I am trying to write some code that searches through a bunch of objects in a MongoDB database. I want to pull the objects from the database by ID, then those objects have ID references. The program should be searching for a specific ID through this process, first getting object from id, then ids from the object.
async function objectFinder(ID1, ID2, depth, previousList = []) {
let route = []
if (ID1 == ID2) {
return [ID2]
} else {
previousList.push(ID1)
let obj1 = await findObjectByID(ID1)
let connectedID = obj1.connections.concat(obj1.inclusions) //creates array of both references to object and references from object
let mapPromises = connectedID.map(async (id) => {
return findID(id) //async function
})
let fulfilled = await Promise.allSettled(mapPromises)
let list = fulfilled.map((object) => {
return object.value.main, object.value.included
})
list = list.filter(id => !previousList.includes(id))
for (id of list) {
await objectFinder(id, ID2, depth - 1, previousList).then(result => {
route = [ID1].concat(result)
if (route[route.length - 1] == ID2) {
return route
}})
}
}
if (route[route.length - 1] == ID2) {
return route
}
}
I am not sure how to make it so that my code works like a tree search, with each object and ID being a node.
I didn't look too much into your code as I strongly believe in letting your database do the work for you if possible.
In this case Mongo has the $graphLookup aggregation stage, which allows recursive lookups. here is a quick example on how to use it:
db.collection.aggregate([
{
$match: {
_id: 1,
}
},
{
"$graphLookup": {
"from": "collection",
"startWith": "$inclusions",
"connectFromField": "inclusions",
"connectToField": "_id",
"as": "matches",
}
},
{
//the rest of the pipeline is just to restore the original structure you don't need this
$addFields: {
matches: {
"$concatArrays": [
[
{
_id: "$_id",
inclusions: "$inclusions"
}
],
"$matches"
]
}
}
},
{
$unwind: "$matches"
},
{
"$replaceRoot": {
"newRoot": "$matches"
}
}
])
Mongo Playground
If for whatever reason you want to keep this in code then I would take a look at your for loop:
for (id of list) {
await objectFinder(id, ID2, depth - 1, previousList).then(result => {
route = [ID1].concat(result);
if (route[route.length - 1] == ID2) {
return route;
}
});
}
Just from a quick glance I can tell you're executing this:
route = [ID1].concat(result);
Many times at the same level. Additional I could not understand your bottom return statements, I feel like there might be an issue there.
i have the following document , it has two array's , one inside the other ,
attachment array and files array inside attachment array .
i want to delete an element inside files array using this element _id . but its not working with me , i tried this code , it return
{ n: 144, nModified: 0, ok: 1 }
Invoice.update({}, {
$pull: {
"attachment":
{
"files":
{
$elemMatch:
{ _id: ObjectId("5b7937014b2a961d082de9bf") }
}
}
}
}, { multi: true })
.then(result => {
console.log("delete", result);
});
this is how the document looks like
You can try below update query in 3.6 version.
Invoice.update(
{},
{"$pull":{"attachment.$[].files":{_id:ObjectId("5b7969ac8fb15f3e5c8e844e")}}},
{"multi": true}, function (err, result) {console.log(result);
});
Use db.adminCommand( { setFeatureCompatibilityVersion: 3.6 or 4.0 depending on your version } ) if your are upgrading from old version.
For Mongodb version prior to 3.6
There is only one nested level here so you can simply use $ positional operator.
Invoice.update(
{ "attachment.files._id": mongoose.Types.ObjectId("5b7937014b2a961d082de9bf") },
{ "$pull": { "attachment.$.files": { "_id": mongoose.Types.ObjectId("5b7937014b2a961d082de9bf") }}},
{ "multi": true }
)
For Mongodb version 3.6 and above
If you want to update multiple elements inside attachement array then you can use $[] the all positional operator.
const mongoose = require("mongoose")
Invoice.update(
{ "attachment.files._id": mongoose.Types.ObjectId("5b7937014b2a961d082de9bf") },
{ "$pull": { "attachment.$[].files": { "_id": mongoose.Types.ObjectId("5b7937014b2a961d082de9bf") }}},
{ "multi": true }
)
And If you want to update single element inside the attachment array then you can use $[<identifier>] that identifies the array elements that match the arrayFilters conditions.
Suppose you want to update only an element inside attachment having _id equal to ObjectId(5b7934f54b2a961d081de9ab)
Invoice.update(
{ "attachment.files._id": mongoose.Types.ObjectId("5b7937014b2a961d082de9bf") },
{ "$pull": { "attachment.$[item].files": { "_id": mongoose.Types.ObjectId("5b7937014b2a961d082de9bf") } } },
{ "arrayFilters": [{ "item._id": mongoose.Types.ObjectId("5b7934f54b2a961d081de9ab") }], "multi": true }
)
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.
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
});
});