MongoDB Aggregation Lookup with Pipeline Doesn't Work - mongodb

Question

I have two collections. I am trying to add the documents of Collection 2 to Collection 1, if number 1 and number 2 in Collection 2 is within a certain range as specified in Collection 1. FYI ObjectId in Collection 1 and ObjectId in Collection 2 refer to two different items/products, hence I cannot join the two collections on this id.
Example Document from Collection 1:
{'_id': ObjectId('4321'),
'number1_lb': 61.205672407820025,
'number1_ub': 61.24170844385606,
'number2_lb': -149.75074963516136,
'number2_ub': -149.71471359912533}
Example Document from Collection 2:
{'_id': ObjectId('1234'),
'number1': 1.282298,
'number2': 103.8475}
I want the output:
{'_id': ObjectId('4321'),
'number1_lb': 61.205672407820025,
'number1_ub': 61.24170844385606,
'number2_lb': -149.75074963516136,
'number2_ub': -149.71471359912533,
'recs': [ObjectId('3456'), ObjectId('4567'),...]
I thought that a lookup stage with pipeline would work. My code is currently as follows:
{"$lookup":{
"from": "Collection 2",
"let":{
"number1_lb":"$number1_lb",
"number1_ub":"$number1_ub",
"number2_lb":"$number2_lb",
"number2_ub":"$number2_ub"
},
"pipeline": [
{"$match":
{"$expr":
{"$and":[
{"$gte":["$number1","$$number1_lb"]},
{"$gte":["$number2","$$number2_lb"]},
{"$lte":["$number1","$$number1_ub"]},
{"$lte":["$number2","$$number2_ub"]}
]}}}
],
"as": "recs"
}}
But running the above gives me no output. Am I doing something wrong??

Answer 1

I ran it and it seems to work fine; but I had to tweak your input data in coll1 as it didn't meet the $match the criteria.
from pymongo import MongoClient
from bson.json_util import dumps
db = MongoClient()["testdatabase"]
# Data Setup
db.coll1.replace_one({"_id": "4321"}, {"_id": "4321", "number1_lb": -61.205672407820025, "number1_ub": 61.24170844385606, "number2_lb": -149.75074963516136, "number2_ub": 149.71471359912533}, upsert=True)
db.coll2.replace_one({"_id": "1234"}, {"_id": "1234", "number1": 1.282298, "number2": 103.8475}, upsert=True)
# Run the aggregation
results = db.coll1.aggregate([
{"$lookup": {
"from": "coll2",
"let": {
"number1_lb": "$number1_lb",
"number1_ub": "$number1_ub",
"number2_lb": "$number2_lb",
"number2_ub": "$number2_ub"
},
"pipeline": [
{"$match":
{"$expr":
{"$and": [
{"$gte": ["$number1", "$$number1_lb"]},
{"$gte": ["$number2", "$$number2_lb"]},
{"$lte": ["$number1", "$$number1_ub"]},
{"$lte": ["$number2", "$$number2_ub"]}
]}}}
],
"as": "recs"
}}
])
# pretty up the results
print(dumps(results, indent=4))
gives:
[
{
"_id": "4321",
"number1_lb": -61.205672407820025,
"number1_ub": 61.24170844385606,
"number2_lb": -149.75074963516136,
"number2_ub": 149.71471359912533,
"recs": [
{
"_id": "1234",
"number1": 1.282298,
"number2": 103.8475
}
]
}
]

Answer 2

You are looking to use a $lookup and a $project :
{
$lookup: {
from: "Collection2",
localField: [Foreign Field of the Collection1],
foreignField: [Principal field of the foreign collection here Collection2],
as: "nameJoint"
}
},
{$project: {
"newFieldName":
}},
But to make a joint between 2 document there as to be an commun field between those 2 documents. I am not sure there is one in this situation or I misunderstand it.
(A $lookup is bassicaly a SQL joint in noSQL )