I am trying to find the latest "order" in "orders" array in the whole collection (Not only in the one object).
Data:
[
{
_id: 1,
orders: [
{
title: 'Burger',
date: {
$date: '2021-07-18T13:12:08.717Z',
},
},
],
},
{
_id: 2,
orders: [
{
title: 'Salad',
date: {
$date: '2021-07-18T13:35:01.586Z',
},
},
],
},
];
Code:
var restaurant = await Restaurant.findOne({
'orders.date': 1,
});
Rather simple:
db.collection.aggregate([
{ $project: { latest_order: { $max: "$orders.date" } } }
])
If you like to get the full order use this:
db.collection.aggregate([
{
$project: {
latest_order: {
$first: {
$filter: {
input: "$orders",
cond: { $eq: [ "$$this.date", { $max: "$orders.date" } ] }
}
}
}
}
},
{ $sort: { "latest_order.date": 1 } },
{ $limit: 1 }
])
Mongo Playground
You have to use aggregation for that
db.collection.aggregate([
{ $unwind: "$orders" },
{ $sort: { "orders.date": -1 } },
{ $limit: 1 },
{
"$group": {
"_id": "$_id",
"orders": { "$first": "$orders" }
}
}
])
Working Mongo playground
Related
I have a Mongo database filled with "Events" records, that look like this:
{
timestamp: 2022-03-15T22:11:34.711Z,
_id: new ObjectId("62310f16b0d71321e887a905")
}
Using a NodeJs server, I need to fetch the last 30 days of Events, grouped/summed by date, and any dates within that 30 days with no records need to be filled with 0.
Using this code I can get the correct events, grouped/summed by date:
Event.aggregate( [
{
$match: {
timestamp: {
$gte: start,
$lte: end,
}
}
},
{
$project: {
date: {
$dateToParts: { date: "$timestamp" }
},
}
},
{
$group: {
_id: {
date: {
year: "$date.year",
month: "$date.month",
day: "$date.day"
}
},
"count": { "$sum": 1 }
}
}
] )
This will return something like this:
[
{
"_id": {
"date": {
"year": 2022,
"month": 3,
"day": 14
}
},
"count": 3
},
{
"_id": {
"date": {
"year": 2022,
"month": 3,
"day": 15
}
},
"count": 8
},
]
I also have this Javascript code to generate the last 30 days of dates:
const getDateRange = (start, end) => {
const arr = [];
for(let dt = new Date(start); dt <= end; dt.setDate(dt.getDate() + 1)){
arr.push(new Date(dt));
}
return arr;
};
const subtractDays = (date, days) => {
return new Date(date.getTime() - (days * 24 * 60 * 60 * 1000));
}
const end = new Date();
const start = subtractDays(end, 30);
const range = getDateRange(start, end);
Which returns something like this:
[
2022-03-09T01:13:10.769Z,
2022-03-10T01:13:10.769Z,
2022-03-11T01:13:10.769Z,
2022-03-12T01:13:10.769Z,
2022-03-13T01:13:10.769Z,
...
]
It seems like I have all the pieces, but I'm having trouble putting all this together to do what I need in an efficient way. Any push in the right direction would be appreciated.
Whenever one has to work with date/time arithmetic then I recommend a library like moment.js
const end = moment().startOf('day').toDate();
const start = moment().startOf('day').subtract(30, 'day').toDate();
In MongoDB version 5.0 you can use $dateTrunc(), which is shorter than $dateToParts and { year: "$date.year", month: "$date.month", day: "$date.day" }
You need to put all data in an array ({$group: {_id: null, data: { $push: "$$ROOT" }}) and then at missing elements with $ifNull:
event.aggregate([
{
$match: {
timestamp: { $gte: start, $lte: end }
}
},
{
$group: {
_id: { $dateTrunc: { date: "$timestamp", unit: "day" } },
count: { $sum: 1 }
}
},
{ $project: {timestamp: "$_id", count: 1, _id: 0} },
{
$group: {
_id: null,
data: { $push: "$$ROOT" }
}
},
{
$set: {
data: {
$map: {
input: { $range: [0, 30] },
as: "i",
in: {
$let: {
vars: {
day: { $dateAdd: { startDate: start, amount: "day", unit: "$$i" } }
},
in: {
$ifNull: [
{
$first: {
$filter: {
input: "$data",
cond: { $eq: ["$$this.timestamp", "$$day"] }
}
}
},
{ timestamp: "$$day", count: 0 }
]
}
}
}
}
}
}
},
{ $unwind: "$data" }
])
$range operator supports only integer values, that's the reason for using $let. Otherwise, if you prefer to use the external generated range, it would be
{
$set: {
data: {
$map: {
input: range,
as: "day",
in: {
$ifNull: [
{
$first: {
$filter: {
input: "$data",
cond: { $eq: ["$$this.timestamp", "$$day"] }
}
}
},
{ timestamp: "$$day", count: 0 }
]
}
}
}
}
}
And for MongoDB version 5.1 you may have a look at $densify
Use aggregation stage densify if you're using MongoDB version 5.1 or later. But for lower version, below query can be used.
db.collection.aggregate([
{
$match: {
timestamp: {
$gte: {
"$date": "2022-03-01T00:00:00.000Z"
},
$lte: {
"$date": "2022-03-31T23:59:59.999Z"
},
}
}
},
{
$project: {
date: {
$dateToParts: {
date: "$timestamp"
}
},
}
},
{
$group: {
_id: {
date: {
year: "$date.year",
month: "$date.month",
day: "$date.day"
}
},
"count": {
"$sum": 1
}
}
},
{
"$group": {
"_id": null,
"originData": {
"$push": "$$ROOT"
}
}
},
{
"$project": {
"_id": 0,
"data": {
"$concatArrays": [
{
"$map": {
"input": {
"$range": [
0,
30,
1
]
},
"in": {
"$let": {
"vars": {
"date": {
"$add": [
{
"$date": "2022-03-01T00:00:00.000Z"
},
{
"$multiply": [
"$$this",
86400000
]
}
]
}
},
"in": {
"_id": {
"date": {
"day": {
"$dayOfMonth": "$$date"
},
"month": {
"$month": "$$date"
},
"year": {
"$year": "$$date"
}
}
},
"count": 0
}
}
}
}
},
"$originData"
]
}
}
},
{
"$unwind": "$data"
},
{
$group: {
_id: {
date: {
year: "$data._id.date.year",
month: "$data._id.date.month",
day: "$data._id.date.day"
}
},
"count": {
"$sum": "$data.count"
}
}
},
{
"$sort": {
"_id.date.year": 1,
"_id.date.month": 1,
"_id.date.day": 1
}
}
])
Link to online playground. https://mongoplayground.net/p/5I0I04HoHXm
Orders.aggregate([{$match: { shippingType: "standardShipping" }},
{ $project: { standardShippingCount: { $size: "$products" } } },
])
Orders.aggregate([{$match: { shippingType: "expressShipping" } },
{ $project: { expressShippingCount: { $size: "$products" } } },
])
I need help to find out if it's possible to write these 2 queries in 1. Any help is appericated.
If you only need the number of total products ordered with each shippingType from the whole collection, then you can use this aggregate query
[
{
$unwind: {
path: "$products"
},
},
{
$group: {
_id: "$shippingType",
count: {
$count: {}
}
}
},
]
It will give you a response in this format
[
{
"_id": "expressShipping",
"count": 14
},
{
"_id": "standardShipping",
"count": 6
}
]
Now to convert it into a format that suits your use-case
queryResponse.reduce((acc, curr) => {
acc[`${curr._id}Count`] = curr.count;
return acc;
}, {})
Finally, you'll have this
{
expressShippingCount: 14,
standardShippingCount: 6
}
I have schema like below
[
{
id:"111"
tags:[222,333,444,555]
},
{
id: "222"
tags:[312,345,534]
},
{
id:"333"
tags:[111,222,333,444,555]
},
]
I want to find all documents where tags array size is greater than document size returned by $match in aggregation pipeline, so in above Ex. the number of documents are 3 so i want to return all documents having tags array size greater that 3
[
{
id:"111"
tags:[222,333,444,555]
},
{
id:"333"
tags:[111,222,333,444,555]
},
]
I am using aggregation pipeline to process other info, I am stuck at how to have store document size so that i can find all tags greater than document size
below is query which i am using, i want to do it in aggregation and in one call
.aggregate([
{
"$match":{
"ids":{
"$in":[
"111",
"222",
"333"
]
}
}
})]
Facet helps you to solve this problem.
$facet helps to categorize the incoming documents. We use totalDoc for counting the document and allDocuments for getting all the documents
$arrayElemAt helps to get the first object from totalDoc where we already know that only one object should be inside the totalDoc. Because when we group it, we use _id:null
$unwind helps to de-structure the allDocuments array
Here is the code
db.collection.aggregate([
{
$facet: {
totalDoc: [
{
$group: {
_id: null,
count: {
$sum: 1
}
}
}
],
allDocuments: [
{
$project: {
tags: 1
}
}
]
}
},
{
$addFields: {
totalDoc: {
"$arrayElemAt": [
"$totalDoc",
0
]
}
}
},
{
$unwind: "$allDocuments"
},
{
$addFields: {
sizeGtDoc: {
$gt: [
{
$size: "$allDocuments.tags"
},
"$totalDoc.count"
]
}
}
},
{
$match: {
sizeGtDoc: true
}
},
{
"$replaceRoot": {
"newRoot": "$allDocuments"
}
}
])
Working Mongo playground
You can try,
$match you condition
$group by null and make root array of documents and get count of root documents in count
$unwind deconstruct root array
$match tags size and count greater than or not using $expr expression match
$replaceRoot to replace root object in root
db.collection.aggregate([
{ $match: { id: { $in: ["111", "222", "333"] } } },
{
$group: {
_id: null,
root: { $push: "$$ROOT" },
count: { $sum: 1 }
}
},
{ $unwind: "$root" },
{ $match: { $expr: { $gt: [{ $size: "$root.tags" }, "$count"] } } },
{ $replaceRoot: { newRoot: "$root" } }
])
Playground
Second option:
first 2 stages $match and $group both are same as like above query,
$project to filter root array match condition if tags size and count greater than or not, this will return filtered root array
$unwind deconstruct root array
$replaceRoot replace root object to root
db.collection.aggregate([
{ $match: { id: { $in: ["111", "222", "333"] } } },
{
$group: {
_id: null,
root: { $push: "$$ROOT" },
count: { $sum: 1 }
}
},
{
$project: {
root: {
$filter: {
input: "$root",
cond: { $gt: [{ $size: "$$this.tags" }, "$count"] }
}
}
}
},
{ $unwind: "$root" },
{ $replaceRoot: { newRoot: "$root" } }
])
Playground
You can skip $unwind and $replaceRoot stages if you want because this query always return one document in root, so you can easily access like this result[0]['root'], you can save 2 stages processing and execution time.
You could use $facet to get two streams i.e. one with the filtered documents and the counts using $count. The resulting streams can then
be aggregated further with a $filter as follows to get the desired result
db.getCollection('collection').aggregate([
{ '$facet': {
'counts': [
{ '$match': { 'id': { '$in': ['111', '222', '333'] } } },
{ '$count': "numberOfMatches" }
],
'docs': [
{ '$match': { 'id': { '$in': ['111', '222', '333'] } } },
]
} },
{ '$project': {
'result': {
'$filter': {
'input': '$docs',
'cond': {
'$gt': [
{ '$size': '$$this.tags' },
{ '$arrayElemAt': ['$counts.numberOfMatches', 0] }
]
}
}
}
} }
])
I am trying to wrap my head around the query which I am trying to make with mongoose on Node JS. Here is my dataset:
{"_id":{"$oid":"5e49c389e3c23a1da881c1c9"},"name":"New York","good_incidents":{"$numberInt":"50"},"salary":{"$numberInt":"50000"},"bad_incidents":"30"}
{"_id":{"$oid":"5e49c3bbe3c23a1da881c1ca"},"name":"Cairo","bad_incidents":{"$numberInt":"59"},"salary":{"$numberInt":"15000"}}
{"_id":{"$oid":"5e49c42de3c23a1da881c1cb"},"name":"Berlin","incidents":{"$numberInt":"30"},"bad_incidents":"15","salary":{"$numberInt":"55000"}}
{"_id":{"$oid":"5e49c58ee3c23a1da881c1cc"},"name":"New York","good_incidents":{"$numberInt":"15"},"salary":{"$numberInt":"56500"}}
What I am trying to do is get these values:
The most repeated city in collection
The average of bad_incidents
The maximum value of good_incidents
Maximum salary where there are no bad_incidents
I am trying to wrap my head around how I can do this in one query, because I only need one value per field. I would be glad if somebody would lead me on the right track. No need for full solution
Regards!
You may perform MongoDB aggregation with $facet operator which allows compute several aggregation at once.
db.collection.aggregate([
{
$facet: {
repeated_city: [
{
$group: {
_id: "$name",
name: {
$first: "$name"
},
count: {
$sum: 1
}
}
},
{
$match: {
count: {
$gt: 1
}
}
},
{
$sort: {
count: -1
}
},
{
$limit: 1
}
],
bad_incidents: [
{
$group: {
_id: null,
avg_bad_incidents: {
$avg: {
$toInt: "$bad_incidents"
}
}
}
}
],
good_incidents: [
{
$group: {
_id: null,
max_good_incidents: {
$max: {
$toInt: "$good_incidents"
}
}
}
}
],
max_salary: [
{
$match: {
bad_incidents: {
$exists: false
}
}
},
{
$group: {
_id: null,
max_salary: {
$max: {
$toInt: "$salary"
}
}
}
}
]
}
},
{
$replaceWith: {
$mergeObjects: [
{
$arrayElemAt: [
"$repeated_city",
0
]
},
{
$arrayElemAt: [
"$bad_incidents",
0
]
},
{
$arrayElemAt: [
"$good_incidents",
0
]
},
{
$arrayElemAt: [
"$max_salary",
0
]
}
]
}
}
])
MongoPlayground
[
{
"_id": null,
"avg_bad_incidents": 34.666666666666664,
"count": 2,
"max_good_incidents": 50,
"max_salary": 56500,
"name": "New York"
}
]
I have 4 collections for store order data.
1. order => field => _id, order_no, cust_id, order_date
2. order_address => field => _id, order_id, cust_name, mobile, address
3. order_details => field => _id, order_id, product_id, seller_id, qty, price
4. order_payment => field => _id, payment_type, payment_status
in that order_details collection has n number of record for a number of product in one order.
in that how to get particular seller order from my data using aggregate in node.js from MongoDB database
i try this code but it's show ordre_details = [] but show order in my result:
var query = [
{ "$lookup": {
from: 'order_details',
let: { order_id: "$_id" },
pipeline: [
{ $match: { $expr: { $and: [{ $eq: [ "$order_id", "$$order_id" ] }, { $eq: [ "$seller_id", ObjectID(seller_id) ] }] } } },
{ $project: {
amount: 1,
cod_charge: 1,
shipping_charge: 1,
pid: 1,
product_attribute_id: 1,
qty: 1
} },
{ "$lookup": {
from: 'product',
let: { product_id: "$pid", product_attribute_id: '$product_attribute_id'},
pipeline: [
{ $match: { $expr: { $eq: [ "$_id", "$$product_id" ] } } },
{ $project: { _id: 1, name: 1, sku: 1 } },
{ "$lookup": {
from: 'product_image',
let: { product_attribute_id: '$$product_attribute_id' },
pipeline: [
{ $match: { $expr: { $eq: [ "$product_attribute_id", "$$product_attribute_id" ] } } },
{ $project: { _id: 0, image: 1, is_default: 1 } },
{ $sort : { is_default: -1 } },
{ $replaceRoot: { newRoot: {_id: "$_id", image: "$image" } } }
],
as: 'product_image'
} },
{ $replaceRoot: { newRoot: {
_id: "$_id",
name: "$name",
sku: "$sku",
image: { $arrayElemAt: [ "$product_image.image", 0 ] }
} } }
],
as: 'product'
} },
{ "$replaceRoot": { newRoot: {
_id: '$$ROOT._id',
pid: '$$ROOT.pid',
amount: '$$ROOT.amount',
cod_charge: '$$ROOT.cod_charge',
shipping_charge: '$$ROOT.shipping_charge',
product_attribute_id: "$$ROOT.product_attribute_id",
qty: "$$ROOT.qty",
product: { $arrayElemAt: [ "$product", 0 ] },
} } },
],
as: 'order_details'
} },
{ "$replaceRoot": {
newRoot: {
_id: "$_id",
order_no: "$order_no",
cust_id: "$cust_id",
order_date: "$order_date",
order_details: "$order_details"
}
} }
]
orderModel.order.aggregate(query, function(err, orderData){})