Two documents containing ObjectId("6148a371c13a6a0be492ebf4")
Document 1
{
"_id" : ObjectId("6144f66fb9543917f96fc"),
"refId" : "ford",
"template" : "6144f61cb96d772317f96f9",
"fieldValues" : {
"PDV" : [
"6126938cd24a8aa3d37b4992",
ObjectId("6148a371c13a6a0be492ebf4")
]
},
"group" : ObjectId("6144f66fb96d7731917f96fd"),
"createdAt" : ISODate("2021-09-17T20:11:27.440Z"),
"updatedAt" : ISODate("2021-09-20T15:06:26.146Z"),
"__v" : 0
}
Document 2
{
"_id" : ObjectId("6144f66fb96d77rr3217f96fc"),
"refId" : "CCM",
"template" : "6144f613296d7731917f96f9",
"fieldValues" : {
"DDB" : [
"6126938cd2448aa3d37b4992",
"5443938cd2448aa3d37b4992",
ObjectId("6148a371c13a6a0be492ebf4"),
]
},
"group" : ObjectId("6144f66fb96de431917f96fd"),
"createdAt" : ISODate("2021-09-17T20:11:27.440Z"),
"updatedAt" : ISODate("2021-09-20T15:06:26.146Z"),
"__v" : 0
}
ObjectId that we looking for is always inside fieldValues but instead of PDV or DDB we will always have the different naming.
So we can't use this type of query:
db.getCollection('products').find({"fieldValues.PDV":ObjectId('6148a371c13a6a0be492ebf4')})
PS. This query should work only on DB, we can't afford to query all products and do calculation on backend there might to be a millions of products.
You can use this one:
db.collection.aggregate([
{
$set: {
kv: { $first: { $objectToArray: "$fieldValues" } }
}
},
{ $match: { "kv.v": ObjectId("6148a371c13a6a0be492ebf3") } },
{ $unset: "kv" }
])
Mongo Playground
db.products.find({'_id': ObjectId("6148a371c13a6a0be492ebf4")})
The mistake in your code is that you used key instead of _id.
This way of writing it is much easier on the fingers though.
You'd think a solution like this would work but one reason why this may not is because you're trying to use === on an object. If you refer to this thread, it might help if you use .equals() instead of ===.
Related
Hi i am mentioning the sample data
///collection - test////
{
"_id" : {
"date" : ISODate("2020-02-11T17:00:00Z"),
"userId" : ObjectId("5e43e5cdc11f750864f46820"),
"adminId" : ObjectId("5e43de778b57693cd46859eb")
},
"outstanding" : 212.39999999999998,
"totalBill" : 342.4,
"totalPayment" : 130
}
{
"_id" : {
"date" : ISODate("2020-02-11T17:00:00Z"),
"userId" : ObjectId("5e43e73169fe1e3fc07eb7c5"),
"adminId" : ObjectId("5e43de778b57693cd46859eb")
},
"outstanding" : 797.8399999999999,
"totalBill" : 797.8399999999999,
"totalPayment" : 0
}
I need to structure a query which does following things-
I need to calculate the actualOutstanding:[(totalBill+outstanding)-totalPayment],
I need to save this actualOutstanding in the same collection & in the same document according to {"_id" : {"date","userId", "adminId" }}
NOTE: userId is different in both the documents.
Introduced in Mongo version 4.2+ pipelined updates, meaning we can now use aggregate expressions to update documents.
db.collection.updateOne(
{
"adminId" : ObjectId("5e43de778b57693cd46859eb")
'_id."userId" : ObjectId("5e43e73169fe1e3fc07eb7c5"),
'_id.date': ISODate("2020-02-11T18:30:00Z"),
},
[
{ '$set': {
actualOutstanding: {
$subtract:[ {$add: ['$totalBill','$outstanding']},'$totalPayment']
}
} }
]);
For any other Mongo version you have to split it into 2 actions, first query and calculate then update the document with the calculation.
I want to update a comment in a post. I first retrieve the post document which looks like this.
{
"_id" : ObjectId("5aac169c229f0136296407d4"),
"title" : "First Node.js App",
"body" : "testing 123",
"status" : "public",
"user" : "John Doe",
"date" : ISODate("2017-12-21T18:30:09.779Z"),
"comments" : [
{
"commentBody" : "This is awesome! ",
"commentUser" : ObjectId("5a3bfd5a9e65351f9c18ba18"),
"_id" : ObjectId("5a3c02379e65351f9c18ba1a"),
"commentDate" : ISODate("2017-12-21T18:49:27.620Z")
},
{
"commentBody" : "This is second comment.",
"commentUser" : ObjectId("5a3bfd5a9e65351f9c18gt19"),
"_id" : ObjectId("5a3c02379e65351f9c18ba1b"),
"commentDate" : ISODate("2017-12-21T18:49:27.620Z")
}
],
"allowComments" : true
}
Let say I want to update comment with "_id" ObjectId("5a3c02379e65351f9c18ba1a").
I've tried the following without luck.
const post = await Post.findById(req.body.postID);
await post.update({'comments._id' : req.body.commentID},{$set : {
'comments.$.commentBody': req.body.comment
}
});
This gave me the following error:
MongoError: cannot use the part (comments of comments._id) to traverse the element
Any suggestion would be greatly appreciated. Thanks in advance!
You can try something like this::
Post.findOneAndUpdate(
{ "_id": req.body.postID, "comments._id": req.body.commentID },
{
"$set": {
'comments.$.commentBody': req.body.comment
}
},
function(err,doc) {
}
);
I'm not sure about how to implement this in node.js but here is the Mongo query:
db.sample.aggregate([
{$match:{"comments.commentUser":ObjectId("5a3bfd5a9e65351f9c18ba19")}},
{$redact:{
$cond:{
if:{$or:[{$eq:["$commentUser",ObjectId("5a3bfd5a9e65351f9c18ba19")]},
{$not:"$commentUser"}]},
then:"$$DESCEND",
else:"$$PRUNE"
}
}},
{$addFields:{comments:{$map:{
input:"$comments",
as:"comment",
in:{"commentBody":"test comment", "commentUser" : "$$comment.commentUser", "_id" :"$$comment._id", "commentDate" :"$$comment.commentDate"}
}}
}},
{$out:"sample"}
])
Restricted the document such that only particular user id comments are displayed. After that, added comments with updated comment. Finally replacing the original content within aggregation without update query(note that collection will get replaced if you run the query). I didnt test this extensively, but working for small data set in my local. However, you might need to add some tweaks to this query and then check how u can add same query to node.js
In Node with Mongoose I want to find an object in the collection Content. It has a list of sub-documents called users which has the properties stream, user and added. I do this to get all documents with a certain user's _id property in there users.user field.
Content.find( { 'users.user': user._id } ).sort( { 'users.added': -1 } )
This seems to work (although I'm unsure if .sort is really working here. However, I want to match two fields, like this:
Content.find( { 'users.user': user._id, 'users.stream': stream } } ).sort( { 'users.added': -1 } )
That does not seem to work. What is the right way to do this?
Here is a sample document
{
"_id" : ObjectId("551c6b37859e51fb9e9fde83"),
"url" : "https://www.youtube.com/watch?v=f9v_XN7Wxh8",
"title" : "Playing Games in 360°",
"date" : "2015-03-10T00:19:53.000Z",
"author" : "Econael",
"description" : "Blinky is a proof of concept of enhanced peripheral vision in video games, showcasing different kinds of lens projections in Quake (a mod of Fisheye Quake, using the TyrQuake engine).\n\nDemo and additional info here:\nhttps://github.com/shaunlebron/blinky\n\nThanks to #shaunlebron for making this very interesting proof of concept!\n\nSubscribe: http://www.youtube.com/subscription_center?add_user=econaelgaming\nTwitter: https://twitter.com/EconaelGaming",
"duration" : 442,
"likes" : 516,
"dislikes" : 13,
"views" : 65568,
"users" : [
{
"user" : "54f6688c55407c0300b883f2",
"added" : 1427925815190,
"_id" : ObjectId("551c6b37859e51fb9e9fde84"),
"tags" : []
}
],
"images" : [
{
"hash" : "1ab544648d7dff6e15826cda7a170ddb",
"thumb" : "...",
"orig" : "..."
}
],
"tags" : [],
"__v" : 0
}
Use $elemMatch operator to specify multiple criteria on an array of embedded documents:
Content.find({"users": {$elemMatch: {"user": user.id, "stream": stream}}});
So I have this document within the course collection
{
"_id" : ObjectId("53580ff62e868947708073a9"),
"startDate" : ISODate("2014-04-23T19:08:32.401Z"),
"scoreId" : ObjectId("531f28fd495c533e5eaeb00b"),
"rewardId" : null,
"type" : "certificationCourse",
"description" : "This is a description",
"name" : "testingAutoSteps1",
"authorId" : ObjectId("532a121e518cf5402d5dc276"),
"steps" : [
{
"name" : "This is a step",
"description" : "This is a description",
"action" : "submitCategory",
"value" : "532368bc2ab8b9182716f339",
"statusId" : ObjectId("5357e26be86f746b68482c8a"),
"_id" : ObjectId("53580ff62e868947708073ac"),
"required" : true,
"quantity" : 1,
"userId" : [
ObjectId("53554b56e3a1e1dc17db903f")
]
},...
And I want to do is create a query that returns all courses that have a specific userId in the userId array that is in the steps array for a specific userId. I've tried using $elemMatch like so
Course.find({
"steps": {
"$elemMatch": {
"userId": {
"$elemMatch": "53554b56e3a1e1dc17db903f"
}
}
}
},
But It seems to be returning a empty document.
I think this will work for you, you have the syntax off a bit plus you need to use ObjectId():
db.Course.find({ steps : { $elemMatch: { userId:ObjectId("53554b56e3a1e1dc17db903f")} } })
The $elemMatch usage is not necessary unless you actually have compound sub-documents in that nested array element. And also is not necessary unless the value being referenced could possibly duplicate in another compound document.
Since this is an ObjectId we are talking about, then it's going to be unique, at least within this array. So just use the "dot-notation" form:
Course.find({
"steps.userId": ObjectId("53554b56e3a1e1dc17db903f")
},
Go back and look at the $elemMatch documentation. In this case, the direct "dot-notation" form is all you need
in my collection each document has 2 dates, modified and sync. I would like to find those which modified > sync, or sync does not exist.
I tried
{'modified': { $gt : 'sync' }}
but it's not showing what I expected. Any ideas?
Thanks
You can not compare a field with the value of another field with the normal query matching. However, you can do this with the aggregation framework:
db.so.aggregate( [
{ $match: …your normal other query… },
{ $match: { $eq: [ '$modified', '$sync' ] } }
] );
I put …your normal other query… in there as you can make that bit use the index. So if you want to do this for only documents where the name field is charles you can do:
db.so.ensureIndex( { name: 1 } );
db.so.aggregate( [
{ $match: { name: 'charles' } },
{ $project: {
modified: 1,
sync: 1,
name: 1,
eq: { $cond: [ { $gt: [ '$modified', '$sync' ] }, 1, 0 ] }
} },
{ $match: { eq: 1 } }
] );
With the input:
{ "_id" : ObjectId("520276459bf0f0f3a6e4589c"), "modified" : 73845345, "sync" : 73234 }
{ "_id" : ObjectId("5202764f9bf0f0f3a6e4589d"), "modified" : 4, "sync" : 4 }
{ "_id" : ObjectId("5202765b9bf0f0f3a6e4589e"), "modified" : 4, "sync" : 4, "name" : "charles" }
{ "_id" : ObjectId("5202765e9bf0f0f3a6e4589f"), "modified" : 4, "sync" : 45, "name" : "charles" }
{ "_id" : ObjectId("520276949bf0f0f3a6e458a1"), "modified" : 46, "sync" : 45, "name" : "charles" }
This returns:
{
"result" : [
{
"_id" : ObjectId("520276949bf0f0f3a6e458a1"),
"modified" : 46,
"sync" : 45,
"name" : "charles",
"eq" : 1
}
],
"ok" : 1
}
If you want any more fields, you need to add them in the $project.
For MongoDB 3.6 and newer:
The $expr operator allows the use of aggregation expressions within the query language, thus you can do the following:
db.test.find({ "$expr": { "$gt": ["$modified", "$sync"] } })
or using aggregation framework with $match pipeline
db.test.aggregate([
{ "$match": { "$expr": { "$gt": ["$modified", "$sync"] } } }
])
For MongoDB 3.0+:
You can also use the aggregation framework with the $redact pipeline operator that allows you to process the logical condition with the $cond operator and uses the special operations $$KEEP to "keep" the document where the logical condition is true or $$PRUNE to "remove" the document where the condition was false.
Consider running the following aggregate operation which demonstrates the above concept:
db.test.aggregate([
{ "$redact": {
"$cond": [
{ "$gt": ["$modified", "$sync"] },
"$$KEEP",
"$$PRUNE"
]
} }
])
This operation is similar to having a $project pipeline that selects the fields in the collection and creates a new field that holds the result from the logical condition query and then a subsequent $match, except that $redact uses a single pipeline stage which is more efficient:
Simply
db.collection.find({$where:"this.modified>this.sync"})
Example
Kobkrits-MacBook-Pro-2:~ kobkrit$ mongo
MongoDB shell version: 3.2.3
connecting to: test
> db.time.insert({d1:new Date(), d2: new Date(new Date().getTime()+10000)})
WriteResult({ "nInserted" : 1 })
> db.time.find()
{ "_id" : ObjectId("577a619493653ac93093883f"), "d1" : ISODate("2016-07-04T13:16:04.167Z"), "d2" : ISODate("2016-07-04T13:16:14.167Z") }
> db.time.find({$where:"this.d1<this.d2"})
{ "_id" : ObjectId("577a619493653ac93093883f"), "d1" : ISODate("2016-07-04T13:16:04.167Z"), "d2" : ISODate("2016-07-04T13:16:14.167Z") }
> db.time.find({$where:"this.d1>this.d2"})
> db.time.find({$where:"this.d1==this.d2"})
>
Use Javascript, use foreach And convert Date To toDateString()
db.ledgers.find({}).forEach(function(item){
if(item.fromdate.toDateString() == item.todate.toDateString())
{
printjson(item)
}
})
Right now your query is trying to return all results such that the modified field is greater than the word 'sync'. Try getting rid of the quotes around sync and see if that fixes anything. Otherwise, I did a little research and found this question. What you're trying to do just might not be possible in a single query, but you should be able to manipulate your data once you pull everything from the database.
To fix this issue without aggregation change your query to this:
{'modified': { $gt : ISODate(this.sync) }}