Hello I have a document with some user records.
"profile":{
"records":[
{
"classId": "LngdsQfL",
"moduleId": "5CDEezDJ",
"sectionId": "nFMu3mwa",
"dateFinished": "",
"dateOpened": "2017-11-15T19:48:20.819Z"
},
{
"classId": "7Smq5sG",
"moduleId": "5CDEezDJ",
"sectionId": "nFMu3mwa",
"dateFinished": "",
"dateOpened": "2017-11-15T19:19:08.669Z"
}
]
}
But when I am trying to update the second record the query updates the first one. And the second one stays the same.
var classId= "7Smq5sG";
var moduleId = "5CDEezDJ";
var sectionId = "nFMu3mwa";
var date = new Date();
Users.update(
{ _id:Meteor.userId() ,
'profile.records.classId' : classId,
'profile.records.moduleId' : moduleId,
'profile.records.sectionId' : sectionId,
},{
$set : {
"profile.records.$.dateOpened": date
}
});
}
What am I missing?
Try to use a request as follows:
Users.update(
{_id:Meteor.userId(),
'profile.records': {$elemMatch: {
'moduleId': {$eq: moduleId},
'sectionId': {$eq: sectionId},
'classId': {$eq: classId}
}
}
},
{$set: {'profile.records.$.dateOpened': date}});
It uses $elemMatch operator to find array element that matches multiple query criteria.
Related
I have the following trigger function that is not function. I would like to know why it does not set the field createdAt:
const collection = context.services.get("comand-dev").db("test").collection("ownerDetails");
const docId = changeEvent.documentKey._id;
collection;
collection.updateOne(
{_id : docId} ,
{
$set :
{
createdAt: Date()
}
}
);
The trigger logs says OK but the field is not there
This worked for me. A small issue with the syntax. you have to add the quotes.
collection.updateOne(
{"_id" : docId} ,
{
"$set" :
{
"createdat": Date()
}
}
);
I was able to figure out so I would share my solution. In my case, I convert _id object id to date and insert it as a new field for newly inserted document. The trigger will be configurated as insert trigger operation. Enable event ordering.
exports = function (changeEvent) {
const docId = changeEvent.documentKey._id;
console.log(docId);
const collection =
context.services.get("Cluster0").db("Driver").collection("Trip");
collection.updateOne({_id: docId },
[{
"$addFields" : {
"CreationDate" : {
"$toDate" : "$_id"
}
}
}],{upsert: false}
);
};
I want to make a find query on my database for documents that have an input value between or equal to these 2 fields, LOC_CEP_INI and LOC_CEP_FIM
Example: user input a number to the system with value : 69923994, then I use this input to search my database for all documents that have this value between the range of the fields LOC_CEP_INI and LOC_CEP_FIM.
One of my documents (in this example this document is selected by the query because the input is inside the range):
{
"_id" : ObjectId("570d57de457405a61b183ac6"),
"LOC_CEP_FIM" : 69923999, //this field is number
"LOC_CEP_INI" : 69900001, // this field is number
"LOC_NO" : "RIO BRANCO",
"LOC_NU" : "00000016",
"MUN_NU" : "1200401",
"UFE_SG" : "AC",
"create_date" : ISODate("2016-04-12T20:17:34.397Z"),
"__v" : 0
}
db.collection.find( { field: { $gt: value1, $lt: value2 } } );
https://docs.mongodb.com/v3.2/reference/method/db.collection.find/
refer this mongo provide range facility with $gt and $lt .
You have to invert your field names and query value.
db.zipcodes.find({
LOC_CEP_INI: {$gte: 69923997},
LOC_CEP_FIM: {$lte: 69923997}
});
For your query example to work, you would need your documents to hold an array property, and that each item in this prop hold a 69923997 prop. Mongo would then check that this 69923997 prop has a value that is both between "LOC_CEP_INI" and "LOC_CEP_FIM" for each item in your array prop.
Also I'm not sure whether you want LOC_CEP_INI <= 69923997 <= LOC_CEP_FIM or the contrary, so you might need to switch the $gte and $lte conditions.
db.zipcodes.find( {
"LOC_CEP_INI": { "$lte": 69900002 },
"LOC_CEP_FIM": { "$gte": 69900002 } })
Here is the logic use it as per the need:
Userdb.aggregate([
{ "$match": { _id: ObjectId(session._id)}},
{ $project: {
checkout_list: {
$filter: {
input: "$checkout_list",
as: "checkout_list",
cond: {
$and: [
{ $gte: [ "$$checkout_list.createdAt", new Date(date1) ] },
{ $lt: [ "$$checkout_list.createdAt", new Date(date2) ] }
]
}
}
}
}
}
Here i use filter, because of some reason data query on nested data is not gets succeed in mongodb
I am new to mongodb and now using aggregate.
I am in a problem that I have 2 column let this column1 and column2 I want to match either by column1 or column2 inside $match Is it possible. I am getting stuck please help.
db Structure:
{
"_id" : ObjectId("55794aa1be1f8fe822da139d"),
"transactionType" : "1",
"_store" : {
"storeLocation" : "Pitampura",
"storeName" : "Godown",
"_id" : "5576b5c5e414d90c03d1e330"
}
}
I am try to filter according to transactionType and storeName, I am sending these 2 params to api but when storeName sended as empty string then only filter according to transactionType else by both paramater. Not wanted to use if-elseif.
Well of course it can suit your query. You just handle as follows:
// Initial data
var request = { "storeName": "", "transactionType": "1" };
// Transform to array
var conditions = Object.keys(request).map(function(key) {
var obj = {},
newKey = "";
if ( key == "storeName" ) {
newKey = "_store." + key;
} else {
newKey = key;
}
obj[newKey] = request[key];
return obj;
});
db.collection.find({ "$or": conditions });
Where the whole structure after transformation breaks down to :
db.collection.find({
"$or": [
{ "_store.storeName": "" },
{ "transactionType": "1" }
]
})
Which of course matches the document on the condition that "transactionType" is met.
So that is what $or does, considers that at least one of the conditions in the query arguments matches data in the document.
The other thing here is that since the data presented in the request is not a "direct match" for the data in the document, manipulation is done on the "key name" to use the correct "dot notation" form for acessing that element.
These are just basic queries, so the same rules apply to aggregation $match, which is just a query element itself:
db.collection.aggregate([
// Possibly other pipeline before
// Your match phase, which probably should be first
{ "$match": {
"$or": [
{ "_store.storeName": "" },
{ "transactionType": "1" }
]
}},
// Other aggregagtion pipeline
])
I have mongodb documents with a field like this:
Image : http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-zoom.jpg
How can I replace the zoom part in the string value with some other text in order to get:
Image : http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-product2.jpg
You could use mongo's forEach() cursor method to do an atomic update with the $set operator :
db.collection.find({}).snapshot().forEach(function(doc) {
var updated_url = doc.Image.replace('zoom', 'product2');
db.collection.update(
{"_id": doc._id},
{ "$set": { "Image": updated_url } }
);
});
Given a very large collection to update, you could speed up things a little bit with bulkWrite and restructure your update operations to be sent in bulk as:
var ops = [];
db.collection.find({}).snapshot().forEach(function(doc) {
ops.push({
"updateOne": {
"filter": { "_id": doc._id },
"update": { "$set": { "Image": doc.Image.replace('zoom', 'product2') } }
}
});
if ( ops.length === 500 ) {
db.collection.bulkWrite(ops);
ops = [];
}
})
if ( ops.length > 0 )
db.collection.bulkWrite(ops);
db.myCollection.update({image: 'http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-zoom.jpg'}, {$set: {image : 'http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-product2.jpg'}})
If you need to do this multiple times to multiple documents, you need to iterate them with a function. See here: MongoDB: Updating documents using data from the same document
Nowadays,
starting Mongo 4.2, db.collection.updateMany (alias of db.collection.update) can accept an aggregation pipeline, finally allowing the update of a field based on its own value.
starting Mongo 4.4, the new aggregation operator $replaceOne makes it very easy to replace part of a string.
// { "Image" : "http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-zoom.jpg" }
// { "Image" : "http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-boom.jpg" }
db.collection.updateMany(
{ "Image": { $regex: /zoom/ } },
[{
$set: { "Image": {
$replaceOne: { input: "$Image", find: "zoom", replacement: "product2" }
}}
}]
)
// { "Image" : "http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-product2.jpg" }
// { "Image" : "http://static14.com/p/Inc.5-Black-Sandals-5131-2713231-7-boom.jpg" }
The first part ({ "Image": { $regex: /zoom/ } }) is just there to make the query faster by filtering which documents to update (the ones containing "zoom")
The second part ($set: { "Image": {...) is the update aggregation pipeline (note the squared brackets signifying the use of an aggregation pipeline):
$set is a new aggregation operator (Mongo 4.2) which in this case replaces the value of a field.
The new value is computed with the new $replaceOne operator. Note how Image is modified directly based on the its own value ($Image).
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 !