There is a way to concat more updates?
For example I would like to change more values in the same element. So having this...
{
cc: [
{ user_id: "1", hasSeen:true}
,{ user_id: "2", hasSeen:false}
,{ user_id: "3", hasSeen:false}
]
,conversation: [{
user_id: "1",
text: "message by 1, to 2and3"
}]
}
...I would like to push a new conversation object and also change all the hasSeen values.
For do the first point, no problem, I just push only a new conversation object. And it works...
...update(
{ _id : _param.conversation_id }
,{ $push:{ conversation:{user_id:"2",text:"message by 2, to 1,3"} }}
)
.exec(function(err, numAffected, rawResponse) {
});
But I would like also to change the three "hasSeen" values in the same time. is it possible?
Can I do it with one query? or i should split it in two queries?
ps: I use mongoose.
Currently the positional operator (which I think you will need here) does not work in such a manner that you can do a type of conditional update whereby you iterate through a list of $incs or $sets to change those subdocument values.
There is a JIRA for such a thing that could possibly help you: https://jira.mongodb.org/browse/SERVER-6566?page=com.atlassian.jira.plugin.system.issuetabpanels:changehistory-tabpanel but it is filed under "features we are not sure of".
Best to split this up currently.
Related
Okay, the title is a bit un-detailed (you could only fit so much in there) but I will explain, so imagine this structure;
{"_id": 123}
Easy right? So what I am doing is adding a field when it does not detect a duplicate, for example if id 123 got the fruit; apple with an amount counter and displaying if it is healthy, then apple will be added into the field, simple, but I'm not done, here it is so far;
{"_id": 123, "Apple": {"Healthy?": "Yes", "amount": 1}}
Now let's say id 123 decides to get him/her a pizza, then the field will once again update;
{"_id": 123, "Apple": {"Healthy?": "Yes", "amount": 1}, "Pizza": {"Healthy?": No, "amount": 1}}
So far, very straightforward, but what if id 123 gets himself another apple? Well also very simple I just used; collection.update({"_id": 123},{"$inc": {"Apple.amount": 1}}) this now turns into;
{"_id": 123, "Apple": {"Healthy?": "Yes", "amount": 2}, "Pizza": {"Healthy?": No, "amount": 1}}
Now if we try to implement both of these together; i.e; detecting if a similar field has been inserted, then update the value, or detect that no fields exist under this id, insert the new data. Right now I have;
try:
collection.update({"_id": user},{"$inc": {f"{thing}.amount": 1}})
except:
collection.update_one({"_id" : user},{"$set":{f"{thing}": idf}})
People who don't know python or doesn't understand this be like; whoa whoa whoa this was a cakewalk until this showed up. Allow me to explain, what is happening is I am getting the user id as {user}, so if user 123 were to use this, then it would be {"_id": "123"} but I have that taken care of, {thing} is the object obtained, if user 123 gets an apple then {thing} would be Apple. In the second update, there is {idf} this is basically how I get the data for each object, having a json store this and pulling the object data and inserting this. Now what this code does right now is it just inserts {"_id": 123, "Apple": {"amount": 1}} if you didn't know, using $inc will create a new field if it does not detect a current field, so it will try to update it, since it succeeds nothing else will happen. What I want this to do is to update the object amount, if it does not manage to detect a file similar to the format, then insert a fresh field with my data on the json. What I have done is try and find the object under the id and then according to that update adaptively, but I have tried so many ways to get this to work, what I thought would work the most is find = collection.find({"_id": user, f"{thing}": {}} ), but it just doesn't work, it doesn't even bother to find anything because there is an error.
Can anyone take a stab at this?
You can use update with aggregation pipeline starting from MongoDB 4.2,
Assume you have the below input data:
user = 123
thing = "Apple"
idf = {
"Healthy?": "Yes",
"amount": 1
}
The query would be,
$cond to check if thing is not missing type
it's not missing then increment amount by $add and merge default properties with an incremented amount using $mergeObjects
if it's missing then add thing new properties
collection.update(
{ '_id': user },
[{
'$set': {
f"{thing}": {
'$cond': [
{ '$ne': [{ '$type': f"${thing}" }, "missing"] },
{
'$mergeObjects': [
f"${thing}",
{ 'amount': { '$add': [f"${thing}.amount", 1] } }
]
},
idf
]
}
}
}]
)
Playground
I have a schema which has one field named ownerId and a field which is an array named participantIds. In the frontend users can select participants. I'm using these ids to filter documents by querying the participantIds with the $all operator and the list of participantsIds from the frontend. This is perfect except that the participantsIds in the document don't include the ownerId. I thought about using aggregate to add a new field which consists of a list like this one: [participantIds, ownerId] and then querying against this new field with $all and after that delete the field again since it isn't need in the frontend.
How would such a query look like or is there any better way to achieve this behavior? I'm really lost right now since I'm trying to implement this with mongo_dart for the last 3 hours.
This is how the schema looks like:
{
_id: ObjectId(),
title: 'Title of the Event',
startDate: '2020-09-09T00:00:00.000',
endDate: '2020-09-09T00:00:00.000',
startHour: 1,
durationHours: 1,
ownerId: '5f57ff55202b0e00065fbd10',
participantsIds: ['5f57ff55202b0e00065fbd14', '5f57ff55202b0e00065fbd15', '5f57ff55202b0e00065fbd13'],
classesIds: [],
categoriesIds: [],
roomsIds: [],
creationTime: '2020-09-10T16:42:14.966',
description: 'Some Desc'
}
Tl;dr I want to query documents with the $all operator on the participantsIds field but the ownerId should be included in this query.
What I want is instead of querying against:
participantsIds: ['5f57ff55202b0e00065fbd14', '5f57ff55202b0e00065fbd15', '5f57ff55202b0e00065fbd13']
I want to query against:
participantsIds: ['5f57ff55202b0e00065fbd14', '5f57ff55202b0e00065fbd15', '5f57ff55202b0e00065fbd13', '5f57ff55202b0e00065fbd10']
Having fun here, by the way, it's better to use Joe answer if you are doing the query frequently, or even better a "All" field on insertion.
Additional Notes: Use projection at the start/end, to get what you need
https://mongoplayground.net/p/UP_-IUGenGp
db.collection.aggregate([
{
"$addFields": {
"all": {
$setUnion: [
"$participantsIds",
[
"$ownerId"
]
]
}
}
},
{
$match: {
all: {
$all: [
"5f57ff55202b0e00065fbd14",
"5f57ff55202b0e00065fbd15",
"5f57ff55202b0e00065fbd13",
"5f57ff55202b0e00065fbd10"
]
}
}
}
])
Didn't fully understand what you want to do but maybe this helps:
db.collection.find({
ownerId: "5f57ff55202b0e00065fbd10",
participantsIds: {
$all: ['5f57ff55202b0e00065fbd14',
'5f57ff55202b0e00065fbd15',
'5f57ff55202b0e00065fbd13']
})
You could use the pipeline form of update to either add the owner to the participant list or add a new consolidated field:
db.collection.update({},[{$set:{
allParticipantsIds: {$setUnion: [
"$participantsIds",
["$ownerId"]
]}
}}])
I am trying to update a value in the nested array but can't get it to work.
My object is like this
{
"_id": {
"$oid": "1"
},
"array1": [
{
"_id": "12",
"array2": [
{
"_id": "123",
"answeredBy": [], // need to push "success"
},
{
"_id": "124",
"answeredBy": [],
}
],
}
]
}
I need to push a value to "answeredBy" array.
In the below example, I tried pushing "success" string to the "answeredBy" array of the "123 _id" object but it does not work.
callback = function(err,value){
if(err){
res.send(err);
}else{
res.send(value);
}
};
conditions = {
"_id": 1,
"array1._id": 12,
"array2._id": 123
};
updates = {
$push: {
"array2.$.answeredBy": "success"
}
};
options = {
upsert: true
};
Model.update(conditions, updates, options, callback);
I found this link, but its answer only says I should use object like structure instead of array's. This cannot be applied in my situation. I really need my object to be nested in arrays
It would be great if you can help me out here. I've been spending hours to figure this out.
Thank you in advance!
General Scope and Explanation
There are a few things wrong with what you are doing here. Firstly your query conditions. You are referring to several _id values where you should not need to, and at least one of which is not on the top level.
In order to get into a "nested" value and also presuming that _id value is unique and would not appear in any other document, you query form should be like this:
Model.update(
{ "array1.array2._id": "123" },
{ "$push": { "array1.0.array2.$.answeredBy": "success" } },
function(err,numAffected) {
// something with the result in here
}
);
Now that would actually work, but really it is only a fluke that it does as there are very good reasons why it should not work for you.
The important reading is in the official documentation for the positional $ operator under the subject of "Nested Arrays". What this says is:
The positional $ operator cannot be used for queries which traverse more than one array, such as queries that traverse arrays nested within other arrays, because the replacement for the $ placeholder is a single value
Specifically what that means is the element that will be matched and returned in the positional placeholder is the value of the index from the first matching array. This means in your case the matching index on the "top" level array.
So if you look at the query notation as shown, we have "hardcoded" the first ( or 0 index ) position in the top level array, and it just so happens that the matching element within "array2" is also the zero index entry.
To demonstrate this you can change the matching _id value to "124" and the result will $push an new entry onto the element with _id "123" as they are both in the zero index entry of "array1" and that is the value returned to the placeholder.
So that is the general problem with nesting arrays. You could remove one of the levels and you would still be able to $push to the correct element in your "top" array, but there would still be multiple levels.
Try to avoid nesting arrays as you will run into update problems as is shown.
The general case is to "flatten" the things you "think" are "levels" and actually make theses "attributes" on the final detail items. For example, the "flattened" form of the structure in the question should be something like:
{
"answers": [
{ "by": "success", "type2": "123", "type1": "12" }
]
}
Or even when accepting the inner array is $push only, and never updated:
{
"array": [
{ "type1": "12", "type2": "123", "answeredBy": ["success"] },
{ "type1": "12", "type2": "124", "answeredBy": [] }
]
}
Which both lend themselves to atomic updates within the scope of the positional $ operator
MongoDB 3.6 and Above
From MongoDB 3.6 there are new features available to work with nested arrays. This uses the positional filtered $[<identifier>] syntax in order to match the specific elements and apply different conditions through arrayFilters in the update statement:
Model.update(
{
"_id": 1,
"array1": {
"$elemMatch": {
"_id": "12","array2._id": "123"
}
}
},
{
"$push": { "array1.$[outer].array2.$[inner].answeredBy": "success" }
},
{
"arrayFilters": [{ "outer._id": "12" },{ "inner._id": "123" }]
}
)
The "arrayFilters" as passed to the options for .update() or even
.updateOne(), .updateMany(), .findOneAndUpdate() or .bulkWrite() method specifies the conditions to match on the identifier given in the update statement. Any elements that match the condition given will be updated.
Because the structure is "nested", we actually use "multiple filters" as is specified with an "array" of filter definitions as shown. The marked "identifier" is used in matching against the positional filtered $[<identifier>] syntax actually used in the update block of the statement. In this case inner and outer are the identifiers used for each condition as specified with the nested chain.
This new expansion makes the update of nested array content possible, but it does not really help with the practicality of "querying" such data, so the same caveats apply as explained earlier.
You typically really "mean" to express as "attributes", even if your brain initially thinks "nesting", it's just usually a reaction to how you believe the "previous relational parts" come together. In reality you really need more denormalization.
Also see How to Update Multiple Array Elements in mongodb, since these new update operators actually match and update "multiple array elements" rather than just the first, which has been the previous action of positional updates.
NOTE Somewhat ironically, since this is specified in the "options" argument for .update() and like methods, the syntax is generally compatible with all recent release driver versions.
However this is not true of the mongo shell, since the way the method is implemented there ( "ironically for backward compatibility" ) the arrayFilters argument is not recognized and removed by an internal method that parses the options in order to deliver "backward compatibility" with prior MongoDB server versions and a "legacy" .update() API call syntax.
So if you want to use the command in the mongo shell or other "shell based" products ( notably Robo 3T ) you need a latest version from either the development branch or production release as of 3.6 or greater.
See also positional all $[] which also updates "multiple array elements" but without applying to specified conditions and applies to all elements in the array where that is the desired action.
I know this is a very old question, but I just struggled with this problem myself, and found, what I believe to be, a better answer.
A way to solve this problem is to use Sub-Documents. This is done by nesting schemas within your schemas
MainSchema = new mongoose.Schema({
array1: [Array1Schema]
})
Array1Schema = new mongoose.Schema({
array2: [Array2Schema]
})
Array2Schema = new mongoose.Schema({
answeredBy": [...]
})
This way the object will look like the one you show, but now each array are filled with sub-documents. This makes it possible to dot your way into the sub-document you want. Instead of using a .update you then use a .find or .findOne to get the document you want to update.
Main.findOne((
{
_id: 1
}
)
.exec(
function(err, result){
result.array1.id(12).array2.id(123).answeredBy.push('success')
result.save(function(err){
console.log(result)
});
}
)
Haven't used the .push() function this way myself, so the syntax might not be right, but I have used both .set() and .remove(), and both works perfectly fine.
I have a collection which elements can be simplified to this:
{tags : [1, 5, 8]}
where there would be at least one element in array and all of them should be different. I want to substitute one tag for another and I thought that there would not be a problem. So I came up with the following query:
db.colll.update({
tags : 1
},{
$pull: { tags: 1 },
$addToSet: { tags: 2 }
}, {
multi: true
})
Cool, so it will find all elements which has a tag that I do not need (1), remove it and add another (2) if it is not there already. The problem is that I get an error:
"Cannot update 'tags' and 'tags' at the same time"
Which basically means that I can not do pull and addtoset at the same time. Is there any other way I can do this?
Of course I can memorize all the IDs of the elements and then remove tag and add in separate queries, but this does not sound nice.
The error is pretty much what it means as you cannot act on two things of the same "path" in the same update operation. The two operators you are using do not process sequentially as you might think they do.
You can do this with as "sequential" as you can possibly get with the "bulk" operations API or other form of "bulk" update though. Within reason of course, and also in reverse:
var bulk = db.coll.initializeOrderedBulkOp();
bulk.find({ "tags": 1 }).updateOne({ "$addToSet": { "tags": 2 } });
bulk.find({ "tags": 1 }).updateOne({ "$pull": { "tags": 1 } });
bulk.execute();
Not a guarantee that nothing else will try to modify,but it is as close as you will currently get.
Also see the raw "update" command with multiple documents.
If you're removing and adding at the same time, you may be modeling a 'map', instead of a 'set'. If so, an object may be less work than an array.
Instead of data as an array:
{ _id: 'myobjectwithdata',
data: [{ id: 'data1', important: 'stuff'},
{ id: 'data2', important: 'more'}]
}
Use data as an object:
{ _id: 'myobjectwithdata',
data: { data1: { important: 'stuff'},
data2: { important: 'more'} }
}
The one-command update is then:
db.coll.update(
'myobjectwithdata',
{ $set: { 'data.data1': { important: 'treasure' } }
);
Hard brain working for this answer done here and here.
Starting in Mongo 4.4, the $function aggregation operator allows applying a custom javascript function to implement behaviour not supported by the MongoDB Query Language.
And coupled with improvements made to db.collection.update() in Mongo 4.2 that can accept an aggregation pipeline, allowing the update of a field based on its own value,
We can manipulate and update an array in ways the language doesn't easily permit:
// { "tags" : [ 1, 5, 8 ] }
db.collection.updateMany(
{ tags: 1 },
[{ $set:
{ "tags":
{ $function: {
body: function(tags) { tags.push(2); return tags.filter(x => x != 1); },
args: ["$tags"],
lang: "js"
}}
}
}]
)
// { "tags" : [ 5, 8, 2 ] }
$function takes 3 parameters:
body, which is the function to apply, whose parameter is the array to modify. The function here simply consists in pushing 2 to the array and filtering out 1.
args, which contains the fields from the record that the body function takes as parameter. In our case, "$tag".
lang, which is the language in which the body function is written. Only js is currently available.
In case you need replace one value in an array to another check this answer:
Replace array value using arrayFilters
Assuming I have the following document structures:
> db.logs.find()
{
'id': ObjectId("50ad8d451d41c8fc58000003")
'name': 'Sample Log 1',
'uploaded_at: ISODate("2013-03-14T01:00:00+01:00"),
'case_id: '50ad8d451d41c8fc58000099',
'tag_doc': {
'group_x: ['TAG-1','TAG-2'],
'group_y': ['XYZ']
}
},
{
'id': ObjectId("50ad8d451d41c8fc58000004")
'name': 'Sample Log 2',
'uploaded_at: ISODate("2013-03-15T01:00:00+01:00"),
'case_id: '50ad8d451d41c8fc58000099'
'tag_doc': {
'group_x: ['TAG-1'],
'group_y': ['XYZ']
}
}
> db.cases.findOne()
{
'id': ObjectId("50ad8d451d41c8fc58000099")
'name': 'Sample Case 1'
}
Is there a way to perform a $match in aggregation framework that will retrieve only all the latest Log for each unique combination of case_id and group_x? I am sure this can be done with multiple $group pipeline but as much as possible, I want to immediately limit the number of documents that will pass through the pipeline via the $match operator. I am thinking of something like the $max operator except it is used in $match.
Any help is very much appreciated.
Edit:
So far, I can come up with the following:
db.logs.aggregate(
{$match: {...}}, // some match filters here
{$project: {tag:'$tag_doc.group_x', case:'$case_id', latest:{uploaded_at:1}}},
{$unwind: '$tag'},
{$group: {_id:{tag:'$tag', case:'$case'}, latest: {$max:'$latest'}}},
{$group: {_id:'$_id.tag', total:{$sum:1}}}
)
As I mentioned, what I want can be done with multiple $group pipeline but this proves to be costly when handling large number of documents. That is why, I wanted to limit the documents as early as possible.
Edit:
I still haven't come up with a good solution so I am thinking if the document structure itself is not optimized for my use-case. Do I have to update the fields to support what I want to achieve? Suggestions very much appreciated.
Edit:
I am actually looking for an implementation in mongodb similar to the one expected in How can I SELECT rows with MAX(Column value), DISTINCT by another column in SQL? except it involves two distinct field values. Also, the $match operation is crucial because it makes the resulting set dynamic, with filters ranging to matching tags or within a range of dates.
Edit:
Due to the complexity of my use-case I tried to use a simple analogy but this proves to be confusing. Above is now the simplified form of the actual use case. Sorry for the confusion I created.
I have done something similar. But it's not possible with match, but only with one group pipeline. The trick is do use multi key with correct sorting:
{ user_id: 1, address: "xyz", date_sent: ISODate("2013-03-14T01:00:00+01:00"), message: "test" }, { user_id: 1, address: "xyz2", date_sent: ISODate("2013-03-14T01:00:00+01:00"), message: "test" }
if i wan't to group on user_id & address and i wan't the message with the latest date we need to create a key like this:
{ user_id:1, address:1, date_sent:-1 }
then you are able to perform aggregate without sort, which is much faster and will work on shards with replicas. if you don't have a key with correct sort order you can add a sort pipeline, but then you can't use it with shards, because all that is transferred to mongos and grouping is done their (also will get memory limit problems)
db.user_messages.aggregate(
{ $match: { user_id:1 } },
{ $group: {
_id: "$address",
count: { $sum : 1 },
date_sent: { $max : "$date_sent" },
message: { $first : "$message" },
} }
);
It's not documented that it should work like this - but it does. We use it on production system.
I'd use another collection to 'create' the search results on the fly - as new posts are posted - by upserting a document in this new collection every time a new blog post is posted.
Every new combination of author/tags is added as a new document in this collection, whereas a new post with an existing combination just updates an existing document with the content (or object ID reference) of the new blog post.
Example:
db.searchResult.update(
... {'author_id':'50ad8d451d41c8fc58000099', 'tag_doc.tags': ["TAG-1", "TAG-2" ]},
... { $set: { 'Referenceid':ObjectId("5152bc79e8bf3bc79a5a1dd8")}}, // or embed your blog post here
... {upsert:true}
)
Hmmm, there is no good way of doing this optimally in such a manner that you only need to pick out the latest of each author, instead you will need to pick out all documents, sorted, and then group on author:
db.posts.aggregate([
{$sort: {created_at:-1}},
{$group: {_id: '$author_id', tags: {$first: '$tag_doc.tags'}}},
{$unwind: '$tags'},
{$group: {_id: {author: '$_id', tag: '$tags'}}}
]);
As you said this is not optimal however, it is all I have come up with.
If I am honest, if you need to perform this query often it might actually be better to pre-aggregate another collection that already contains the information you need in the form of:
{
_id: {},
author: {},
tag: 'something',
created_at: ISODate(),
post_id: {}
}
And each time you create a new post you seek out all documents in this unqiue collection which fullfill a $in query of what you need and then update/upsert created_at and post_id to that collection. This would be more optimal.
Here you go:
db.logs.aggregate(
{"$sort" : { "uploaded_at" : -1 } },
{"$match" : { ... } },
{"$unwind" : "$tag_doc.group_x" },
{"$group" : { "_id" : { "case" :'$case_id', tag:'$tag_doc.group_x'},
"latest" : { "$first" : "$uploaded_at"},
"Name" : { "$first" : "$Name" },
"tag_doc" : { "$first" : "$tag_doc"}
}
}
);
You want to avoid $max when you can $sort and take $first especially if you have an index on uploaded_at which would allow you to avoid any in memory sorts and reduce the pipeline processing costs significantly. Obviously if you have other "data" fields you would add them along with (or instead of) "Name" and "tag_doc".