I've already successfully used an embedded document to create a nested amenities attribute, under a spot in my database, but now I'd like to populate it with true values. (by default they're false) The object that I created on mongoDB looks like this so far:
And on Postman, when I go to my spots index, this is what a spot looks like:
[
{
"amenities": {
"wifi": false,
"kitchen": false,
"breakfast": false,
"parking": false,
"pool": false,
"essentials": false
},
"_id": "5e4317871c9d440000b1613f",
"name": "Test home 1",
"latitude": 5.97,
"longitude": 62.54,
"city": "Los Angeles",
"state": "California",
"country": "United States",
"description": "This is a test description",
"occupancy": 4,
"bedrooms": 2,
"baths": 1,
"date": "2020-02-11T21:20:28.969Z"
}
]
How would I populate the amenities attribute on mongoDB? Do I need to add a line like this into the document on mongoDB?
amenities: { wifi: true, kitchen: true, breakfast: true, etc... }
Related
when creating a product in Shopify via the REST API, adds a default option and variant like below
"options": [
{
"id": 9651869188247,
"product_id": 7644173172887,
"name": "Title",
"position": 1,
"values": [
"Default Title"
]
}
]
Variants:
{
"variants": [
{
"id": 42211487744151,
"product_id": 7644173172887,
"title": "Default Title",
"price": "1.00",
"sku": "",
"position": 1,
"inventory_policy": "deny",
"compare_at_price": null,
"fulfillment_service": "manual",
"inventory_management": "shopify",
"option1": "Default Title",
"option2": null,
"option3": null,
"created_at": "2022-06-17T17:18:24+05:30",
"updated_at": "2022-06-17T17:18:24+05:30",
"taxable": true,
"barcode": null,
"grams": 0,
"image_id": null,
"weight": 0.0,
"weight_unit": "kg",
"inventory_item_id": 44310083534999,
"inventory_quantity": 0,
"old_inventory_quantity": 0,
"requires_shipping": true,
"admin_graphql_api_id": "gid://shopify/ProductVariant/42211487744151"
}
]
}
I want to update the existing Option and Variants of a product to show "Color" & "Size" as options and variants of them. For that I tried the Shopify Rest API but that still is raising the below error
request model:
{
"variant": {
"product_id": 7644173172887,
"option1": "red",
"option2": "small",
"price": "1.0",
"title": "S"
}
}
response :
{
"errors": {
"base": [
"Option values provided for 1 unknown option(s)"
]
}
}
You are not specifing what endpoint you're using but I can see that you're specifing the Product Id and that should not be the case. If you need to add a new variant this is the request you should do
POST https://yourstore.myshopify.com/admin/api/2022-04/products/7644173172887/variants.json
{"variant":{"option1":"Red", "option2" :"Small", "title": "Red", "price":"1.00"}}
You will also need to update the current "Default Title" variant (I suggest, if possible to create the product with a valid variant).
PUT https://yourstore.myshopify.com/admin/api/2022-04/variants/42211487744151.json
{"variant":{"id":42211487744151,"option1":"Red","option2" : "S", "price":"99.00", "title" : "Red"}}
I'm trying to do a POST to the Strapi API and can't seem to figure out how to attach a 'has and belongs to one' (one to one) relationship from the profile to the user.
I know the relationship works well because in the admin panel I can create the relationship without any problem
I've already tried the following body's:
{
"fullName":"Test Name",
"country": "Nigeria",
"phone": "09070933598",
"verified": true,
"users_permissions_user": {
"id": 22
}
}
I got this response
{
"id": 3,
"users_permissions_user": {},
"fullName": "Test Name",
"country": "Nigeria",
"verified": true,
"plan": null,
"earnings": 0,
"availableBalance": 0,
"planRegDate": null,
"planActive": false,
"planPaymentVerified": false,
"phone": "09070933598",
"published_at": "2021-10-19T08:43:04.412Z",
"created_at": "2021-10-19T08:43:04.428Z",
"updated_at": "2021-10-19T08:43:04.470Z",
"identification": null
}
I expect to at least have some info about the user with the id passed in the body. It isn't just linking them
You need to pass the id of one of the users already in your strapi database to "users_permissions_users".
You can get this from the user object.
{
"fullName":"Test Name",
"country": "Nigeria",
"phone": "09070933598",
"verified": true,
"users_permissions_user": user.id
}
I had to change one of the fields of my collection in mongoDB from an object to array of objects containing a lot of data. New documents get inserted without any problem, but when attempted to get old data, it never maps to the original DTO correctly and runs into errors.
subject is the field that was changed in Students collection.
I was wondering is there any way to update all the records so they all have the same data type, without losing any data.
The old version of Student:
{
"_id": "5fb2ae251373a76ae58945df",
"isActive": true,
"details": {
"picture": "http://placehold.it/32x32",
"age": 17,
"eyeColor": "green",
"name": "Vasquez Sparks",
"gender": "male",
"email": "vasquezsparks#orbalix.com",
"phone": "+1 (962) 512-3196",
"address": "619 Emerald Street, Nutrioso, Georgia, 6576"
},
"subject":
{
"id": 0,
"name": "math",
"module": {
"name": "Advanced",
"semester": "second"
}
}
}
This needs to be updated to the new version like this:
{
"_id": "5fb2ae251373a76ae58945df",
"isActive": true,
"details": {
"picture": "http://placehold.it/32x32",
"age": 17,
"eyeColor": "green",
"name": "Vasquez Sparks",
"gender": "male",
"email": "vasquezsparks#orbalix.com",
"phone": "+1 (962) 512-3196",
"address": "619 Emerald Street, Nutrioso, Georgia, 6576"
},
"subject": [
{
"id": 0,
"name": "math",
"module": {
"name": "Advanced",
"semester": "second"
}
},
{
"id": 1,
"name": "history",
"module": {
"name": "Basic",
"semester": "first"
}
},
{
"id": 2,
"name": "English",
"module": {
"name": "Basic",
"semester": "second"
}
}
]
}
I understand there might be a way to rename old collection, create new and insert data based on old one in to new one. I was wondering for some direct way.
The goal is to turn subject into an array of 1 if it is not already an array, otherwise leave it alone. This will do the trick:
update args are (predicate, actions, options).
db.foo.update(
// Match only those docs where subject is an object (i.e. not turned into array):
{$expr: {$eq:[{$type:"$subject"},"object"]}},
// Actions: set subject to be an array containing $subject. You MUST use the pipeline version
// of the update actions to correctly substitute $subject in the expression!
[ {$set: {subject: ["$subject"] }} ],
// Do this for ALL matches, not just first:
{multi:true});
You can run this converter over and over because it will ignore converted docs.
If the goal is to convert and add some new subjects, preserving the first one, then we can set up the additional subjects and concatenate them into one array as follows:
var mmm = [ {id:8, name:"CORN"}, {id:9, name:"DOG"} ];
rc = db.foo.update({$expr: {$eq:[{$type:"$subject"},"object"]}},
[ {$set: {subject: {$concatArrays: [["$subject"], mmm]} }} ],
{multi:true});
Below is my mongo db document named business
{
"_id": ObjectId("5be8e24a6600321ead321466"),
"business_id": "r89Re4FNgVWHgBfjCVZyVw",
"name": "Harlow",
"neighborhood": "Ville-Marie",
"address": "438 Place Jacques Cartier",
"city": "Montréal",
"state": "QC",
"postal_code": "H2Y 3B3",
"stars": 3.5,
"attributes": {
"Alcohol": "full_bar",
"BikeParking": "True",
"BusinessAcceptsCreditCards": "True",
"BusinessParking": "{'garage': False, 'street': False, 'validated': False, 'lot': False, 'valet': False}",
"Caters": "False",
"GoodForMeal": "{'dessert': False, 'latenight': False, 'lunch': False, 'dinner': False, 'breakfast': False, 'brunch': False}",
"RestaurantsDelivery": "False",
"RestaurantsGoodForGroups": "True",
},
"categories": "Nightlife, Bars, American (Traditional), Tapas/Small Plates, Poutineries, Supper Clubs, Restaurants, Tapas Bars",
}
Question:In the above collection named business i need to Find all restaurants which provides meal for lunch. (need to Check attributes-GoodForMeal-lunch)
it is nested array. please suggest me how can this be done with mongo db
I'm in the process of developing Route Tracking/Optimization software for my refuse collection company and would like some feedback on my current data structure/situation.
Here is a simplified version of my MongoDB structure:
Database: data
Collections:
“customers” - data collection containing all customer data.
[
{
"cust_id": "1001",
"name": "Customer 1",
"address": "123 Fake St",
"city": "Boston"
},
{
"cust_id": "1002",
"name": "Customer 2",
"address": "123 Real St",
"city": "Boston"
},
{
"cust_id": "1003",
"name": "Customer 3",
"address": "12 Elm St",
"city": "Boston"
},
{
"cust_id": "1004",
"name": "Customer 4",
"address": "16 Union St",
"city": "Boston"
},
{
"cust_id": "1005",
"name": "Customer 5",
"address": "13 Massachusetts Ave",
"city": "Boston"
}, { ... }, { ... }, ...
]
“trucks” - data collection containing all truck data.
[
{
"truckid": "21",
"type": "Refuse",
"year": "2011",
"make": "Mack",
"model": "TerraPro Cabover",
"body": "Mcneilus Rear Loader XC",
"capacity": "25 cubic yards"
},
{
"truckid": "22",
"type": "Refuse",
"year": "2009",
"make": "Mack",
"model": "TerraPro Cabover",
"body": "Mcneilus Rear Loader XC",
"capacity": "25 cubic yards"
},
{
"truckid": "12",
"type": "Dump",
"year": "2006",
"make": "Chevrolet",
"model": "C3500 HD",
"body": "Rugby Hydraulic Dump",
"capacity": "15 cubic yards"
}
]
“drivers” - data collection containing all driver data.
[
{
"driverid": "1234",
"name": "John Doe"
},
{
"driverid": "4321",
"name": "Jack Smith"
},
{
"driverid": "3421",
"name": "Don Johnson"
}
]
“route-lists” - data collection containing all predetermined route lists.
[
{
"route_name": "monday_1",
"day": "monday",
"truck": "21",
"stops": [
{
"cust_id": "1001"
},
{
"cust_id": "1010"
},
{
"cust_id": "1002"
}
]
},
{
"route_name": "friday_1",
"day": "friday",
"truck": "12",
"stops": [
{
"cust_id": "1003"
},
{
"cust_id": "1004"
},
{
"cust_id": "1012"
}
]
}
]
"routes" - data collections containing data for all active and completed routes.
[
{
"routeid": "1",
"route_name": "monday1",
"start_time": "04:31 AM",
"status": "active",
"stops": [
{
"customerid": "1001",
"status": "complete",
"start_time": "04:45 AM",
"finish_time": "04:48 AM",
"elapsed_time": "3"
},
{
"customerid": "1010",
"status": "complete",
"start_time": "04:50 AM",
"finish_time": "04:52 AM",
"elapsed_time": "2"
},
{
"customerid": "1002",
"status": "incomplete",
"start_time": "",
"finish_time": "",
"elapsed_time": ""
},
{
"customerid": "1005",
"status": "incomplete",
"start_time": "",
"finish_time": "",
"elapsed_time": ""
}
]
}
]
Here is the process thus far:
Each day drivers begin by Starting a New Route. Before starting a new route drivers must first input data:
driverid
date
truck
Once all data is entered correctly the Start a New Route will begin:
Create new object in collection “routes”
Query collection “route-lists” for “day” + “truck” match and return "stops"
Insert “route-lists” data into “routes” collection
As driver proceeds with his daily stops/tasks the “routes” collection will update accordingly.
On completion of all tasks the driver will then have the ability to Complete the Route Process by simply changing “status” field to “active” from “complete” in the "routes" collection.
That about sums it up. Any feedback, opinions, comments, links, optimization tactics are greatly appreciated.
Thanks in advance for your time.
You database schema looks like for me as 'classic' relational database schema. Mongodb good fit for data denormaliztion. I guess when you display routes you loading all related customers, driver, truck.
If you want make your system really fast you may embedd everything in route collection.
So i suggest following modifications of your schema:
customers - as-is
trucks - as-is
drivers - as-is
route-list:
Embedd data about customers inside stops instead of reference. Also embedd truck. In this case schema will be:
{
"route_name": "monday_1",
"day": "monday",
"truck": {
_id = 1,
// here will be all truck data
},
"stops": [{
"customer": {
_id = 1,
//here will be all customer data
}
}, {
"customer": {
_id = 2,
//here will be all customer data
}
}]
}
routes:
When driver starting new route copy route from route-list and in addition embedd driver information:
{
//copy all route-list data (just make new id for the current route and leave reference to routes-list. In this case you will able to sync route with route-list.)
"_id": "1",
route_list_id: 1,
"start_time": "04:31 AM",
"status": "active",
driver: {
//embedd all driver data here
},
"stops": [{
"customer": {
//all customer data
},
"status": "complete",
"start_time": "04:45 AM",
"finish_time": "04:48 AM",
"elapsed_time": "3"
}]
}
I guess you asking yourself what do if driver, customer or other denormalized data changed in main collection. Yeah, you need update all denormalized data within other collections. You will probably need update billions of documents (depends on your system size) and it's okay. You can do it async if it will take much time.
What benfits in above data structure?
Each document contains all data that you may need to display in your application. So, for instance, you no need load related customers, driver, truck when you need display routes.
You can make any difficult queries to your database. For example in your schema you can build query that will return all routes thats contains stops in stop of customer with name = "Bill" (you need load customer by name first, get id, and look by customer id in your current schema).
Probably you asking yourself that your data can be unsynchronized in some cases, but to solve this you just need build a few unit test to ensure that you update your denormolized data correctly.
Hope above will help you to see the world from not relational side, from document database point of view.