I have documents in a collection which look like this:
`{
"_id": { "$oid": "63c6c823131d0b01d353b8d7" },
"customer_id": "5a4c8b63b7055a9109477c5b",
"couponId": "63c6c823131d0b01d353b8d6",
"prefix": 999,
"amount": 1000,
"used": 12,
"keys": {
"375354522485": {
"id": "375354522485",
"used": true
},
"375354538550": {
"id": "375354538550",
"used": false
},
"375354549291": {
"id": "375354549291",
"used": false
}
}
}`
the amount of keys in the object can be thousands (200,000)
I am trying to index the keys by id in mongoose like this:
CouponSeriesSchema.index({ 'keys.*$*.id': 1 });
but the index size does not make sense, it is 20.5KB while the _id index is 36.9KB
I would expect this index size to be much bigger
How should I index the id's?
A smarter design would be this:
{
"_id": { "$oid": "63c6c823131d0b01d353b8d7" },
"customer_id": "5a4c8b63b7055a9109477c5b",
"couponId": "63c6c823131d0b01d353b8d6",
"prefix": 999,
"amount": 1000,
"used": 12,
"keys": [
{
"id": "375354522485",
"used": true
},
{
"id": "375354538550",
"used": false
},
{
"id": "375354549291",
"used": false
}
]
}
Then an index { 'keys.id': 1 } would work.
Related
I have this kind of mongodb document example
"data": {
"2023-02-01": {
"123": {
"price": 100,
},
"234": {
"price": 100,
},
},
"2023-02-02": {
"123": {
"price": 100,
},
"234": {
"price": 100,
},
},
"2023-02-03": {
"123": {
"price": 100,
},
"234": {
"price": 100,
},
},
}
I have list of mapped ID on my aystem, it should be like
ids = [123]
I want to remove the key that not in the list (ids) from the document, started from a specific date (today/"2023-02-02"), the date always updated and so the ID, my expected result is
"data": {
"2023-02-01": {
"123": {
"price": 100,
},
"234": {
"price": 100,
},
},
"2023-02-02": {
"123": {
"price": 100,
},
},
"2023-02-03": {
"123": {
"price": 100,
},
},
}
Could I achieve that on MongoDB aggregation? I'm using pymongo
Following the discussion in comments, if refactoring the schema is an option, you can achieve what you need in very simple query.
db.collection.update({
"date": {
$gte: ISODate("2023-02-02")
}
},
[
{
$set: {
value: {
$filter: {
input: "$value",
as: "v",
cond: {
$in: [
"$$v.key",
[
"123"
]
]
}
}
}
}
}
],
{
multi: true
})
Mongo Playground
The schema I am proposing:
[
{
"date": ISODate("2023-02-01"),
"value": [
{
"key": "123",
"price": 100
},
{
"key": "234",
"price": 100
}
]
},
{
"date": ISODate("2023-02-02"),
"value": [
{
"key": "123",
"price": 100
},
{
"key": "234",
"price": 100
}
]
},
{
"date": ISODate("2023-02-03"),
"value": [
{
"key": "123",
"price": 100
},
{
"key": "234",
"price": 100
}
]
}
]
You can see there is a few things:
avoided using dynamic value as field name
formatted date as proper date objects
avoided highly nesting arrays/objects
I have a Json document in cloudant as:
{
"createdAt": "2022-10-26T09:16:29.472Z",
"user_id": "4499c1c2-7507-4707-b0e4-ec83e2d2f34d",
"_id": "606a4d591031c14a8c48fcb4a9541ff0"
}
{
"createdAt": "2022-10-24T11:15:24.269Z",
"user_id": "c4bdcb54-3d0a-4b6a-a8a9-aa12e45345f3",
"_id": "fb24a15d8fb7cdf12feadac08e7c05dc"
}
{
"createdAt": "2022-10-24T11:08:24.269Z",
"user_id": "06d67681-e2c4-4ed4-b40a-5a2c5e7e6ed9",
"_id": "2d277ec3dd8c33da7642b72722aa93ed"
}
I have created a index json as:
{
"type": "json",
"partitioned": false,
"def": {
"fields": [
{
"createdAt": "asc"
},
{
"user_id": "asc"
}
]
}
}
I have created a index text as:
{
"type": "text",
"partitioned": false,
"def": {
"default_analyzer": "keyword",
"default_field": {},
"selector": {},
"fields": [
{
"_id": "string"
},
{
"createdAt": "string"
},
{
"user_id": "string"
}
],
"index_array_lengths": true
}
}
I have created a selctor cloudant query :
{
"selector": {
"$and": [
{
"createdAt": {
"$exists": true
}
},
{
"user_id": {
"$exists": true
}
}
]
},
"fields": [
"createdAt",
"user_id",
"_id"
],
"sort": [
{
"createdAt": "desc"
}
],
"limit": 10,
"skip": 0
}
This code work fine inside the cloudant ambient.
My problem is in the Search Index.
I created this function code that works,
function (doc) {
index("specialsearch", doc._id);
if(doc.createdAt){
index("createdAt", doc.createdAt, {"store":true})
}
if(doc.user_id){
index("user_id", doc.user_id, {"store":true})
}
}
result by this url:
// https://[user]-bluemix.cloudant.com/[database]/_design/attributes/_search/by_all?q=*:*&counts=["createdAt"]&limit=2
{
"total_rows": 10,
"bookmark": "xxx",
"rows": [
{
"id": "fb24a15d8fb7cdf12feadac08e7c05dc",
"order": [
1.0,
0
],
"fields": {
"createdAt": "2022-10-24T11:15:24.269Z",
"user_id": "c4bdcb54-3d0a-4b6a-a8a9-aa12e45345f3"
}
},
{
"id": "dad431735986bbf41b1fa3b1cd30cd0f",
"order": [
1.0,
0
],
"fields": {
"createdAt": "2022-10-24T11:07:02.138Z",
"user_id": "76f03307-4497-4a19-a647-8097fa288e77"
}
},
{
"id": "2d277ec3dd8c33da7642b72722aa93ed",
"order": [
1.0,
0
],
"fields": {
"createdAt": "2022-10-24T11:08:24.269Z",
"user_id": "06d67681-e2c4-4ed4-b40a-5a2c5e7e6ed9"
}
}
]
}
but it doesn't return the id sorted by date based on the createdAt and user_id keys.
What I would like is to get a list of an organized search with the index of the createdAt and user_id keys without having to indicate the value; a wildcard type search
Where am I wrong?
I have read several posts and guides but I did not understand how to do it.
Thanks for your help.
You say you want to return a list of id, createdAt and user_id, sorted by createdAt and user_id. And that you want all the documents returned.
If that is the case, what you need to do is simply create a MapReduce view of your data that emits the createdAt and user_id fields in that order, i.e. :
function (doc) {
emit([doc.createdAt, doc.user_id], 1);
}
You don't need to include the document id because that comes for free.
You can then query the view by visiting the URL:
https://<URL>/<database>/_design/<ddoc_name>/_view/<view_name>
You will get all the docs like this:
{"total_rows":3,"offset":0,"rows":[
{"id":"2d277ec3dd8c33da7642b72722aa93ed","key":["2022-10-24T11:08:24.269Z","06d67681-e2c4-4ed4-b40a-5a2c5e7e6ed9"],"value":1},
{"id":"fb24a15d8fb7cdf12feadac08e7c05dc","key":["2022-10-24T11:15:24.269Z","c4bdcb54-3d0a-4b6a-a8a9-aa12e45345f3"],"value":1},
{"id":"606a4d591031c14a8c48fcb4a9541ff0","key":["2022-10-26T09:16:29.472Z","4499c1c2-7507-4707-b0e4-ec83e2d2f34d"],"value":1}
]}
I have a collection where from the backend user can input multiple same name bikes but with different registration number but in front-End I want them to be grouped by matching the same name but as user updates separately display image changes but I want only one display image as it is 1 vehicle
provided there is a node created I will implement it we can sort it by the latest and take the price and image of it
Activa -2 Count
KTM -1 Count
but there is a catch.
Activa 2 bikes but I want only count 2 and the price as it is the same in an array I want only 1 and the same applies to displayimage here display image file path is different but I want the latest one only Sharing data below
Data:
[
{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62e69ee3edfe4d0f3cb4994a",
"bikename": "KTM",
"bikenumber": "KA05HM2034",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-2020-honda-city-exterior-8-1659281111883.jpg",
"file_path": "https://www.example.com/images/upload/bike-2020-honda-city-exterior-8-1659281111883.jpg",
"idx": 1
}
},
{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62dba8418ef8f51f454ed757",
"bikename": "Activa",
"bikenumber": "KA05HM2033",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-v_activa-i-deluxe-1658562557459.jpg",
"file_path": "https://www.example.com/images/upload/bike-v_activa-i-deluxe-1658562557459.jpg",
"idx": 0
}
},
{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62d7ff7e70b9ab38c6ab0cb1",
"bikename": "Activa",
"bikenumber": "KA05HM2223",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"afterfreekmprice": 22,
"descreption": "Activa",
"displayimage": {
"file": "bike-v_activa-i-deluxe-1658322798414.jpg",
"file_path": "https://www.example.com/images/upload/bike-v_activa-i-deluxe-1658322798414.jpg",
"idx": 0
}
}
]
Expected:
[
{
"_id":{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62dba8418ef8f51f454ed757",
"bikename": "Activa",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-v_activa-i-deluxe-1658562557459.jpg",
"file_path": "https://www.example.com/images/upload/bike-v_activa-i-deluxe-1658562557459.jpg",
"idx": 0
}
},
"count": 2
},
{
"_id":{
"price": [
{
"Description": "Hourly",
"Price": "1"
},
{
"Description": "Daily",
"Price": "11"
},
{
"Description": "Monthly",
"Price": "111"
}
],
"_id": "62e69ee3edfe4d0f3cb4994a",
"bikename": "KTM",
"bikebrand": {
"id": 1,
"label": "Honda"
},
"freekm": 234,
"displayimage": {
"file": "bike-2020-honda-city-exterior-8-1659281111883.jpg",
"file_path": "https://www.example.com/images/upload/bike-2020-honda-city-exterior-8-1659281111883.jpg",
"idx": 1
}
}
"count": 1
}
]
You can use the aggregation pipeline,
$sort by _id in descending order
$group by bikename and get the first root document that is latest one in root and count total documents in count
$project to show required documents
db.collection.aggregate([
{ $sort: { _id: -1 } },
{
$group: {
_id: "$bikename",
root: { $first: "$$ROOT" },
count: { $sum: 1 }
}
},
{
$project: {
_id: "$root",
count: 1
}
}
])
Playground
You can use $group for this:
db.collection.aggregate([
{$group: {
_id: "$bikename",
count: {$sum: 1},
data: {$first: "$$ROOT"}
}
},
{$set: {"data.count": "$count"}},
{$replaceRoot: {newRoot: "$data"}}
])
See how it works on the playground example
Here is a sample product document stored in MongoDB:
[
{
"_id": "....",
"user_id": "....",
"username": "....",
// omitted
"product": {
"description": "A stunningly beautiful page with a constant growth of followers, etc. ❤",
"banner_img": "https://tse3-mm.cn.bing.net/th/id/OIP.jNCbt_c_8vnq7sbWluCVnQHaCG?w=300&h=85&c=7&o=5&pid=1.7",
"niches": "Fashion & Style",
"categories": [
{
"type": "Single",
"pricing": [
{
"time": 6,
"price": 15,
"bio_price": 10
},
{
"time": 12,
"price": 20,
"bio_price": 10
}
]
},
{
"type": "Multiple",
"pricing": [
{
"time": 12,
"price": 30.5,
"bio_price": 15
}
]
},
{
"type": "Story",
"pricing": [
{
"time": 24,
"price": 40,
"bio_price": 20
}
]
}
]
},
"created_at": "2020-01-11T18:19:54.312Z",
"updated_at": "2020-01-11T18:19:54.312Z"
}
],
I'd like to find an account that has a product with Multiple or Story pricing type. My query is as follows:
{
product: {
categories: {
pricing: {
$elemMatch: {
type: { $in: ['Multiple', 'Story'] }
}
}
}
}
}
I'm running this query with lucid-mongo in adonisjs framework.
It should at least return one document but it returns nothing.
I ran the query both in framework and on mongo.exe but not works.
What's wrong with my query?
I have my json object like this
{
"_id": "5c2e811154855c0012308f00",
"__pclass": "QXRzXFByb2plY3RcTW9kZWxcUHJvamVjdA==",
"id": 44328,
"name": "Test project via postman2//2",
"address": "some random address",
"area": null,
"bidDate": null,
"building": {
"name": "Health Care Facilities",
"type": "Dental Clinic"
},
"collaborators": [],
"createdBy": {
"user": {
"id": 7662036,
"name": "Someone Here"
},
"firm": {
"id": 2520967,
"type": "ATS"
}
},
"createdDate": "2019-01-03T21:39:29Z",
"customers": [],
"doneBy": null,
"file": null,
"firm": {
"id": 1,
"name": "MyFirm"
},
"leadSource": {
"name": "dontknow",
"number": "93794497"
},
"location": {
"id": null,
"city": {
"id": 567,
"name": "Bahamas"
},
"country": {
"id": 38,
"name": "Canada"
},
"province": {
"id": 7,
"name": "British Columbia"
}
},
"modifiedBy": null,
"modifiedDate": null,
"projectPhase": {
"id": 1,
"name": "pre-design"
},
"quotes": [{
"id": 19,
"opportunityValues": {
"Key1": 100,
"Key2 Key2": 100,
"Key3 Key3 Key3": 200,
}
}],
"specForecast": [],
"specIds": [],
"tags": [],
"valuation": "something"
}
I am trying to aggregate using this query in MongoDB. My aggregation key is 4 level deep and also contains spaces. On all online examples shows me the aggregation at the first level. Looking to the online codes, I tried to re-iterate the same with my 4th level deep key.
db.mydata.aggregate([
{$match: {"id": 44328 } } ,
{$group: { _id: "$quotes.id",
totalKey2:{ $sum: "$quotes.opportunityValues.Key2 Key2"},
totalKey3:{ $sum: "$quotes.opportunityValues.Key3 Key3 Key3"}
}
}
]);
This should return
_id totalKey2 totalKey3
0 19 100 300
But it is returning
_id totalKey2 totalKey3
0 19 0 0
What am I doing Wrong?
Although it's not recommended to use space in field names in Mongo, it works as expected.
The problem with your query is that "quotes" is an array and you should first unwind it before grouping it.
This works as expected:
db.mydata.aggregate([
{ $match: { "id": 44328 } } ,
{ $unwind: "$quotes" },
{ $group: { _id: "$quotes.id",
totalKey2:{ $sum: "$quotes.opportunityValues.Key2 Key2" },
totalKey3:{ $sum: "$quotes.opportunityValues.Key3 Key3 Key3" } }
}
]);