MongoDB $graphLookup inside update query [duplicate] - javascript

In MongoDB, is it possible to update the value of a field using the value from another field? The equivalent SQL would be something like:
UPDATE Person SET Name = FirstName + ' ' + LastName
And the MongoDB pseudo-code would be:
db.person.update( {}, { $set : { name : firstName + ' ' + lastName } );

The best way to do this is in version 4.2+ which allows using the aggregation pipeline in the update document and the updateOne, updateMany, or update(deprecated in most if not all languages drivers) collection methods.
MongoDB 4.2+
Version 4.2 also introduced the $set pipeline stage operator, which is an alias for $addFields. I will use $set here as it maps with what we are trying to achieve.
db.collection.<update method>(
{},
[
{"$set": {"name": { "$concat": ["$firstName", " ", "$lastName"]}}}
]
)
Note that square brackets in the second argument to the method specify an aggregation pipeline instead of a plain update document because using a simple document will not work correctly.
MongoDB 3.4+
In 3.4+, you can use $addFields and the $out aggregation pipeline operators.
db.collection.aggregate(
[
{ "$addFields": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}},
{ "$out": <output collection name> }
]
)
Note that this does not update your collection but instead replaces the existing collection or creates a new one. Also, for update operations that require "typecasting", you will need client-side processing, and depending on the operation, you may need to use the find() method instead of the .aggreate() method.
MongoDB 3.2 and 3.0
The way we do this is by $projecting our documents and using the $concat string aggregation operator to return the concatenated string.
You then iterate the cursor and use the $set update operator to add the new field to your documents using bulk operations for maximum efficiency.
Aggregation query:
var cursor = db.collection.aggregate([
{ "$project": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}}
])
MongoDB 3.2 or newer
You need to use the bulkWrite method.
var requests = [];
cursor.forEach(document => {
requests.push( {
'updateOne': {
'filter': { '_id': document._id },
'update': { '$set': { 'name': document.name } }
}
});
if (requests.length === 500) {
//Execute per 500 operations and re-init
db.collection.bulkWrite(requests);
requests = [];
}
});
if(requests.length > 0) {
db.collection.bulkWrite(requests);
}
MongoDB 2.6 and 3.0
From this version, you need to use the now deprecated Bulk API and its associated methods.
var bulk = db.collection.initializeUnorderedBulkOp();
var count = 0;
cursor.snapshot().forEach(function(document) {
bulk.find({ '_id': document._id }).updateOne( {
'$set': { 'name': document.name }
});
count++;
if(count%500 === 0) {
// Excecute per 500 operations and re-init
bulk.execute();
bulk = db.collection.initializeUnorderedBulkOp();
}
})
// clean up queues
if(count > 0) {
bulk.execute();
}
MongoDB 2.4
cursor["result"].forEach(function(document) {
db.collection.update(
{ "_id": document._id },
{ "$set": { "name": document.name } }
);
})

You should iterate through. For your specific case:
db.person.find().snapshot().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);

Apparently there is a way to do this efficiently since MongoDB 3.4, see styvane's answer.
Obsolete answer below
You cannot refer to the document itself in an update (yet). You'll need to iterate through the documents and update each document using a function. See this answer for an example, or this one for server-side eval().

For a database with high activity, you may run into issues where your updates affect actively changing records and for this reason I recommend using snapshot()
db.person.find().snapshot().forEach( function (hombre) {
hombre.name = hombre.firstName + ' ' + hombre.lastName;
db.person.save(hombre);
});
http://docs.mongodb.org/manual/reference/method/cursor.snapshot/

Starting Mongo 4.2, db.collection.update() can accept an aggregation pipeline, finally allowing the update/creation of a field based on another field:
// { firstName: "Hello", lastName: "World" }
db.collection.updateMany(
{},
[{ $set: { name: { $concat: [ "$firstName", " ", "$lastName" ] } } }]
)
// { "firstName" : "Hello", "lastName" : "World", "name" : "Hello World" }
The first part {} is the match query, filtering which documents to update (in our case all documents).
The second part [{ $set: { name: { ... } }] is the update aggregation pipeline (note the squared brackets signifying the use of an aggregation pipeline). $set is a new aggregation operator and an alias of $addFields.

Regarding this answer, the snapshot function is deprecated in version 3.6, according to this update. So, on version 3.6 and above, it is possible to perform the operation this way:
db.person.find().forEach(
function (elem) {
db.person.update(
{
_id: elem._id
},
{
$set: {
name: elem.firstname + ' ' + elem.lastname
}
}
);
}
);

I tried the above solution but I found it unsuitable for large amounts of data. I then discovered the stream feature:
MongoClient.connect("...", function(err, db){
var c = db.collection('yourCollection');
var s = c.find({/* your query */}).stream();
s.on('data', function(doc){
c.update({_id: doc._id}, {$set: {name : doc.firstName + ' ' + doc.lastName}}, function(err, result) { /* result == true? */} }
});
s.on('end', function(){
// stream can end before all your updates do if you have a lot
})
})

update() method takes aggregation pipeline as parameter like
db.collection_name.update(
{
// Query
},
[
// Aggregation pipeline
{ "$set": { "id": "$_id" } }
],
{
// Options
"multi": true // false when a single doc has to be updated
}
)
The field can be set or unset with existing values using the aggregation pipeline.
Note: use $ with field name to specify the field which has to be read.

Here's what we came up with for copying one field to another for ~150_000 records. It took about 6 minutes, but is still significantly less resource intensive than it would have been to instantiate and iterate over the same number of ruby objects.
js_query = %({
$or : [
{
'settings.mobile_notifications' : { $exists : false },
'settings.mobile_admin_notifications' : { $exists : false }
}
]
})
js_for_each = %(function(user) {
if (!user.settings.hasOwnProperty('mobile_notifications')) {
user.settings.mobile_notifications = user.settings.email_notifications;
}
if (!user.settings.hasOwnProperty('mobile_admin_notifications')) {
user.settings.mobile_admin_notifications = user.settings.email_admin_notifications;
}
db.users.save(user);
})
js = "db.users.find(#{js_query}).forEach(#{js_for_each});"
Mongoid::Sessions.default.command('$eval' => js)

With MongoDB version 4.2+, updates are more flexible as it allows the use of aggregation pipeline in its update, updateOne and updateMany. You can now transform your documents using the aggregation operators then update without the need to explicity state the $set command (instead we use $replaceRoot: {newRoot: "$$ROOT"})
Here we use the aggregate query to extract the timestamp from MongoDB's ObjectID "_id" field and update the documents (I am not an expert in SQL but I think SQL does not provide any auto generated ObjectID that has timestamp to it, you would have to automatically create that date)
var collection = "person"
agg_query = [
{
"$addFields" : {
"_last_updated" : {
"$toDate" : "$_id"
}
}
},
{
$replaceRoot: {
newRoot: "$$ROOT"
}
}
]
db.getCollection(collection).updateMany({}, agg_query, {upsert: true})

(I would have posted this as a comment, but couldn't)
For anyone who lands here trying to update one field using another in the document with the c# driver...
I could not figure out how to use any of the UpdateXXX methods and their associated overloads since they take an UpdateDefinition as an argument.
// we want to set Prop1 to Prop2
class Foo { public string Prop1 { get; set; } public string Prop2 { get; set;} }
void Test()
{
var update = new UpdateDefinitionBuilder<Foo>();
update.Set(x => x.Prop1, <new value; no way to get a hold of the object that I can find>)
}
As a workaround, I found that you can use the RunCommand method on an IMongoDatabase (https://docs.mongodb.com/manual/reference/command/update/#dbcmd.update).
var command = new BsonDocument
{
{ "update", "CollectionToUpdate" },
{ "updates", new BsonArray
{
new BsonDocument
{
// Any filter; here the check is if Prop1 does not exist
{ "q", new BsonDocument{ ["Prop1"] = new BsonDocument("$exists", false) }},
// set it to the value of Prop2
{ "u", new BsonArray { new BsonDocument { ["$set"] = new BsonDocument("Prop1", "$Prop2") }}},
{ "multi", true }
}
}
}
};
database.RunCommand<BsonDocument>(command);

MongoDB 4.2+ Golang
result, err := collection.UpdateMany(ctx, bson.M{},
mongo.Pipeline{
bson.D{{"$set",
bson.M{"name": bson.M{"$concat": []string{"$lastName", " ", "$firstName"}}}
}},
)

Related

how do I increment field in array of objects after finding it (using findOne()) and before saving it?

I want to update an object inside an array of schemas without having to do two requests to the database. I currently am incrementing the field using findOneAndUpdate() if the object already exists and it works fine. but in case the object does not exist then I am having to make another request using update() to push the new object and make it available for later increments.
I want to be able to do only one request (e.g. findOne()) to get the user and then increment the field only if object exists in the array and if not I would like to push the new object instead. then save the document. this way I am only making one read/request from the database instead of two.
this is the function now:
async addItemToCart(body, userId) {
const itemInDb = await Model.findOneAndUpdate(
{
_id: userId,
'cart.productId': body.productId,
},
{ $inc: { 'cart.$.count': 1 } }
);
if (itemInDb) return true;
const updated = await Model.update(
{ _id: userId },
{ $push: { cart: body } }
);
if (updated.ok !== 1)
return createError(500, 'something went wrong in userService');
return true;
}
what I would like to do is:
async addItemToCart(body, userId) {
const itemInDb = await Model.findOne(
{
_id: userId,
'cart.productId': body.productId,
}
);
if (itemInDb) {
/**
*
* increment cart in itemInDb then do itemInDb.save() <<------------
*/
} else {
/**
* push product to itemInDb then save
*/
}
Thank you!
You can try findOneAndUpdate with upsert.
upsert: true then create data if not exists in DB.
Model.findOneAndUpdate(
{
_id: userId,
'cart.productId': body.productId,
},
{ $inc: { 'cart.$.count': 1 } },
{
upsert: true,
}
)
Use $set and $inc in one query.
try {
db.scores.findOneAndUpdate(
{
_id: userId,
'cart.productId': body.productId,
},
{ $set: { "cart.$.productName" : "A.B.C", "cart.$.productPrice" : 5}, $inc : { "cart.$.count" : 1 } },
{ upsert:true, returnNewDocument : true }
);
}
catch (e){
//error
}
reference Link : here
You can use upsert.
upsert is defined as an operation that creates a new document when no document matches the query criteria and if matches then it updates the document. It is an option for the update command. If you execute a command like below it works as an update, if there is a document matching query, or as an insert with a document described by the update as an argument.
Example: I am just giving a simple example. You have to change it according to your requirement.
db.people.update(
{ name: "Andy" },
{
name: "Andy",
rating: 1,
score: 1
},
{ upsert: true }
)
So in the above example, if the people with name Andy is found then the update operation will be performed. If not then it will create a new document.

If the specific field is double, convert it to Int [duplicate]

I am trying to change the type of a field from within the mongo shell.
I am doing this...
db.meta.update(
{'fields.properties.default': { $type : 1 }},
{'fields.properties.default': { $type : 2 }}
)
But it's not working!
The only way to change the $type of the data is to perform an update on the data where the data has the correct type.
In this case, it looks like you're trying to change the $type from 1 (double) to 2 (string).
So simply load the document from the DB, perform the cast (new String(x)) and then save the document again.
If you need to do this programmatically and entirely from the shell, you can use the find(...).forEach(function(x) {}) syntax.
In response to the second comment below. Change the field bad from a number to a string in collection foo.
db.foo.find( { 'bad' : { $type : 1 } } ).forEach( function (x) {
x.bad = new String(x.bad); // convert field to string
db.foo.save(x);
});
Convert String field to Integer:
db.db-name.find({field-name: {$exists: true}}).forEach(function(obj) {
obj.field-name = new NumberInt(obj.field-name);
db.db-name.save(obj);
});
Convert Integer field to String:
db.db-name.find({field-name: {$exists: true}}).forEach(function(obj) {
obj.field-name = "" + obj.field-name;
db.db-name.save(obj);
});
Starting Mongo 4.2, db.collection.update() can accept an aggregation pipeline, finally allowing the update of a field based on its own value:
// { a: "45", b: "x" }
// { a: 53, b: "y" }
db.collection.updateMany(
{ a : { $type: 1 } },
[{ $set: { a: { $toString: "$a" } } }]
)
// { a: "45", b: "x" }
// { a: "53", b: "y" }
The first part { a : { $type: 1 } } is the match query:
It filters which documents to update.
In this case, since we want to convert "a" to string when its value is a double, this matches elements for which "a" is of type 1 (double)).
This table provides the code representing the different possible types.
The second part [{ $set: { a: { $toString: "$a" } } }] is the update aggregation pipeline:
Note the squared brackets signifying that this update query uses an aggregation pipeline.
$set is a new aggregation operator (Mongo 4.2) which in this case modifies a field.
This can be simply read as "$set" the value of "a" to "$a" converted "$toString".
What's really new here, is being able in Mongo 4.2 to reference the document itself when updating it: the new value for "a" is based on the existing value of "$a".
Also note "$toString" which is a new aggregation operator introduced in Mongo 4.0.
In case your cast isn't from double to string, you have the choice between different conversion operators introduced in Mongo 4.0 such as $toBool, $toInt, ...
And if there isn't a dedicated converter for your targeted type, you can replace { $toString: "$a" } with a $convert operation: { $convert: { input: "$a", to: 2 } } where the value for to can be found in this table:
db.collection.updateMany(
{ a : { $type: 1 } },
[{ $set: { a: { $convert: { input: "$a", to: 2 } } } }]
)
For string to int conversion.
db.my_collection.find().forEach( function(obj) {
obj.my_value= new NumberInt(obj.my_value);
db.my_collection.save(obj);
});
For string to double conversion.
obj.my_value= parseInt(obj.my_value, 10);
For float:
obj.my_value= parseFloat(obj.my_value);
db.coll.find().forEach(function(data) {
db.coll.update({_id:data._id},{$set:{myfield:parseInt(data.myfield)}});
})
all answers so far use some version of forEach, iterating over all collection elements client-side.
However, you could use MongoDB's server-side processing by using aggregate pipeline and $out stage as :
the $out stage atomically replaces the existing collection with the
new results collection.
example:
db.documents.aggregate([
{
$project: {
_id: 1,
numberField: { $substr: ['$numberField', 0, -1] },
otherField: 1,
differentField: 1,
anotherfield: 1,
needolistAllFieldsHere: 1
},
},
{
$out: 'documents',
},
]);
To convert a field of string type to date field, you would need to iterate the cursor returned by the find() method using the forEach() method, within the loop convert the field to a Date object and then update the field using the $set operator.
Take advantage of using the Bulk API for bulk updates which offer better performance as you will be sending the operations to the server in batches of say 1000 which gives you a better performance as you are not sending every request to the server, just once in every 1000 requests.
The following demonstrates this approach, the first example uses the Bulk API available in MongoDB versions >= 2.6 and < 3.2. It updates all
the documents in the collection by changing all the created_at fields to date fields:
var bulk = db.collection.initializeUnorderedBulkOp(),
counter = 0;
db.collection.find({"created_at": {"$exists": true, "$type": 2 }}).forEach(function (doc) {
var newDate = new Date(doc.created_at);
bulk.find({ "_id": doc._id }).updateOne({
"$set": { "created_at": newDate}
});
counter++;
if (counter % 1000 == 0) {
bulk.execute(); // Execute per 1000 operations and re-initialize every 1000 update statements
bulk = db.collection.initializeUnorderedBulkOp();
}
})
// Clean up remaining operations in queue
if (counter % 1000 != 0) { bulk.execute(); }
The next example applies to the new MongoDB version 3.2 which has since deprecated the Bulk API and provided a newer set of apis using bulkWrite():
var bulkOps = [];
db.collection.find({"created_at": {"$exists": true, "$type": 2 }}).forEach(function (doc) {
var newDate = new Date(doc.created_at);
bulkOps.push(
{
"updateOne": {
"filter": { "_id": doc._id } ,
"update": { "$set": { "created_at": newDate } }
}
}
);
})
db.collection.bulkWrite(bulkOps, { "ordered": true });
To convert int32 to string in mongo without creating an array just add "" to your number :-)
db.foo.find( { 'mynum' : { $type : 16 } } ).forEach( function (x) {
x.mynum = x.mynum + ""; // convert int32 to string
db.foo.save(x);
});
What really helped me to change the type of the object in MondoDB was just this simple line, perhaps mentioned before here...:
db.Users.find({age: {$exists: true}}).forEach(function(obj) {
obj.age = new NumberInt(obj.age);
db.Users.save(obj);
});
Users are my collection and age is the object which had a string instead of an integer (int32).
You can easily convert the string data type to numerical data type.
Don't forget to change collectionName & FieldName.
for ex : CollectionNmae : Users & FieldName : Contactno.
Try this query..
db.collectionName.find().forEach( function (x) {
x.FieldName = parseInt(x.FieldName);
db.collectionName.save(x);
});
I need to change datatype of multiple fields in the collection, so I used the following to make multiple data type changes in the collection of documents. Answer to an old question but may be helpful for others.
db.mycoll.find().forEach(function(obj) {
if (obj.hasOwnProperty('phone')) {
obj.phone = "" + obj.phone; // int or longint to string
}
if (obj.hasOwnProperty('field-name')) {
obj.field-name = new NumberInt(obj.field-name); //string to integer
}
if (obj.hasOwnProperty('cdate')) {
obj.cdate = new ISODate(obj.cdate); //string to Date
}
db.mycoll.save(obj);
});
demo change type of field mid from string to mongo objectId using mongoose
Post.find({}, {mid: 1,_id:1}).exec(function (err, doc) {
doc.map((item, key) => {
Post.findByIdAndUpdate({_id:item._id},{$set:{mid: mongoose.Types.ObjectId(item.mid)}}).exec((err,res)=>{
if(err) throw err;
reply(res);
});
});
});
Mongo ObjectId is just another example of such styles as
Number, string, boolean that hope the answer will help someone else.
I use this script in mongodb console for string to float conversions...
db.documents.find({ 'fwtweaeeba' : {$exists : true}}).forEach( function(obj) {
obj.fwtweaeeba = parseFloat( obj.fwtweaeeba );
db.documents.save(obj); } );
db.documents.find({ 'versions.0.content.fwtweaeeba' : {$exists : true}}).forEach( function(obj) {
obj.versions[0].content.fwtweaeeba = parseFloat( obj.versions[0].content.fwtweaeeba );
db.documents.save(obj); } );
db.documents.find({ 'versions.1.content.fwtweaeeba' : {$exists : true}}).forEach( function(obj) {
obj.versions[1].content.fwtweaeeba = parseFloat( obj.versions[1].content.fwtweaeeba );
db.documents.save(obj); } );
db.documents.find({ 'versions.2.content.fwtweaeeba' : {$exists : true}}).forEach( function(obj) {
obj.versions[2].content.fwtweaeeba = parseFloat( obj.versions[2].content.fwtweaeeba );
db.documents.save(obj); } );
And this one in php)))
foreach($db->documents->find(array("type" => "chair")) as $document){
$db->documents->update(
array('_id' => $document[_id]),
array(
'$set' => array(
'versions.0.content.axdducvoxb' => (float)$document['versions'][0]['content']['axdducvoxb'],
'versions.1.content.axdducvoxb' => (float)$document['versions'][1]['content']['axdducvoxb'],
'versions.2.content.axdducvoxb' => (float)$document['versions'][2]['content']['axdducvoxb'],
'axdducvoxb' => (float)$document['axdducvoxb']
)
),
array('$multi' => true)
);
}
The above answers almost worked but had a few challenges-
Problem 1: db.collection.save no longer works in MongoDB 5.x
For this, I used replaceOne().
Problem 2: new String(x.bad) was giving exponential number
I used "" + x.bad as suggested above.
My version:
let count = 0;
db.user
.find({
custID: {$type: 1},
})
.forEach(function (record) {
count++;
const actualValue = record.custID;
record.custID = "" + record.custID;
console.log(`${count}. Updating User(id:${record._id}) from old id [${actualValue}](${typeof actualValue}) to [${record.custID}](${typeof record.custID})`)
db.user.replaceOne({_id: record._id}, record);
});
And for millions of records, here are the output (for future investigation/reference)-

Find Documents Where a Field Compares with Another in an Array

Let's say I have a collection of documents that look like this:
{
"_id" : ObjectId("5afa6df3a24cdb1652632ef5"),
"createdBy" : {
"_id" : "59232a1a41aa651ddff0939f"
},
"owner" : {
"_id" : "5abc4dc0f47f732c96d84aac"
},
"acl" : [
{
"profile" : {
"_id" : "59232a1a41aa651ddff0939f"
}
},
{
"profile" : {
"_id" : "5abc4dc0f47f732c96d84aac"
}
}
]
}
I want to find all documents where createdBy._id != owner._id, AND where the createdBy._id appears in one of the entries in the acl array. Eventually, I will want to update all such documents to set the owner._id field to equal the createdBy._id field. For now, I'm just trying to figure out how to query the subset of documents I want to update.
So far, I have come up with this:
db.boards.find({
$where: "this.createdBy._id != this.owner._id",
$where: function() {
return this.acl.some(
function(e) => {
e.profile._id === this.createdBy._id
}, this);
}
)
(I have used ES5 syntax just in case ES6 isn't ok)
But when I run this query, I get the following error:
Error: error: { "ok" : 0, "errmsg" : "TypeError: e.profile is
undefined :\n_funcs2/<#:2:36\n_funcs2#:2:12\n", "code" : 139 }
How do I perform this query / what is going on here? I would have expected my query to work, based on the docs I've read. Above, e should be an element of the acl array, so I expect it to have a field profile, but that doesn't seem to be the case.
Note, I'm using Mongo 3.2, so I can't use $expr, which I've seen some resources suggest is a possibility.
Resolution
It turns out that I had made an incorrect assumption about the schema of this collection. The reason I was running into the above error is because some documents have an acl array with an element that doesn't have a profile field. The below query checks for this case. It also has a single $where, because the way I had written it originally (with two) seemed to end up giving me an OR of the conditions instead of an AND.
db.boards.find({
$where: function() {
return this.acl.some(
function(e) => {
e.profile !== undefined && e.profile._id === this.createdBy._id && this.createdBy._id != this.owner._id
}, this);
}
)
You can still use aggregate() here with MongoDB 3.2, but just using $redact instead:
db.boards.aggregate([
{ "$redact": {
"$cond": {
"if": {
"$and": [
{ "$ne": [ "$createdBy._id", "$owner._id" ] },
{ "$setIsSubset": [["$createdBy._id"], "$acl.profile._id"] }
]
},
"then": "$$KEEP",
"else": "$$PRUNE"
}
}}
])
Or with $where for the MongoDB 3.2 shell, you just need to keep a scoped copy of this, and your syntax was a bit off:
db.boards.find({
"$where": function() {
var self = this;
return (this.createdBy._id != this.owner._id)
&& this.acl.some(function(e) {
return e.profile._id === self.createdBy._id
})
}
})
Or in an ES6 compatible environment then:
db.boards.find({
"$where": function() {
return (this.createdBy._id != this.owner._id)
&& this.acl.some(e => e.profile._id === this.createdBy._id)
}
})
The aggregate is the most performant option of the two and should always be preferable to using JavaScript evalulation
And for what it's worth, the newer syntax with $expr would be:
db.boards.find({
"$expr": {
"$and": [
{ "$ne": [ "$createdBy._id", "$owner._id" ] },
{ "$in": [ "$createdBy._id", "$acl.profile._id"] }
]
}
})
Using $in in preference to $setIsSubset where the syntax is a little shorter.
NOTE The only reason the JavaScript comparison here works is because you have mistakenly stored ObjectId values as "strings" in those fields. Where there is a "real" ObjectId just like in the _id field, the comparison needs to take the "string" from valueOf() in order to compare:
return (this.createdBy._id.valueOf() != this.owner._id.valueOf())
&& this.acl.some(e => e.profile._id.valueOf() === this.createdBy._id.valueOf())
Without that it's actually an "Object Comparison" with JavaScript and { a: 1 } === { a: 1 } is actually false. So avoiding that complexity is another reason there are native operators for this instead.

How count pages total number of pages? [duplicate]

I am interested in optimizing a "pagination" solution I'm working on with MongoDB. My problem is straight forward. I usually limit the number of documents returned using the limit() functionality. This forces me to issue a redundant query without the limit() function in order for me to also capture the total number of documents in the query so I can pass to that to the client letting them know they'll have to issue an additional request(s) to retrieve the rest of the documents.
Is there a way to condense this into 1 query? Get the total number of documents but at the same time only retrieve a subset using limit()? Is there a different way to think about this problem than I am approaching it?
Mongodb 3.4 has introduced $facet aggregation
which processes multiple aggregation pipelines within a single stage
on the same set of input documents.
Using $facet and $group you can find documents with $limit and can get total count.
You can use below aggregation in mongodb 3.4
db.collection.aggregate([
{ "$facet": {
"totalData": [
{ "$match": { }},
{ "$skip": 10 },
{ "$limit": 10 }
],
"totalCount": [
{ "$group": {
"_id": null,
"count": { "$sum": 1 }
}}
]
}}
])
Even you can use $count aggregation which has been introduced in mongodb 3.6.
You can use below aggregation in mongodb 3.6
db.collection.aggregate([
{ "$facet": {
"totalData": [
{ "$match": { }},
{ "$skip": 10 },
{ "$limit": 10 }
],
"totalCount": [
{ "$count": "count" }
]
}}
])
No, there is no other way. Two queries - one for count - one with limit. Or you have to use a different database. Apache Solr for instance works like you want. Every query there is limited and returns totalCount.
MongoDB allows you to use cursor.count() even when you pass limit() or skip().
Lets say you have a db.collection with 10 items.
You can do:
async function getQuery() {
let query = await db.collection.find({}).skip(5).limit(5); // returns last 5 items in db
let countTotal = await query.count() // returns 10-- will not take `skip` or `limit` into consideration
let countWithConstraints = await query.count(true) // returns 5 -- will take into consideration `skip` and `limit`
return { query, countTotal }
}
Here's how to do this with MongoDB 3.4+ (with Mongoose) using $facets. This examples returns a $count based on the documents after they have been matched.
const facetedPipeline = [{
"$match": { "dateCreated": { $gte: new Date('2021-01-01') } },
"$project": { 'exclude.some.field': 0 },
},
{
"$facet": {
"data": [
{ "$skip": 10 },
{ "$limit": 10 }
],
"pagination": [
{ "$count": "total" }
]
}
}
];
const results = await Model.aggregate(facetedPipeline);
This pattern is useful for getting pagination information to return from a REST API.
Reference: MongoDB $facet
Times have changed, and I believe you can achieve what the OP is asking by using aggregation with $sort, $group and $project. For my system, I needed to also grab some user info from my users collection. Hopefully this can answer any questions around that as well. Below is an aggregation pipe. The last three objects (sort, group and project) are what handle getting the total count, then providing pagination capabilities.
db.posts.aggregate([
{ $match: { public: true },
{ $lookup: {
from: 'users',
localField: 'userId',
foreignField: 'userId',
as: 'userInfo'
} },
{ $project: {
postId: 1,
title: 1,
description: 1
updated: 1,
userInfo: {
$let: {
vars: {
firstUser: {
$arrayElemAt: ['$userInfo', 0]
}
},
in: {
username: '$$firstUser.username'
}
}
}
} },
{ $sort: { updated: -1 } },
{ $group: {
_id: null,
postCount: { $sum: 1 },
posts: {
$push: '$$ROOT'
}
} },
{ $project: {
_id: 0,
postCount: 1,
posts: {
$slice: [
'$posts',
currentPage ? (currentPage - 1) * RESULTS_PER_PAGE : 0,
RESULTS_PER_PAGE
]
}
} }
])
there is a way in Mongodb 3.4: $facet
you can do
db.collection.aggregate([
{
$facet: {
data: [{ $match: {} }],
total: { $count: 'total' }
}
}
])
then you will be able to run two aggregate at the same time
By default, the count() method ignores the effects of the
cursor.skip() and cursor.limit() (MongoDB docs)
As the count method excludes the effects of limit and skip, you can use cursor.count() to get the total count
const cursor = await database.collection(collectionName).find(query).skip(offset).limit(limit)
return {
data: await cursor.toArray(),
count: await cursor.count() // this will give count of all the documents before .skip() and limit()
};
It all depends on the pagination experience you need as to whether or not you need to do two queries.
Do you need to list every single page or even a range of pages? Does anyone even go to page 1051 - conceptually what does that actually mean?
Theres been lots of UX on patterns of pagination - Avoid the pains of pagination covers various types of pagination and their scenarios and many don't need a count query to know if theres a next page. For example if you display 10 items on a page and you limit to 13 - you'll know if theres another page..
MongoDB has introduced a new method for getting only the count of the documents matching a given query and it goes as follows:
const result = await db.collection('foo').count({name: 'bar'});
console.log('result:', result) // prints the matching doc count
Recipe for usage in pagination:
const query = {name: 'bar'};
const skip = (pageNo - 1) * pageSize; // assuming pageNo starts from 1
const limit = pageSize;
const [listResult, countResult] = await Promise.all([
db.collection('foo')
.find(query)
.skip(skip)
.limit(limit),
db.collection('foo').count(query)
])
return {
totalCount: countResult,
list: listResult
}
For more details on db.collection.count visit this page
It is possible to get the total result size without the effect of limit() using count() as answered here:
Limiting results in MongoDB but still getting the full count?
According to the documentation you can even control whether limit/pagination is taken into account when calling count():
https://docs.mongodb.com/manual/reference/method/cursor.count/#cursor.count
Edit: in contrast to what is written elsewhere - the docs clearly state that "The operation does not perform the query but instead counts the results that would be returned by the query". Which - from my understanding - means that only one query is executed.
Example:
> db.createCollection("test")
{ "ok" : 1 }
> db.test.insert([{name: "first"}, {name: "second"}, {name: "third"},
{name: "forth"}, {name: "fifth"}])
BulkWriteResult({
"writeErrors" : [ ],
"writeConcernErrors" : [ ],
"nInserted" : 5,
"nUpserted" : 0,
"nMatched" : 0,
"nModified" : 0,
"nRemoved" : 0,
"upserted" : [ ]
})
> db.test.find()
{ "_id" : ObjectId("58ff00918f5e60ff211521c5"), "name" : "first" }
{ "_id" : ObjectId("58ff00918f5e60ff211521c6"), "name" : "second" }
{ "_id" : ObjectId("58ff00918f5e60ff211521c7"), "name" : "third" }
{ "_id" : ObjectId("58ff00918f5e60ff211521c8"), "name" : "forth" }
{ "_id" : ObjectId("58ff00918f5e60ff211521c9"), "name" : "fifth" }
> db.test.count()
5
> var result = db.test.find().limit(3)
> result
{ "_id" : ObjectId("58ff00918f5e60ff211521c5"), "name" : "first" }
{ "_id" : ObjectId("58ff00918f5e60ff211521c6"), "name" : "second" }
{ "_id" : ObjectId("58ff00918f5e60ff211521c7"), "name" : "third" }
> result.count()
5 (total result size of the query without limit)
> result.count(1)
3 (result size with limit(3) taken into account)
Try as bellow:
cursor.count(false, function(err, total){ console.log("total", total) })
core.db.users.find(query, {}, {skip:0, limit:1}, function(err, cursor){
if(err)
return callback(err);
cursor.toArray(function(err, items){
if(err)
return callback(err);
cursor.count(false, function(err, total){
if(err)
return callback(err);
console.log("cursor", total)
callback(null, {items: items, total:total})
})
})
})
Thought of providing a caution while using the aggregate for the pagenation. Its better to use two queries for this if the API is used frequently to fetch data by the users. This is atleast 50 times faster than getting the data using aggregate on a production server when more users are accessing the system online. The aggregate and $facet are more suited for Dashboard , reports and cron jobs that are called less frequently.
We can do it using 2 query.
const limit = parseInt(req.query.limit || 50, 10);
let page = parseInt(req.query.page || 0, 10);
if (page > 0) { page = page - 1}
let doc = await req.db.collection('bookings').find().sort( { _id: -1 }).skip(page).limit(limit).toArray();
let count = await req.db.collection('bookings').find().count();
res.json({data: [...doc], count: count});
I took the two queries approach, and the following code has been taken straight out of a project I'm working on, using MongoDB Atlas and a full-text search index:
return new Promise( async (resolve, reject) => {
try {
const search = {
$search: {
index: 'assets',
compound: {
should: [{
text: {
query: args.phraseToSearch,
path: [
'title', 'note'
]
}
}]
}
}
}
const project = {
$project: {
_id: 0,
id: '$_id',
userId: 1,
title: 1,
note: 1,
score: {
$meta: 'searchScore'
}
}
}
const match = {
$match: {
userId: args.userId
}
}
const skip = {
$skip: args.skip
}
const limit = {
$limit: args.first
}
const group = {
$group: {
_id: null,
count: { $sum: 1 }
}
}
const searchAllAssets = await Models.Assets.schema.aggregate([
search, project, match, skip, limit
])
const [ totalNumberOfAssets ] = await Models.Assets.schema.aggregate([
search, project, match, group
])
return await resolve({
searchAllAssets: searchAllAssets,
totalNumberOfAssets: totalNumberOfAssets.count
})
} catch (exception) {
return reject(new Error(exception))
}
})
I had the same problem and came across this question. The correct solution to this problem is posted here.
You can do this in one query. First you run a count and within that run the limit() function.
In Node.js and Express.js, you will have to use it like this to be able to use the "count" function along with the toArray's "result".
var curFind = db.collection('tasks').find({query});
Then you can run two functions after it like this (one nested in the other)
curFind.count(function (e, count) {
// Use count here
curFind.skip(0).limit(10).toArray(function(err, result) {
// Use result here and count here
});
});

How to replace string in all documents in Mongo

I need to replace a string in certain documents. I have googled this code, but it unfortunately does not change anything. I am not sure about the syntax on the line bellow:
pulpdb = db.getSisterDB("pulp_database");
var cursor = pulpdb.repos.find();
while (cursor.hasNext()) {
var x = cursor.next();
x['source']['url'].replace('aaa', 'bbb'); // is this correct?
db.foo.update({_id : x._id}, x);
}
I would like to add some debug prints to see what the value is, but I have no experience with MongoDB Shell. I just need to replace this:
{ "source": { "url": "http://aaa/xxx/yyy" } }
with
{ "source": { "url": "http://bbb/xxx/yyy" } }
It doesn't correct generally: if you have string http://aaa/xxx/aaa (yyy equals to aaa) you'll end up with http://bbb/xxx/bbb.
But if you ok with this, code will work.
To add debug info use print function:
var cursor = db.test.find();
while (cursor.hasNext()) {
var x = cursor.next();
print("Before: "+x['source']['url']);
x['source']['url'] = x['source']['url'].replace('aaa', 'bbb');
print("After: "+x['source']['url']);
db.test.update({_id : x._id}, x);
}
(And by the way, if you want to print out objects, there is also printjson function)
The best way to do this if you are on MongoDB 2.6 or newer is looping over the cursor object using the .forEach method and update each document usin "bulk" operations for maximum efficiency.
var bulk = db.collection.initializeOrderedBulkOp();
var count = 0;
db.collection.find().forEach(function(doc) {
print("Before: "+doc.source.url);
bulk.find({ '_id': doc._id }).update({
'$set': { 'source.url': doc.source.url.replace('aaa', 'bbb') }
})
count++;
if(count % 200 === 0) {
bulk.execute();
bulk = db.collection.initializeOrderedBulkOp();
}
// Clean up queues
if (count > 0)
bulk.execute();
From MongoDB 3.2 the Bulk() API and its associated methods are deprecated you will need to use the db.collection.bulkWrite() method.
You will need loop over the cursor, build your query dynamically and $push each operation to an array.
var operations = [];
db.collection.find().forEach(function(doc) {
print("Before: "+doc.source.url);
var operation = {
updateOne: {
filter: { '_id': doc._id },
update: {
'$set': { 'source.url': doc.source.url.replace('aaa', 'bbb') }
}
}
};
operations.push(operation);
})
operations.push({
ordered: true,
writeConcern: { w: "majority", wtimeout: 5000 }
})
db.collection.bulkWrite(operations);
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.
// { "source" : { "url" : "http://aaa/xxx/yyy" } }
// { "source" : { "url" : "http://eee/xxx/yyy" } }
db.collection.updateMany(
{ "source.url": { $regex: /aaa/ } },
[{
$set: { "source.url": {
$replaceOne: { input: "$source.url", find: "aaa", replacement: "bbb" }
}}
}]
)
// { "source" : { "url" : "http://bbb/xxx/yyy" } }
// { "source" : { "url" : "http://eee/xxx/yyy" } }
The first part ({ "source.url": { $regex: /aaa/ } }) is the match query, filtering which documents to update (the ones containing "aaa")
The second part ($set: { "source.url": {...) 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 $replaceOne operator. Note how source.url is modified directly based on the its own value ($source.url).
Note that this is fully handled server side which won't allow you to perform the debug printing part of your question.
MongoDB can do string search/replace via mapreduce. Yes, you need to have a very special data structure for it -- you can't have anything in the top keys but you need to store everything under a subdocument under value. Like this:
{
"_id" : ObjectId("549dafb0a0d0ca4ed723e37f"),
"value" : {
"title" : "Top 'access denied' errors",
"parent" : "system.admin_reports",
"p" : "\u0001\u001a%"
}
}
Once you have this neatly set up you can do:
$map = new \MongoCode("function () {
this.value['p'] = this.value['p'].replace('$from', '$to');
emit(this._id, this.value);
}");
$collection = $this->mongoCollection();
// This won't be called.
$reduce = new \MongoCode("function () { }");
$collection_name = $collection->getName();
$collection->db->command([
'mapreduce' => $collection_name,
'map' => $map,
'reduce' => $reduce,
'out' => ['merge' => $collection_name],
'query' => $query,
'sort' => ['_id' => 1],
]);

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