I have a user model like this:
user : {
myArmy : {
mySoldiers : [
{
positioned : false,
soldierInfo : {
_id : s99212
}
},
{
positioned : true,
soldierInfo : {
_id : s99112
}
}
]
}
},
user : {
myArmy : {
mySoldiers : [
{
positioned : true,
soldierInfo : {
_id : s99212
}
},
{
positioned : false,
soldierInfo : {
_id : s99112
}
}
]
}
}
...
I have a query that i want to do to return the user(s) who have soldier id s99212 positioned (true): (could be thousands of those, and i need to read and retrieve them all)
This is my faulty query with mongoose:
var soldierId = s99212;
stream = User.find({
$and: [
{'myArmy.mySoldier.positioned': {$ne: null}},
{'myArmy.mySoldier.soldierInfo._id': soldierId}
]
}).lean(true).stream();
Nothing is returned by this query, should there be another way to do this $and stuff?
How exactly am i suppose to use $elemMatch if at all, should it be instead of the find? (If it worth to mention, i want to return the complete user object, not just parts of it...)
Tried this, crashed my app:
stream = User.find({
'$elemMatch': [
{'myArmy.mySoldiers.pos': {$ne: null}},
{'myArmy.mySoldiers.soldierInfo._id': soldierId}
]
}).lean(true).stream();
I know i have a small syntax problem, where is it?
Very simple and well documented. The $elemMatch operator acts as a "query in itself", where it applies "it's conditions" to members of the array specified:
var query = User.find({
"myArmy.mySoldiers": {
"$elemMatch": {
"positioned": { "$ne": null },
"soldierInfo._id": soldierId
}
}
});
Therefore for a document to "match" then the conditions specfied under $elemMatch must be present and valid for the "same" array element. Array on "left", arguments on "right".
Other "dot notation" forms only ever test that the values match "some element" in the array, and not necessarily the same one.
Related
I have a JSON in MongoDB and I am trying to check if at least one of the items in the JSON doesn't contain a specific field.
{
"_id" : 12345,
"orderItems" : [
{
"itemId" : 45678,
"isAvailable" : true,
"isEligible" " false
},
{
"itemId" : 87653,
"isAvailable" : true
}
]
}
So in the above JSON, since the 2nd one under order items doesn't contain iseligible field, I need to get this _id.
I tried the below query so far, which didnt work:
db.getCollection('orders').find({"orderItems.iseligible":{$exists:false})
You can use $elemMatch to evaluate the presence of the nested key. Once that's accomplished, project out the _id value.
db.orders.find({
orderItems: {
$elemMatch: {
"isEligible": {
$exists: false
}
}
}
},
{
_id: 1
})
Here is a Mongo playground with the finished code, and a similar SO answer.
In my mongodb (using Mongoose), I have story collection which has comments sub collection and I want to query the subdocument by client id, as
Story.find({ 'comments.client': id }, { title: 1, 'comments.$': 1 }, function (err, stories) {
...
})
})
The query works except that it only returns the first matched subdocument, but I want it to return all matching subdocuments. Did I miss an option?
EDIT:
On Blakes Seven's tip, I tried the answers from Retrieve only the queried element in an object array in MongoDB collection, but I couldn't make it work.
First tried this:
Story.find({'comments.client': id}, { title: 1, comments: {$elemMatch: { client: id } } }, function (err, stories) {
})
It also returns the first match only.
Then, I tried the accepted answer there:
Story.aggregate({$match: {'comments.client': id} }, {$unwind: '$comments'}, {$match : {'comments.client': id} }, function (err, stories) {
})
but this returns nothing. What is wrong here?
UPDATE:
My data structure looks like this:
{
"_id" : ObjectId("55e2185288fee5a433ceabf5"),
"title" : "test",
"comments" : [
{
"_id" : ObjectId("55e2184e88fee5a433ceaaf5"),
"client" : ObjectId("55e218446033de4e7db3f2a4"),
"time" : ISODate("2015-08-29T20:16:00.000Z")
}
]
}
Is it possible to aggregate on data that is stored via DBRef?
Mongo 2.6
Let's say I have transaction data like:
{
_id : ObjectId(...),
user : DBRef("user", ObjectId(...)),
product : DBRef("product", ObjectId(...)),
source : DBRef("website", ObjectId(...)),
quantity : 3,
price : 40.95,
total_price : 122.85,
sold_at : ISODate("2015-07-08T09:09:40.262-0700")
}
The trick is "source" is polymorphic in nature - it could be different $ref values such as "webpage", "call_center", etc that also have different ObjectIds. For example DBRef("webpage", ObjectId("1")) and DBRef("webpage",ObjectId("2")) would be two different webpages where a transaction originated.
I would like to ultimately aggregate by source over a period of time (like a month):
db.coll.aggregate( { $match : { sold_at : { $gte : start, $lt : end } } },
{ $project : { source : 1, total_price : 1 } },
{ $group : {
_id : { "source.$ref" : "$source.$ref" },
count : { $sum : $total_price }
} } );
The trick is you get a path error trying to use a variable starting with $ either by trying to group by it or by trying to transform using expressions via project.
Any way to do this? Actually trying to push this data via aggregation to a subcollection to operate on it there. Trying to avoid a large cursor operation over millions of records to transform the data so I can aggregate it.
Mongo 4. Solved this issue in the following way:
Having this structure:
{
"_id" : LUUID("144e690f-9613-897c-9eab-913933bed9a7"),
"owner" : {
"$ref" : "person",
"$id" : NumberLong(10)
},
...
...
}
I needed to use "owner.$id" field. But because of "$" in the name of field, I was unable to use aggregation.
I transformed "owner.$id" -> "owner" using following snippet:
db.activities.find({}).aggregate([
{
$addFields: {
"owner": {
$arrayElemAt: [{ $objectToArray: "$owner" }, 1]
}
}
},
{
$addFields: {
"owner": "$owner.v"
}
},
{"$group" : {_id:"$owner", count:{$sum:1}}},
{$sort:{"count":-1}}
])
Detailed explanations here - https://dev.to/saurabh73/mongodb-using-aggregation-pipeline-to-extract-dbref-using-lookup-operator-4ekl
You cannot use DBRef values with the aggregation framework. Instead you need to use JavasScript processing of mapReduce in order to access the property naming that they use:
db.coll.mapReduce(
function() {
emit( this.source.$ref, this["total_price"] )
},
function(key,values) {
return Array.sum( values );
},
{
"query": { "sold_at": { "$gte": start, "$lt": end } },
"out": { "inline": 1 }
}
)
You really should not be using DBRef at all. The usage is basically deprecated now and if you feel you need some external referencing then you should be "manually referencing" this with your own code or implemented by some other library, with which you can do so in a much more supported way.
Is there a way to conditionally $addToSet based on a specific key field in a subdocument on an array?
Here's an example of what I mean - given the collection produced by the following sample bootstrap;
cls
db.so.remove();
db.so.insert({
"Name": "fruitBowl",
"pfms" : [
{
"n" : "apples"
}
]
});
n defines a unique document key. I only want one entry with the same n value in the array at any one time. So I want to be able to update the pfms array using n so that I end up with just this;
{
"Name": "fruitBowl",
"pfms" : [
{
"n" : "apples",
"mState": 1111234
}
]
}
Here's where I am at the moment;
db.so.update({
"Name": "fruitBowl",
},{
// not allowed to do this of course
// "$pull": {
// "pfms": { n: "apples" },
// },
"$addToSet": {
"pfms": {
"$each": [
{
"n": "apples",
"mState": 1111234
}
]
}
}
}
)
Unfortunately, this adds another array element;
db.so.find().toArray();
[
{
"Name" : "fruitBowl",
"_id" : ObjectId("53ecfef5baca2b1079b0f97c"),
"pfms" : [
{
"n" : "apples"
},
{
"n" : "apples",
"mState" : 1111234
}
]
}
]
I need to effectively upsert the apples document matching on n as the unique identifier and just set mState whether or not an entry already exists. It's a shame I can't do a $pull and $addToSet in the same document (I tried).
What I really need here is dictionary semantics, but that's not an option right now, nor is breaking out the document - can anyone come up with another way?
FWIW - the existing format is a result of language/driver serialization, I didn't choose it exactly.
further
I've gotten a little further in the case where I know the array element already exists I can do this;
db.so.update({
"Name": "fruitBowl",
"pfms.n": "apples",
},{
$set: {
"pfms.$.mState": 1111234,
},
}
)
But of course that only works;
for a single array element
as long as I know it exists
The first limitation isn't a disaster, but if I can't effectively upsert or combine $addToSet with the previous $set (which of course I can't) then it the only workarounds I can think of for now mean two DB round-trips.
The $addToSet operator of course requires that the "whole" document being "added to the set" is in fact unique, so you cannot change "part" of the document or otherwise consider it to be a "partial match".
You stumbled on to your best approach using $pull to remove any element with the "key" field that would result in "duplicates", but of course you cannot modify the same path in different update operators like that.
So the closest thing you will get is issuing separate operations but also doing that with the "Bulk Operations API" which is introduced with MongoDB 2.6. This allows both to be sent to the server at the same time for the closest thing to a "contiguous" operations list you will get:
var bulk = db.so.initializeOrderedBulkOp();
bulk.find({ "Name": "fruitBowl", "pfms.n": "apples": }).updateOne({
"$pull": { "pfms": { "n": "apples" } }
});
bulk.find({ "Name": "fruitBowl" }).updateOne({
"$push": { "pfms": { "n": "apples", "state": 1111234 } }
})
bulk.execute();
That pretty much is your best approach if it is not possible or practical to move the elements to another collection and rely on "upserts" and $set in order to have the same functionality but on a collection rather than array.
I have faced the exact same scenario. I was inserting and removing likes from a post.
What I did is, using mongoose findOneAndUpdate function (which is similar to update or findAndModify function in mongodb).
The key concept is
Insert when the field is not present
Delete when the field is present
The insert is
findOneAndUpdate({ _id: theId, 'likes.userId': { $ne: theUserId }},
{ $push: { likes: { userId: theUserId, createdAt: new Date() }}},
{ 'new': true }, function(err, post) { // do the needful });
The delete is
findOneAndUpdate({ _id: theId, 'likes.userId': theUserId},
{ $pull: { likes: { userId: theUserId }}},
{ 'new': true }, function(err, post) { // do the needful });
This makes the whole operation atomic and there are no duplicates with respect to the userId field.
I hope this helpes. If you have any query, feel free to ask.
As far as I know MongoDB now (from v 4.2) allows to use aggregation pipelines for updates.
More or less elegant way to make it work (according to the question) looks like the following:
db.runCommand({
update: "your-collection-name",
updates: [
{
q: {},
u: {
$set: {
"pfms.$[elem]": {
"n":"apples",
"mState": NumberInt(1111234)
}
}
},
arrayFilters: [
{
"elem.n": {
$eq: "apples"
}
}
],
multi: true
}
]
})
In my scenario, The data need to be init when not existed, and update the field If existed, and the data will not be deleted. If the datas have these states, you might want to try the following method.
// Mongoose, but mostly same as mongodb
// Update the tag to user, If there existed one.
const user = await UserModel.findOneAndUpdate(
{
user: userId,
'tags.name': tag_name,
},
{
$set: {
'tags.$.description': tag_description,
},
}
)
.lean()
.exec();
// Add a default tag to user
if (user == null) {
await UserModel.findOneAndUpdate(
{
user: userId,
},
{
$push: {
tags: new Tag({
name: tag_name,
description: tag_description,
}),
},
}
);
}
This is the most clean and fast method in the scenario.
As a business analyst , I had the same problem and hopefully I have a solution to this after hours of investigation.
// The customer document:
{
"id" : "1212",
"customerCodes" : [
{
"code" : "I"
},
{
"code" : "YK"
}
]
}
// The problem : I want to insert dateField "01.01.2016" to customer documents where customerCodes subdocument has a document with code "YK" but does not have dateField. The final document must be as follows :
{
"id" : "1212",
"customerCodes" : [
{
"code" : "I"
},
{
"code" : "YK" ,
"dateField" : "01.01.2016"
}
]
}
// The solution : the solution code is in three steps :
// PART 1 - Find the customers with customerCodes "YK" but without dateField
// PART 2 - Find the index of the subdocument with "YK" in customerCodes list.
// PART 3 - Insert the value into the document
// Here is the code
// PART 1
var myCursor = db.customers.find({ customerCodes:{$elemMatch:{code:"YK", dateField:{ $exists:false} }}});
// PART 2
myCursor.forEach(function(customer){
if(customer.customerCodes != null )
{
var size = customer.customerCodes.length;
if( size > 0 )
{
var iFoundTheIndexOfSubDocument= -1;
var index = 0;
customer.customerCodes.forEach( function(clazz)
{
if( clazz.code == "YK" && clazz.changeDate == null )
{
iFoundTheIndexOfSubDocument = index;
}
index++;
})
// PART 3
// What happens here is : If i found the indice of the
// "YK" subdocument, I create "updates" document which
// corresponds to the new data to be inserted`
//
if( iFoundTheIndexOfSubDocument != -1 )
{
var toSet = "customerCodes."+ iFoundTheIndexOfSubDocument +".dateField";
var updates = {};
updates[toSet] = "01.01.2016";
db.customers.update({ "id" : customer.id } , { $set: updates });
// This statement is actually interpreted like this :
// db.customers.update({ "id" : "1212" } ,{ $set: customerCodes.0.dateField : "01.01.2016" });
}
}
}
});
Have a nice day !
Here is an example of a document from the collection I am querying
meteor:PRIMARY> db.research.findOne({_id: 'Z2zzA7dx6unkzKiSn'})
{
"_id" : "Z2zzA7dx6unkzKiSn",
"_userId" : "NtE3ANq2b2PbWSEqu",
"collaborators" : [
{
"userId" : "aTPzFad8DdFXxRrX4"
}
],
"name" : "new one",
"pending" : {
"collaborators" : [ ]
}
}
I want to find all documents within this collection with either _userId: 'aTPzFad8DdFXxRrX4' or from the collaborators array, userId: 'aTPzFad8DdFXxRrX4'
So I want to look though the collection and check if the _userId field is 'aTPzFad8DdFXxRrX4'. If not then check the collaborators array on the document and check if there is an object with userId: 'aTPzFad8DdFXxRrX4'.
Here is the query I am trying to use:
db.research.find({$or: [{_userId: 'aTPzFad8DdFXxRrX4'}, {collaborators: {$in: [{userId: 'aTPzFad8DdFXxRrX4'}]}}] })
It does not find the document and gives me a syntax error. What is my issue here? Thanks
The $in operator is basically a simplified version of $or but you really only have one argument here so you should not even need it. Use dot notation instead:
db.research.find({
'$or': [
{ '_userId': 'aTPzFad8DdFXxRrX4'},
{ 'collaborators.userId': 'aTPzFad8DdFXxRrX4'}
]
})
If you need more than one value then use $in:
db.research.find({
'$or': [
{ '_userId': 'aTPzFad8DdFXxRrX4'},
{ 'collaborators.userId': {
'$in': ['aTPzFad8DdFXxRrX4','aTPzFad8DdFXxRrX5']
}}
]
})