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”, “$$id”] }}}, { “$project”: { “scheduleStart”: 1, “scheduleEnd”: 1 }} ], “as”: “user_detail” }} ])
There is the db.getCollectionNames() helper method that does this for you. You can then implement your code: db.getCollectionNames().forEach(function(collname) { // find the last item in a collection var last_element = db[collname].find().sort({_id:-1}).limit(1); // check that it’s not empty if (last_element.hasNext()) { // print its timestamp printjson(last_element.next()._id.getTimestamp()); } }) You probably also want a .hasNext() check in … Read more
I would definitely go with using the $in query and providing a array of _ids. Example: db.collection.find({ “key”: { “$in”: [ ObjectId(“xxx”), ObjectId(“yyy”), ObjectId(“zzz”) ] } }) Why? If you loop, there is a certain amount of setup and teardown for each query creating and exhausting cursors which would create overhead. If you are not … Read more
Assuming that the date_created is in a valid date format along with the timestamp, You should insert the parsed value of date_created using Date.parse() javascript function, which gives the number of milliseconds between January 1, 1970 and date value contained in date_created. As a result of that, the most recently added record will contain greater … Read more
I believe you want imgs.0. eg, given your example document, you want to say: db.products.find({“imgs.0”: “http://foo.jpg”}) Be aware that referencing array indexes only works for the first-level array. Mongo doesn’t support searching array indexes any deeper.
I’ll TL;DR since this turned out to be a hell of a ride. I’ve tried $elemMatch, I’ve tried $redact (also with $$CURRENT and $$ROOT), I’ve tried $map, I’ve tried the aggregation framework, I’ve tried $project. You can read all about it here: https://www.devsbedevin.net/mongodb-find-findone-with-nested-array-filtering-finally/ TL;DR The solution seems to be to use the aggregation framework to … Read more
Personally I am not a big fan of transforming “data” as the names of keys in a result. The aggregation framework principles tend to aggree as this sort of operation is not supported either. So the personal preference is to maintain “data” as “data” and accept that the processed output is actually better and more … Read more
You need to use $filter aggregation to filter out the external origin and internal origin along with the $size aggregation to calculate the length of the arrays. Something like this db.collection.aggregate([ { “$addFields”: { “internalUsersCount”: { “$size”: { “$filter”: { “input”: “$participants”, “as”: “part”, “cond”: { “$eq”: [“$$part.origin”, “internal”]} } } }, “externalUsersCount”: { “$size”: … Read more