Have the two following collections:
// collection1: { user1: 1, user2: 2, percent: 0.56 } // collection2: { user1: 1, user2: 2, percent: 0.3 }
I want to join these two collections on user1
and user2
.
How can I write a pipeline in order to get a result like this:
{ user1: 1, user2: 2, percent1: 0.56, percent2: 0.3 }
We can do multiple join conditions with the $lookup
aggregation pipeline operator in version 3.6 and newer.
We need to assign the fields's values to variable using the let
optional field; you then access those variables in the pipeline
field stages where you specify the pipeline to run on the collections.
Note that in the $match
stage, we use the $expr
evaluation query operator to compare the fields's value.
The last stage in the pipeline is the $replaceRoot
aggregation pipeline stage where we simply merge the $lookup
result with part of the $$ROOT
document using the $mergeObjects
operator.
db.collection2.aggregate([ { $lookup: { from: "collection1", let: { firstUser: "$user1", secondUser: "$user2" }, pipeline: [ { $match: { $expr: { $and: [ { $eq: [ "$user1", "$$firstUser" ] }, { $eq: [ "$user2", "$$secondUser" ] } ] } } } ], as: "result" } }, { $replaceRoot: { newRoot: { $mergeObjects:[ { $arrayElemAt: [ "$result", 0 ] }, { percent1: "$$ROOT.percent1" } ] } } } ] )
This pipeline yields something that look like this:
{ "_id" : ObjectId("59e1ad7d36f42d8960c06022"), "user1" : 1, "user2" : 2, "percent" : 0.3, "percent1" : 0.56 }
If you are not on version 3.6+, you can first join using one of your field let say "user1" then from there you unwind the array of the matching document using the $unwind
aggregation pipeline operator. The next stage in the pipeline is the $redact
stage where you filter out those documents where the value of "user2" from the "joined" collection and the input document are not equal using the $$KEEP
and $$PRUNE
system variables. You can then reshape your document in $project
stage.
db.collection1.aggregate([ { "$lookup": { "from": "collection2", "localField": "user1", "foreignField": "user1", "as": "collection2_doc" }}, { "$unwind": "$collection2_doc" }, { "$redact": { "$cond": [ { "$eq": [ "$user2", "$collection2_doc.user2" ] }, "$$KEEP", "$$PRUNE" ] }}, { "$project": { "user1": 1, "user2": 1, "percent1": "$percent", "percent2": "$collection2_doc.percent" }} ])
which produces:
{ "_id" : ObjectId("572daa87cc52a841bb292beb"), "user1" : 1, "user2" : 2, "percent1" : 0.56, "percent2" : 0.3 }
If the documents in your collections have the same structure and you find yourself performing this operation often, then you should consider to merge the two collections into one or insert the documents in those collections into a new collection.
db.collection3.insertMany( db.collection1.find({}, {"_id": 0}) .toArray() .concat(db.collection2.find({}, {"_id": 0}).toArray()) )
Then $group
your documents by "user1" and "user2"
db.collection3.aggregate([ { "$group": { "_id": { "user1": "$user1", "user2": "$user2" }, "percent": { "$push": "$percent" } }} ])
which yields:
{ "_id" : { "user1" : 1, "user2" : 2 }, "percent" : [ 0.56, 0.3 ] }
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