": 1 }).pretty()

Part-7 has an interesting discussion about aggregation pipeline. Have a look at it.

Thanks for reading, any correction or recommendation is welcome.