Right now I have a lookup stage that matches a collection of answers with their respective questions. The problem I'm having is that on the $match if the question does not having a matching answer document in the lookup collection it is removed from the results of the aggregation. How can I avoid this?
{
$lookup: {
from: 'groupansphotos',
let: { question_id: '$questions._id' },
pipeline: [
{
$match: {
$expr: { $eq: ['$_id', '$$question_id'] },
},
},
{ $unwind: '$answers' },
{ $match: { 'answers.reported': { $lt: 1 } } },
{ $sort: { 'answers.helpful': -1 } },
{ $limit: 2 },
{
$project: {
_id: 0,
k: { $toString: '$answers._id' }, // k
v: '$$ROOT.answers', // v
},
},
],
as: 'answers',
},
},
Related
I am quite new to MongoDB. And I have a Mongo aggregate query that takes 5 minutes on 10k+ documents. That doesn't seem right. Basically Products and SKUs have a 1-to-many relationship and I want to find all products with SKUs greater than 0.00001
products = await this.productModel.aggregate([
{
$lookup: {
from: 'skus',
let: { myid: '$_id' },
pipeline: [
{
$match: {
$expr: {
$and: [
{ $eq: ['$product', '$$myid'] },
{ $gt: ['$quantity', 0.00001] },
],
},
},
},
],
as: 'skus',
},
},
{
$addFields: {
id: '$_id',
skusize: { $size: '$skus' },
},
},
{
$match: { skusize: { $gt: 0 } },
},
]);
I am new to mongodb,
I'm trying to extract expectedDeliveryTime from the following data:
{
"from": "Giza",
"delivery_rule": [
{
"to": "Giza",
"expectedDeliveryTime": 3
},
{
"to": "Riyadh",
"expectedDeliveryTime": 2
}
]
}
I am trying to fetch expectedDeliveryTime WHERE from='Giza' and to='Riyadh'
MySQL equivalent would be SELECT expectedDeliveryTime FROM delivery_rules AS d WHERE d.from='Giza' AND d.to='Giza'
Below is part of my code
{
$lookup: {
from: 'Setting',
pipeline: [
{
$match: {
$expr: { $eq: ['$name', 'delivery_rules'] },
},
}
],
as: 'delivery_rules',
}
},
{
$addFields: {
delivery_rules: "$delivery_rules.value"
}
},
{ $unwind: '$delivery_rules' },
{
$addFields: {
delivery_rules: {
$filter: {
input: "$delivery_rules",
as: "rule",
cond: {
$eq: [
"$$rule.from",
"Giza"
]
},
}
}
}
},
{
$group: {
expectedDeliveryTime: { $first: '$delivery_rules' },
}
},
{
$project: {
_id: 0,
expectedDeliveryTime: 1,
}
}
You can solve this using simply $match and $unwind
db.collection.aggregate([
{
"$match": {
"from": "Giza"
}
},
{
"$unwind": "$delivery_rule"
},
{
"$match": {
"delivery_rule.to": "Riyadh"
}
},
{
$project: {
_id: 0,
expectedDeliveryTime: "$delivery_rule.expectedDeliveryTime"
}
}
])
Here is the Mongo playground for your reference.
This is my first experience using aggregate pipeline. I'm not able to get a "$match" expression to work inside the pipeline. If I remove the "_id" match, I get every document in the collection past the start date, but once I add the $eq expression, it returns empty.
I read a lot of other examples and tried many different ways, and this seems like it is correct. But the result is empty.
Any suggestions?
let now = new Date()
let doc = await Team.aggregate([
{ $match: { created_by: mongoose.Types.ObjectId(req.params.user_oid)} },
{ $sort: { create_date: 1 } },
{ $lookup: {
from: 'events',
let: { "team_oid": "$team_oid" },
pipeline: [
{ $addFields: { "team_oid" : { "$toObjectId": "$team_oid" }}},
{ $match: {
$expr: {
$and: [
{ $gt: [ "$start", now ] },
{ $eq: [ "$_id", "$$team_oid" ] }
]
},
}
},
{
$sort: { start: 1 }
},
{
$limit: 1
}
],
as: 'events',
}},
{
$group: {
_id: "$_id",
team_name: { $first: "$team_name" },
status: { $first: "$status" },
invited: { $first: "$invited" },
uninvited: { $first: "$uninvited" },
events: { $first: "$events.action" },
dates: { $first: "$events.start" } ,
team_oid: { $first: "$events.team_oid" }
}
}])
Example Docs (added by request)
Events:
_id:ObjectId("60350837c57b3a15a414d265")
invitees:null
accepted:null
sequence:7
team_oid:ObjectId("60350837c57b3a15a414d263")
type:"Calendar Invite"
action:"Huddle"
status:"Questions Issued"
title:"Huddle"
body:"This is a Huddle; you should receive new questions 5 days befor..."
creator_oid:ObjectId("5ff9e50a206b1924dccd691e")
start:2021-02-26T07:00:59.999+00:00
end:2021-02-26T07:30:59.999+00:00
__v:0
Team:
_id:ObjectId("60350837c57b3a15a414d263")
weekly_schedule:1
status:"Live"
huddle_number:2
reminders:2
active:true
created_by:ObjectId("5ff9e50a206b1924dccd691e")
team_name:"tESTI"
create_date:2021-02-23T13:50:47.172+00:00
__v:0
This is just a guess since you don't have schema in your question. But it looks like your have some of your _ids mixed up. Where you are currently trying to $match events whose _id is equal to a team_oid. Rather than the event's team_oid field being equal to the current 'team' _id.
I'm pretty confident this will produce the correct output. If you post any schema or sample docs I will edit it.
https://mongoplayground.net/p/5i1w2Ii7KCR
let now = new Date()
let doc = await Team.aggregate([
{ $match: { created_by: mongoose.Types.ObjectId(req.params.user_oid)} },
{ $sort: { create_date: 1 } },
{ $lookup: {
from: 'events',
// Set tea_oid as the current team _id
let: { "team_oid": "$_id" },
pipeline: [
{ $match: {
$expr: {
$and: [
{ $gt: [ "$start", now ] },
// Match events whose 'team_oid' field matches the 'team' _id set above
{ $eq: [ "$team_oid", "$$team_oid" ] }
]
},
}
},
{
$sort: { start: 1 }
},
{
$limit: 1
}
],
as: 'events',
}},
{
$group: {
_id: "$_id",
team_name: { $first: "$team_name" },
status: { $first: "$status" },
invited: { $first: "$invited" },
uninvited: { $first: "$uninvited" },
events: { $first: "$events.action" },
dates: { $first: "$events.start" } ,
team_oid: { $first: "$events.team_oid" }
}
}])
I am trying to get the total count of documents which match my pipeline operators and then after I get that count of all of them I would like to use $skip and $limit to return a subset for pagination. Right now I am basically doing the same aggregation twice - once to get the count of all matches and once to do the skip/limit. Can this be done using one aggregation pipeline?
To get the count I do
let [count] = await MyModel.aggregate([
{
$match: {
store: mongoose.Types.ObjectId(storeId),
},
},
{
$lookup: {
from: "resaleitems",
let: {
store: "$store",
},
as: "itemsForSale",
pipeline: [
{
$match: {
$expr: {
$eq: ["$store", "$$store"],
},
},
},
],
},
},
{
$match: {
"itemsForSale.0": { $exists: true },
},
},
{ $count: "totalCount" },
]).exec();
and then right after to get the skipped and limited results I do basically the same thing, but have added the $skip and $limit steps
let items = await MyModel.aggregate([
{
$match: {
store: mongoose.Types.ObjectId(storeId),
},
},
{ $skip: skip.toNumber() },
{ $limit: bnLimit.toNumber() },
{
$lookup: {
from: "resaleitems",
let: {
store: "$store",
},
as: "itemsForSale",
pipeline: [
{
$match: {
$expr: {
$eq: ["$store", "$$store"],
},
},
},
],
},
},
{
$match: {
"itemsForSale.0": { $exists: true },
},
},
]).exec();
Multi level $lookup sort not working in aggregation.
Sorting works only for country, state name. Tried applying sorting for cities, but country sort overwrites the city sort.
Query2 is working but i don't want to sort collections inside lookup pipeline.
Is there any way to achieve all level of sorting(country,state,city) in Query1
Query1(Not Working):
Country.aggregate([
{
$lookup:{
from: 'states',
localField:'_id',
foreignField:'countryId',
as:'states'
}
},
{
$unwind: {
path: "$states",
preserveNullAndEmptyArrays: true
}
},
{
$sort: {
'states.name': 1
}
},
{
$lookup:{
from: 'cities',
localField:'states._id',
foreignField:'stateId',
as:'states.cities'
}
},
{
$sort: {
'states.cities.name': 1
}
},
{
$group: {
_id: {
_id: '$_id',
name: '$name'
},
states: {
$push: '$states'
}
}
},
{
$project: {
_id: '$_id._id',
name: '$_id.name',
states: 1
}
},
{
$sort: {
name: 1
}
}
])
Query2(Working):
Execution time is 8 times higher than Query1.
[
{
$lookup : {
from : 'states',
let: { 'countryId': '$_id' },
pipeline: [
{
$match: {
$expr:
{
$eq: ['$countryId', '$$countryId']
}
}
},
{
$sort : {
name : -1
}
}
],
as : 'states'
}
},
{
$unwind: {
path: '$states',
preserveNullAndEmptyArrays: true
}
},
{
$lookup : {
from : 'cities',
let: { 'stateId': '$states._id' },
pipeline: [
{
$match: {
$expr:
{
$eq: ['$stateId', '$$stateId']
}
}
},
{
$sort : {
name : -1
}
}
],
as : 'states.cities'
}
},
{
$group: {
_id: {
_id: '$_id',
name: '$name'
},
states: {
$push: '$states'
}
}
},
{
$project: {
_id: '$_id._id',
name: '$_id.name',
states: 1
}
}
]
In the newer $lookup syntax you do not need to use $unwind to join nested fields. You can easily use $lookup inside the pipeline to join multiple level.
[
{ "$lookup": {
"from": "states",
"let": { "countryId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$countryId", "$$countryId"] }}},
{ "$lookup": {
"from": "cities",
"let": { "stateId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$stateId", "$$stateId"] }}},
{ "$sort": { "name": -1 }}
],
"as": "cities"
}},
{ "$sort": { "name": -1 }}
],
"as": "states"
}}
]