My model :
const scheduleTaskSchema = new Schema({
activity: { type: Object, required: true },
date: { type: Date, required: true },
crew: Object,
vehicle: Object,
pickups: Array,
details: String,
});
const ScheduleTaskModel = mongoose.model("schedule_task", scheduleTaskSchema),
and this aggregation pipeline :
let aggregation = [
{
$sort: {
"pickups.0.time": 1,
},
},
{
$group: {
_id: "$date",
tasks: { $push: "$$ROOT" },
},
},
{ $sort: { _id: -1 } },
];
if (hasDateQuery) {
aggregation.unshift({
$match: {
date: { $gte: new Date(start_date), $lte: new Date(end_date) },
},
});
} else {
aggregation.push({ $limit: 2 });
}
const scheduledTasksGroups = await ScheduleTaskModel.aggregate(aggregation);
the crew object can have arbitrary number of keys with this structure :
crew : {
drivers: [
{
_id: "656b1e9cf5b894a4f2v643bc",
name: "john"
},
{
_id: "567b1e9cf5b954a4f2c643bhh",
name: "bill"
}
],
officers: [
{
_id: "655b1e9cf5b6632a4f2c643jk",
name: "mark"
},
{
_id: "876b1e9af5b664a4f2c234bb",
name: "jane"
}
],
//...any number of keys that contain an array of objects that all have an _id
}
I'm looking for a way to return all documents (before sorting/grouping) that contain a given _id anywhere within the crew object without knowing which key to search,it can be many different keys that all contain an array of objects that all have an _id
Any ideas ?
You can use $objectToArray for this:
db.collection.aggregate([
{$addFields: {crewFilter: {$objectToArray: "$crew"}}},
{$set: {
crewFilter: {$size: {
$reduce: {
input: "$crewFilter",
initialValue: [],
in: {$concatArrays: [
"$$value",
{$filter: {
input: "$$this.v",
as: "member",
cond: {$eq: ["$$member._id", _id]}
}
}
]
}
}
}}
}},
{$match: {crewFilter: {$gt: 0}}}
])
See how it works on the playground example
Related
I have a collection Shops. Each object in Shops collection has an array of Item objects called items.
{
_id: ObjectId(...),
shopName: 'Ice cream Shop',
items: [
<Item>{
itemName: 'Chocolate IC',
availabilities: [
{
city: 'NY',
arrivals: [
{
price: 3.99,
quantityLeft: 0,
date: 'yesterday'
},
{
price: 3.99,
quantityLeft: 40,
date: 'today'
}
]
},
{
city: 'LA',
arrivals: []
}
]
},
<Item>{
itemName: 'Strawberry IC',
availabilities: [
{
city: 'NY',
arrivals: [
{
price: 3.99,
quantityLeft: 0,
date: 'yesterday'
},
]
}
]
},
],
},
... anotherShops
I want to get list of Item objects which has overall quantityLeft more than 0 from a specific shop.
I tried this code to get all items with the name start with "Straw" from a Shop with shopName equal to 'Ice cream Shop':
const items = await Shop.aggregate()
.match({
shopName: 'Ice cream Shop',
})
.project({
items: {
$filter: {
input: "$items",
as: "item",
cond: {
$regexMatch: {
input: "$$item.itemName",
regex: `.*Straw.*`,
},
},
},
},
});
And it works. But I don't know how to sum up all quantityLeft values inside availabilities array of each item, and return only that items that has sum more than 0.
availabilities array can be an empty array [].
The city parameter also needs to be in condition. For example, only Items that are in stock in NY
I need this to get the list of items from a certain shop, and only the items that are still in stock.
Pretty hard.
I came up with this solution. If you have a better solution, please post it.
const shop = await GCShop.aggregate([
{
$match: {
shopName: 'Ice Cream Shop',
},
},
{
$unwind: "$items",
},
{
$unwind: "$items.availabilities",
},
{
$unwind: "$items.availabilities.arrivals",
},
{
$group: {
_id: "$items.id",
items_name: { $first: "$items.name" },
arrivals: {
$push: {
arrival_id: "$items.availabilities.arrivals.arrival_id",
price: "$items.availabilities.arrivals.price",
qtty: "$items.availabilities.arrivals.qtty",
},
},
totalQtty: { $sum: "$items.availabilities.arrivals.qtty" },
},
},
{
$project: {
offer_id: "$_id",
_id: 0,
offer_name: 1,
totalQtty: 1,
arrivals: 1,
},
},
{
$match: {
totalQtty: {
$gt: 0,
},
},
},
]).limit(20);
I have a database of a the employees of a company that looks like this:
{
_id: 7698,
name: 'Blake',
job: 'manager',
manager: 7839,
hired: ISODate("1981-05-01T00:00:00.000Z"),
salary: 2850,
department: {name: 'Sales', location: 'Chicago'},
missions: [
{company: 'Mac Donald', location: 'Chicago'},
{company: 'IBM', location: 'Chicago'}
]
}
I have an exercise in which I need to write the MongoDb command that returns all them employees who did all their missions in Chicago. I struggle with the all because I cannot find a way to check that all the locations of the missions array are equal to 'Chicago'.
I was thinking about doing it in two time: first find the total number of missions the employee has and then compare it to the number of mission he has in Chicago (that how I would do in SQL I guess). But I cannot found the number of mission the employee did in Chicago. Here is what I tried:
db.employees.aggregate([
{
$match: { "missions": { $exists: true } }
},
{
$project: {
name: 1,
nbMissionsChicago: {
$sum: {
$cond: [
{
$eq: [{
$getField: {
field: { $literal: "$location" },
input: "$missions"
}
}, "Chicago"]
}, 1, 0
]
}
}
}
}
])
Here is the result :
{ _id: 7698, name: 'Blake', nbMissionsChicago: 0 }
{ _id: 7782, name: 'Clark', nbMissionsChicago: 0 }
{ _id: 8000, name: 'Smith', nbMissionsChicago: 0 }
{ _id: 7902, name: 'Ford', nbMissionsChicago: 0 }
{ _id: 7499, name: 'Allen', nbMissionsChicago: 0 }
{ _id: 7654, name: 'Martin', nbMissionsChicago: 0 }
{ _id: 7900, name: 'James', nbMissionsChicago: 0 }
{ _id: 7369, name: 'Smith', nbMissionsChicago: 0 }
First of all, is there a better method to check that all the locations of the missions array respect the condition? And why does this commands returns only 0 ?
Thanks!
If all you need is the agents who had all their missions in "Chicago" then you don't need an aggregation pipeline for it, specifically the approach of filtering the array as part of the aggregation can't utilize an index and will make performance even worse.
A simple query should suffice here:
db.collection.find({
$and: [
{
"missions": {
$exists: true
}
},
{
"missions.location": {
$not: {
$gt: "Chicago"
}
}
},
{
"missions.location": {
$not: {
$lt: "Chicago"
}
}
}
]
})
Mongo Playground
This way we can build an index on the missions field and utilize it properly, any documents with a different value other then "Chigaco" will not match as they will fail the $gt or $lt comparion.
Note that an empty array also matches the condition, you can change the generic "missions" exists condition key into "missions.0": {$exists: true}, this will also require at least one mission.
You are unable to get the correct result as it is not the correct way to iterate the element in an array field.
Instead, you need to work with $size operator to get the size of an array and the $filter operator to filter the document.
Updated: You can directly compare the filtered array with the original array.
db.employees.aggregate([
{
$match: {
"missions": {
$exists: true
}
}
},
{
$project: {
name: 1,
nbMissionsChicago: {
$eq: [
{
$filter: {
input: "$missions",
cond: {
$eq: [
"$$this.location",
"Chicago"
]
}
}
},
"$missions"
]
}
}
}
])
Demo # Mongo Playground
I have the following document structure which contains an array of votes:
{ _id: ObjectId("6350e2c1a15e0e656f4a7472"),
category: 'business',
votes:
[ { voteType: 'like',
userId: ObjectId("62314007da34df3f32f7cfc0") },
{ voteType: 'like',
userId: ObjectId("6356b5cbe2272ebf628451b") } ] }
What I would like to achieve is to add for each document the sum of votes for which voteType = like, while keeping the original document, such as:
[ [{ _id: ObjectId("6350e2c1a15e0e656f4a7472"),
category: 'business',
votes:
[ { voteType: 'like',
userId: ObjectId("62314007da34df3f32f7cfc0") },
{ voteType: 'like',
userId: ObjectId("6356b5cbe2272ebf628451b") } ] }, {sum: 2, voteType: "like"} ], ...]
At the moment, the only workaround that I found is through an aggregation although I cannot manage to keep the original documents in the results:
db.getCollection('MyDocument') .aggregate([ {
$unwind: "$votes" }, {
$match: {
"votes.voteType": "like",
} }, {
$group: {
_id: {
name: "$_id",
type: "$votes.voteType"
},
count: {
$sum: 1
}
} },
{ $sort : { "count" : -1 } }, {$limit : 5}
])
which gives me:
{ _id: { name: ObjectId("635004f1b96e494947caaa5e"), type: 'like' },
count: 3 }
{ _id: { name: ObjectId("63500456b96e494947cbd448"), type: 'like' },
count: 3 }
{ _id: { name: ObjectId("63500353b6c7eb0a01df268e"), type: 'like' },
count: 2 }
{ _id: { name: ObjectId("634e315bb7d17339f8077c39"), type: 'like' },
count: 1 }
You can do it like this:
$cond with $isArray - to check if the votes property is of the type array.
$filter - to filter votes based on voteType property.
$size - to get the sized of the filtered array.
db.collection.aggregate([
{
"$set": {
"count": {
"$cond": {
"if": {
"$isArray": "$votes"
},
"then": {
"$size": {
"$filter": {
"input": "$votes",
"cond": {
"$eq": [
"$$this.voteType",
"like"
]
}
}
}
},
"else": 0
}
}
}
}
])
Working example
So I have document that is structure like this
_id: ObjectId('62bbe17d8fececa06b91873d')
clubName: 'test'
staff:[
'62bbe47f8fececa06b9187d8'
'624f4b56ab4f5170570cdba3' //IDS of staff members
]
A single staff can be assigned to multiple clubs so what I'm trying to achieve is to get all staff that has been assigned to at least one club and display them on a table on the front end, I followed this solution since distinct and skip can't be used on a single query but it just returned this:
[
{ _id: [ '624f5054ab4f5170570cdd16', '624f5054ab4f5170570cdd16' ] } //staff from club 1,
{ _id: [ '624f5054ab4f5170570cdd16', '624f9194ab4f5170570cded1' ] } //staff from club 2,
{ _id: [ '624f4b56ab4f5170570cdba3' ]} //staff from club 3
]
my desired outcome would be like this:
[ _id : ['624f5054ab4f5170570cdd16', '624f9194ab4f5170570cded1', '624f4b56ab4f5170570cdba3'] ]
here's my query:
const query = this.clubModel.aggregate(
[{ $group: { _id: '$staff' } }, { $skip: 0}, { $limit: 10}],
(err, results) => {
console.log(results);
},
);
the values returned are not distinct at all, is there an operation that can evaluate the value inside an array and make them distinct?
Here's my new query after adding the 'createdAt' field in my document structure:
const query = this.clubModel.aggregate([
{ $sort: { createdAt: -1 } },
{
$unwind: '$drivers',
},
{
$project: {
isActive: true,
},
},
{
$group: {
_id: 'null',
ids: {
$addToSet: '$drivers',
},
},
},
{
$project: {
_id: 0,
},
},
{
$skip: skip,
},
{
$limit: limit,
},
]);
Does this works for you, first UNWIND the staff array, and then group on "_id" as null and add staff values using $addToSet:
db.collection.aggregate([
{
"$unwind": "$staff"
},
{
"$group": {
"_id": "null",
"ids": {
"$addToSet": "$staff"
}
}
},
{
"$project": {
"_id": 0,
}
},
{
$skip: 0
},
{
$limit: 10
}
])
Here's the working link.
I'm making a blog and have an query about which would give me better performace, simple lookup or lookup with pipeline because sometime simple lookup gave me fast result and sometime pipleline lookup. So, I am bit confused now which one to use or where to use. Suppose I have 2 collection, user and comment collection.
// Users Collection
{
_id: "MONGO_OBJECT_ID",
userName: "Web Alchemist"
}
// Comments Collection
{
_id: "MONGO_OBJECT_ID",
userId: "USER_MONGO_OBJECT_ID",
isActive: "YES", // YES or NO
comment: "xyz"
}
Now I want to Lookup from users collection to comments, which one would be better for this. I made two query which giving me same result.
[
{
$match: { _id: ObjectId("5d68c019c7d56410cc33b01a") }
},
{
$lookup: {
from: "comments",
as: "comments",
localField: "_id",
foreignField: "userId"
}
},
{
$unwind: "$comments"
},
{
$match: {
"comments.isActive": "YES"
}
},
{ $limit: 5},
{
_id: 1, userName: 1, comments: { _id: "$comments._id", comment: "$comments.comment"}
},
{
$group: {
_id: "$_id",
userName: { '$first': '$userName' },
comments: { $addToSet: "comments"}
}
}
]
OR
[
{
$match: { _id: ObjectId("5d68c019c7d56410cc33b01a") }
},
{
$lookup: {
from: "comments",
as: "comments",
let: { userId: "$_id" },
pipeline: [
{
$match: {
$expr: {
$and: [
{ $eq: ['$userId', '$$userId'] },
{ $eq: ['$isActive', 'YES'] }
]
}
}
},
{ limit: 5 },
{
$project: { _id: 1, comment: 1 }
}
]
}
}
]