MongoDB join data inside an array of objects - mongodb

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 } }
...