2017 update $lookup can now directly use an array as the local field. $unwind is no longer needed. Old answer The $lookup aggregation pipeline stage will not work directly with an array. The main intent of the design is for a “left join” as a “one to many” type of join ( or really a … Read more
Assuming, var friend = { firstName: ‘Harry’, lastName: ‘Potter’ }; There are two options you have: Update the model in-memory, and save (plain javascript array.push): person.friends.push(friend); person.save(done); or PersonModel.update( { _id: person._id }, { $push: { friends: friend } }, done ); I always try and go for the first option when possible, because it’ll … Read more
There’s a more efficient way to do this in MongoDB 2.2+ now that you can use numeric array indexes (0 based) in query object keys. // Find all docs that have at least two name array elements. db.accommodations.find({‘name.1’: {$exists: true}}) You can support this query with an index that uses a partial filter expression (requires … Read more
The primary committer to node-mongodb-native says: You open do MongoClient.connect once when your app boots up and reuse the db object. It’s not a singleton connection pool each .connect creates a new connection pool. So, to answer your question directly, reuse the db object that results from MongoClient.connect(). This gives you pooling, and will provide … Read more
As noted, the order of the arguments in the array of an $in clause does not reflect the order of how the documents are retrieved. That of course will be the natural order or by the selected index order as shown. If you need to preserve this order, then you basically have two options. So … Read more
Starting with the 3.2 release of MongoDB, you can get N random docs from a collection using the $sample aggregation pipeline operator: // Get one random document from the mycoll collection. db.mycoll.aggregate([{ $sample: { size: 1 } }]) If you want to select the random document(s) from a filtered subset of the collection, prepend a … Read more
Using aggregate is the right approach, but you need to $unwind the list array before applying the $match so that you can filter individual elements and then use $group to put it back together: db.test.aggregate([ { $match: {_id: ObjectId(“512e28984815cbfcb21646a7”)}}, { $unwind: ‘$list’}, { $match: {‘list.a’: {$gt: 3}}}, { $group: {_id: ‘$_id’, list: {$push: ‘$list.a’}}} ]) … Read more
You could do this with MapReduce: mr = db.runCommand({ “mapreduce” : “my_collection”, “map” : function() { for (var key in this) { emit(key, null); } }, “reduce” : function(key, stuff) { return null; }, “out”: “my_collection” + “_keys” }) Then run distinct on the resulting collection so as to find all the keys: db[mr.result].distinct(“_id”) [“foo”, … Read more
There are a couple of ways to do this. The first is with Date Aggregation Operators, which allow you to dissect the “date” values in documents. Specifically for “grouping” as the primary intent: db.collection.aggregate([ { “$group”: { “_id”: { “year”: { “$year”: “$created_at” }, “dayOfYear”: { “$dayOfYear”: “$created_at” }, “hour”: { “$hour”: “$created_at” }, “interval”: … Read more
With a modern MongoDB greater than 3.2 you can use $lookup as an alternate to .populate() in most cases. This also has the advantage of actually doing the join “on the server” as opposed to what .populate() does which is actually “multiple queries” to “emulate” a join. So .populate() is not really a “join” in … Read more