how to count number of keys in subdocument using aggregation pipeline? - mongodb

Question

Suppose I have a document like this:
{
"_id" : ObjectId("57eb386e37b4842ff5f386c9"),
"lesson_id" : ObjectId("57e27cd190e6993e393f5c74"),
"student_id" : ObjectId("57d3c3f590e6995fe8de7932"),
"answer_records" : {
"1" : {
"answer" : [
"A"
]
},
"3" : {
"answer" : [
"C"
]
}
}
I want to count the number of answer records in the collection. Apparently, this document contribute two answer records which are "1" and "3". So, my question is how to achieve this using aggregation pipeline.

Answer 1

In your case, it is far easier to just use JS.
On the mongo shell :
var json=db.sof.findOne().answer_records;
Object.keys(json).length;
Prints 2 for the number of answer records in the said document.

Answer 2

For MongoDB 3.6 and newer, use the $objectToArray operator within an aggregation pipeline to convert the document to an array. The return array contains an element for each field/value pair in the original document. Each element in the return array is a document that contains two fields k and v.
On getting the array, you can then leverage the use of $addFields pipeline step to create a field that holds the counts and the actual count is derived with the use of the $size operator.
All this can be done in a single pipeline by nesting the expressions as follows:
db.collection.aggregate([
{
"$addFields": {
"answers_count": {
"$size": {
"$objectToArray": "$answer_records"
}
}
}
}
])
Sample Output
{
"_id" : ObjectId("57eb386e37b4842ff5f386c9"),
"lesson_id" : ObjectId("57e27cd190e6993e393f5c74"),
"student_id" : ObjectId("57d3c3f590e6995fe8de7932"),
"answer_records" : {
"1" : {
"answer" : [
"A"
]
},
"3" : {
"answer" : [
"C"
]
}
},
"answers_count": 2
}
For MongoDB server versions which do not support the above operators, you would need to change your schema design in order to carry out efficient queries with the aggregation framework. As it is currently you'd need
to preprocess the documents either on the client or server with JavaScript thus you won't be able to fully utilise MongoDB's better infrastructure built for faster querying.
The ideal design follows:
{
"_id" : ObjectId("57eb386e37b4842ff5f386c9"),
"lesson_id" : ObjectId("57e27cd190e6993e393f5c74"),
"student_id" : ObjectId("57d3c3f590e6995fe8de7932"),
"answer_records" : [
{ "id": "1", "answer": "A" }
{ "id": "3", "answer": "C" }
]
}
which you can then simply apply the aggregation's $project pipeline that uses the $size operator to return the length of the answer_records array per document:
db.collection.aggregate([
{
"$project": {
"lesson_id": 1,
"student_id": 1,
"count": { "$size": "$answer_records" }
}
}
])
If you want the total number of answer records for the whole collection then add another $group pipeline to get the accumulated total for all the documents using an _id of null:
db.collection.aggregate([
{
"$project": {
"count": { "$size": "$answer_records" }
}
},
{
"$group": {
"_id": null,
"total_answers": { "$sum": "$count" }
}
}
])
Otherwise with the current design your only option is MapReduce which is much slower:
db.collection.mapReduce(
function() {
emit(this._id, Object.keys(this.answer_records).length);
},
function() { },
{ "out": { "inline": 1 } }
)
Sample Output:
{
"results" : [
{
"_id" : ObjectId("57eb386e37b4842ff5f386c9"),
"value" : 2
}
],
....
}
To get the total for all the documents in the collection then run this mapReduce operation:
db.collection.mapReduce(
function() {
emit(null, Object.keys(this.answer_records).length);
},
function(key, values) {
return Array.sum(values);
},
{ "out": { "inline": 1 } }
)