MongoDB join data inside an array of objects

Question

I have document like this in a collection called diagnoses :

   {
        "_id" : ObjectId("582d43d18ec3f432f3260682"),
        "patientid" : ObjectId("582aacff3894c3afd7ad4677"),
        "doctorid" : ObjectId("582a80c93894c3afd7ad4675"),
        "medicalcondition" : "high fever, cough, runny nose.",
        "diagnosis" : "Viral Flu",
        "addmissiondate" : "2016-01-12",
        "dischargedate" : "2016-01-16",
        "bhtno" : "125",
        "prescription" : [ 
            {
                "drug" : ObjectId("58345e0e996d340bd8126149"),
                "instructions" : "Take 2 daily, after meals."
            }, 
            {
                "drug" : ObjectId("5836bc0b291918eb42966320"),
                "instructions" : "Take 1 daily, after meals."
            }
        ]
    }

The drug id inside the prescription object array is from a separate collection called drugs, see sample document below :

{
    "_id" : ObjectId("58345e0e996d340bd8126149"),
    "genericname" : "Paracetamol Tab 500mg",
    "type" : "X",
    "isbrand" : false
}

I am trying to create a mongodb query using the native node.js driver to get a result like this:

        {
                "_id" : ObjectId("582d43d18ec3f432f3260682"),
                "patientid" : ObjectId("582aacff3894c3afd7ad4677"),
                "doctorid" : ObjectId("582a80c93894c3afd7ad4675"),
                "medicalcondition" : "high fever, cough, runny nose.",
                "diagnosis" : "Viral Flu",
                "addmissiondate" : "2016-01-12",
                "dischargedate" : "2016-01-16",
                "bhtno" : "125",
                "prescription" : [ 
                    {
                        "drug" : 
                        {
                          "_id" : ObjectId("58345e0e996d340bd8126149"),
                          "genericname" : "Paracetamol Tab 500mg",
                          "type" : "X",
                          "isbrand" : false
                        },
                        "instructions" : "Take 2 daily, after meals."
                    },
                    ...
                ]
            }

Any advice on how to approach a similar result like this is much appreciated, thanks.

Answer 1

Using MongoDB 3.4.4 and newer

With the aggregation framework, the $lookup operators supports arrays

db.diagnoses.aggregate([
    { "$addFields": { 
        "prescription": { "$ifNull" : [ "$prescription", [ ] ] }    
    } },
    { "$lookup": {
        "from": "drugs",
        "localField": "prescription.drug",
        "foreignField": "_id",
        "as": "drugs"
    } },
    { "$addFields": {
        "prescription": {
            "$map": {
                "input": "$prescription",
                "in": {
                    "$mergeObjects": [
                        "$$this",
                        { "drug": {
                            "$arrayElemAt": [
                                "$drugs",
                                { 
                                    "$indexOfArray": [
                                        "$drugs._id",
                                        "$$this.drug"
                                    ] 
                                }
                            ]
                        } }
                    ]
                }
            }
        }
    } },
    { "$project": { "drugs": 0 } }
])

For older MongoDB versions:

You can create a pipeline that first flattens the prescription array using the $unwind operator and a $lookup subsequent pipeline step to do a "left outer join" on the "drugs" collection. Apply another $unwind operation on the created array from the "joined" field. $group the previously flattened documents from the first pipeline where there $unwind operator outputs a document for each element in the prescription array.

Assembling the above pipeline, run the following aggregate operation:

db.diagnoses.aggregate([
    { 
        "$project": {               
            "patientid": 1,
            "doctorid": 1,
            "medicalcondition": 1,
            "diagnosis": 1,
            "addmissiondate": 1,
            "dischargedate": 1,
            "bhtno": 1,
            "prescription": { "$ifNull" : [ "$prescription", [ ] ] } 
        }
    },
    {
       "$unwind": {
           "path": "$prescription",
           "preserveNullAndEmptyArrays": true
        }
    },      
    {
        "$lookup": {
            "from": "drugs",
            "localField": "prescription.drug",
            "foreignField": "_id",
            "as": "prescription.drug"
        }
    },
    { "$unwind": "$prescription.drug" },
    { 
        "$group": {
            "_id": "$_id",
            "patientid" : { "$first": "$patientid" },
            "doctorid" : { "$first": "$doctorid" },
            "medicalcondition" : { "$first": "$medicalcondition" },
            "diagnosis" : { "$first": "$diagnosis" },
            "addmissiondate" : { "$first": "$addmissiondate" },
            "dischargedate" : { "$first": "$dischargedate" },
            "bhtno" : { "$first": "$bhtno" },
            "prescription" : { "$push": "$prescription" }
        }
    }
])

Sample Output

{
    "_id" : ObjectId("582d43d18ec3f432f3260682"),
    "patientid" : ObjectId("582aacff3894c3afd7ad4677"),
    "doctorid" : ObjectId("582a80c93894c3afd7ad4675"),
    "medicalcondition" : "high fever, cough, runny nose.",
    "diagnosis" : "Viral Flu",
    "addmissiondate" : "2016-01-12",
    "dischargedate" : "2016-01-16",
    "bhtno" : "125",
    "prescription" : [ 
        {
            "drug" : {
                "_id" : ObjectId("58345e0e996d340bd8126149"),
                "genericname" : "Paracetamol Tab 500mg",
                "type" : "X",
                "isbrand" : false
            },
            "instructions" : "Take 2 daily, after meals."
        }, 
        {
            "drug" : {
                "_id" : ObjectId("5836bc0b291918eb42966320"),
                "genericname" : "Paracetamol Tab 100mg",
                "type" : "Y",
                "isbrand" : false
            },
            "instructions" : "Take 1 daily, after meals."
        }
    ]
}

Answer 2

In MongoDB 3.6 or later versions

It seems that $lookup will overwrite the original array instead of merging it. A working solution (a workaround, if you prefer) is to create a different field, and then merge two fields, as shown below:

db.diagnoses.aggregate([
    { "$lookup": {
        "from": "drugs",
        "localField": "prescription.drug",
        "foreignField": "_id",
        "as": "prescription_drug_info"
    } },
    { "$addFields": {
        "merged_drug_info": {
            "$map": {
                "input": "$prescription",
                "in": {
                    "$mergeObjects": [
                        "$$this",
                        { "$arrayElemAt": [
                            "$prescription_drug_info._id",
                            "$$this._id"
                        ] }
                    ] 
                }
            }
        }
    } }
])

This would add two more fields and the name of the desired field will be merged_drug_info. We can then add $project stage to filter out excessive fields and $set stage to rename the field:

...
{ "$set": { "prescription": "$merged_drug_info" } },
{ "$project": { "prescription_drug_info": 0, "merged_drug_info": 0 } }
...