Starting from MongoDB 3.4, you can use the $type aggregation operator to return a field’s type. db.posts.aggregate( [ { “$project”: { “fieldType”: { “$type”: “$date2” } } } ] ) which yields: { “_id” : ObjectId(“4c0ec11e8fd2e65c0b010000”), “fieldType” : “string” }
Add Stage 2.5 😛 { $project:{ FileName:1, FileSize:{$substr:[“$FileSize”, 0, -1 ]} } } FileSize is a integer and there is no operation to convert it to String. So you can use hack, and use substr to convert it to string, 0 for starting and -1 rest of the string.
You can use $lookup 3.6 syntax to $project the fields inside the $lookup pipeline User.aggregate([ { “$lookup”: { “from”: “schedules”, “let”: { “id”: “$_id.phone” }, “pipeline”: [ { “$match”: { “$expr”: { “$eq”: [“$customer.phone”, “$$id”] }}}, { “$project”: { “scheduleStart”: 1, “scheduleEnd”: 1 }} ], “as”: “user_detail” }} ])
As the docs you quote indicate, you can’t use $lookup on a sharded collection. So the best practice workaround is to perform the lookup yourself in a separate query. Perform your aggregate query. Pull the “localField” values from your query results into an array, possibly using Array#map. Perform a find query against the “from” collection, … Read more
I’ll TL;DR since this turned out to be a hell of a ride. I’ve tried $elemMatch, I’ve tried $redact (also with $$CURRENT and $$ROOT), I’ve tried $map, I’ve tried the aggregation framework, I’ve tried $project. You can read all about it here: https://www.devsbedevin.net/mongodb-find-findone-with-nested-array-filtering-finally/ TL;DR The solution seems to be to use the aggregation framework to … Read more
When I had a moment to think about this, I ran back home to perl and worked this out: use Modern::Perl; use Moose::Autobox; use JSON; my $encoder = JSON->new->pretty; my $input = [ { 4 => 10 }, { 7 => 9 }, { 90 => 7 }, { 1 => 8 } ]; my … Read more
Personally I am not a big fan of transforming “data” as the names of keys in a result. The aggregation framework principles tend to aggree as this sort of operation is not supported either. So the personal preference is to maintain “data” as “data” and accept that the processed output is actually better and more … Read more
You need to use $filter aggregation to filter out the external origin and internal origin along with the $size aggregation to calculate the length of the arrays. Something like this db.collection.aggregate([ { “$addFields”: { “internalUsersCount”: { “$size”: { “$filter”: { “input”: “$participants”, “as”: “part”, “cond”: { “$eq”: [“$$part.origin”, “internal”]} } } }, “externalUsersCount”: { “$size”: … Read more
Let say we have the following documents in our collection: { “_id” : ObjectId(“5759658e654456bf4a014d01”), “a” : [ 1, 3, 9, 2, 9, 0 ] } { “_id” : ObjectId(“5759658e654456bf4a014d02”), “a” : [ 0, 8, 1 ] } { “_id” : ObjectId(“5759658e654456bf4a014d03”), “a” : [ 0, 8, 432, 9, 34, -3 ] } { “_id” : … Read more
Querying this structure for the results you want is not possible without knowing all of the possible forms names beforehand, and using them in the query. It would be very messy at any rate. That said, read on as I explain how it can be done. There is a problem with the structure of these … Read more