i am working on a app inwhich anyone can purchase a product
when one place his order there is some extra charges added i.e minimum delivery charge, GST, and these values are gereral data of my app, i just want to read and calculate accordingly,
i want to store some data in the mongodb database
and i dont want to make multiple document of these data.
just want to read and update
data like =>
currentGST:18%,
minDeliveryCharge:100,
appVersion:"1.0.0",
appName:"MyAwesomeApp",
appSlogan:"Some Beautiful Slogan",
i handle it by creating a schema with these field
and put a single document in it
i read it by findOne() and limit(1) then document.currentGST
and i don't thing this is the standard way.
is there any standard way of doing this
by which i can simply store data without creating multiple documents
may be i am unable to describe my problem,sorry for that.
Any help appriciated, THANKS IN ADVANCE
How about creating a Schema for all the values required for look-up. The Schema will have two fields, the label which will be an String and the value which can also be a string.
You may also save timeStamps.
here is how it can be done...
const generalDataSchema= new mongoose.Schema({
label:{
type:String,
required:true
},
value:{
type:String,
required:true
} },{timeStamps:true});
Related
I am having a collection 'users' in MongoDB which contains multiple records without timestamps. I am using that collection with my node application and have set timestamps to true as shown:
const userSchema = new Schema({
...
},{
timestamps: true
});
I wanted to apply timestamps to the existing records and use it with my node application in future. If I make new fields 'createdAt' and 'updatedAt', will they work with my Mongoose schema? Or if there is any alternative way to achieve the task, please enlighten me as I am new to node and mongo in general.
first of all, I think this applies cannot affect the existing collections in the database, cause these fields are just a bunch of documents you inserting with existing/updating operations.
in MongoDB, everything is just a document and MongoDB does not care about data you store inside a collection, no validation here.so mongoose comes in for handling those validations and etc. if you change a schema in a collection it only effects to incoming requests from now on. but be careful if conflict fields happen, you will get an error for getting collections.
in short answer: MongoDB does not know when data stored or edited
but you can get timeStamp of creation in mongo ObjectId:
https://docs.mongodb.com/manual/reference/method/ObjectId.getTimestamp/index.html
I have three collections in MongoDB
achievements
students
student_achievements
achievements is a list of achievements a students can achieve in an academic year while
students collections hold data list of students in the school.
student_achievements holds documents where each documents contains studentId & achievementId.
I have an interface where i use select2 multiselect to allocate one or more achievements from achievements to students from students and save it to their collection student_achievements, right now to do this i populate select2 with available achievements from database. I have also made an arrangement where if a student is being allocated same achievement again the system throws an error.
what i am trying to achieve is if an achievement is allocated to student that shouldn't be available in the list or removed while fetching the list w.r.t student id,
what function in mongodb or its aggregate framework can i use to achieve this i.e to compare to collections and remove out the common.
Perhaps your data-structure could be made different to make the problem easier to solve. MongoDB is a NoSQL schemaless store, don't try to make it be like a relational database.
Perhaps we could do something like this:
var StudentSchmea = new Schema({
name: String,
achievements: [{ type: Schema.Types.ObjectId, ref: 'Achivement' }]
});
Then you can do something like this which will only add the value if it is unique to the achievements array:
db.student.update(
{ _id: 1 },
{ $addToSet: { achievements: <achivement id> } }
)
If you are using something like Mongoose you can also write your own middleware to remove orphaned docs:
AchivementSchema.post('remove', function(next) {
// Remove all references to achievements in Student schema
});
Also, if you need to verify that the achievement exists before adding it to the set, you can do a findOne query before updating/inserting to verify.
Even with the post remove hook in place, there are certain cases where you will end up with orphaned relationships potentially. The best thing to do for those situations is to have a regularly run cron task to to do cleanup when needed. These are some of the tradeoffs you encounter when using a NoSQL store.
I know there are no "joins" in MongoDB. I'm attempting to link a large number of documents to the 40,000+ locations in my locations collection.
My locations collection has custom (read: not under my control) identifiers for locations and their corresponding lat/lng coordinates.
var Locations = new Schema({
location_id: String,
loc: { //lng, lat: as per mongodb documents
type: [Number],
index: '2d'
}
});
There are several collections that have a field referencing this custom identifier to match latitude and longitude.
var MyCollection = new Schema({
location: String,
otherFields: Strings...
});
I'm a little lost on how to best go about this. A lot of posts suggest linking via Schema, but I've only seen that with an Schema.Types.ObjectId. This seems impractical for me because the data I'm importing only have the custom identifier.
Could I perhaps add another field into MyCollection and find the correct _id of the location to link to while I'm uploading data. If so, can someone point me in the right direction for accomplishing this.
Map reduce could be used somehow perhaps? I'm still a bit novice with Mongo.
Tried
I did try loading up the entirety of the location data into a JS object then checking that object against the return object from my other query, injecting the matching location data into my return object. This works but is unbearably slow.
First, just for the record: MongoDb will still generate an _id property for each object you store.
1. "[...], if the mongod receives a document to insert that does not contain an _id field, mongod will add the _id field that holds an ObjectId. [...]"
Source
You wrote that location_id is not under your control. And you want to use location_id because the other collections are using it also? So you don't want to break the standard in your project which is good.
As I see, you already have the location property in MyCollection and can store the location_id there.
As far as I know, you have to write your own linking methods now. You have to store the location_id in MyCollection and load the Location if you want to access if via MyCollection by
Locations.find({location_id: <the_location_id>})
But maybe your main problem is that you cannot find the Locations you are looking for in a reliable time?
I don't know your criteria for finding Locations for MyCollection is. If it is proximity of coordinates then you can reduce the amount of locations to check by filtering out the ones you really don't need to check. Then you don't have to check all the 40.000 Locations, but maybe just 100? In the following I assume it is the proximity.
Do you have lat, lon in both collections (Locations, MyCollection) ?
If so, you can define a query which gets locations around your MyCollection object (square). Then you will receive a smaller amount of Locations from MongoDb. Now you can apply your more complex check which checks if they really belong to your MyCollection-object.
something like this:
Locations.find({lat: {$gt: <x>-a, $lt: <x>+a}, lon: {$gt: <y>-b, $lt: <y>+b}}, function(locations){ ... });
I hope it helps.
I'm using mongoose with Node.js for an application. I have a Document class, which has a Review subdocument. I also have a User class.
I want the user to be able to see all the reviews they've done, while I also want the Document to be able to easily get all of its reviews. Searching through all the documents and all their reviews to find ones matching a user seems horribly ineffecient. So, how do I allow the Review to be owned by both a Document and a User?
If this is impossible, how else can I efficiently have two documents know about one subdocument.
If you don't want to deal with consistency issues I don't think there's any way except for normalization to assign two parents for a document. Your issue is a common one for social networks, when developers have to deal with friends, followers, etc. Usually the best solution depends on what queries you are gonna run, what data is volatile and what is not and how many children a document might have. Usually it turns out to be a balance between embedding and referencing. Here's what I would do if I were you:
Let's assume Documents usually have 0-5 Reviews. Which is a few, so we might consider embed Reviews into Documents. Also we would often need to display reviews every time a Document is queried, this is one more reason for embedding. Now we need a way to query all reviews by a User efficiently. Assume we don't run this query as often as the first one but still it is important. Let's also assume that when we query for User's Reviews we just want to display Review titles as links to Review page or even Document page as probably it's hard to read a review without seeing the actual Document. So the best way here would be to store { document_id, review_id, reviewTitle }. ReviewTitle should not be volatile in this case. So now when you have a User object, you can easily query for reviews. Using document_id you will filter out most documents and it will be super fast. Then you can get required Reviews either on the client side or by using MapReduce to turn Reviews into separate list of documents.
This example contains many assumption so it might not be exactly what you need by my goal was to show you the most important things to consider while designing your collections and the logic you should follow. So just to sum up, consider QUERIES, HOW VOLATILE SOME DATA IS and HOW MANY CHILDREN A DOCUMENT IS GONNA HAVE, and find a balance between embeding and referencing
Hope it helps!
This is an old question, but here is a solution that, I think, works well:
var mongoose = require('mongoose'),
Schema = mongoose.Schema;
var DocumentSchema = new Schema({
title: String,
...
});
mongoose.model('Document', DocumentSchema);
var UserSchema = new Schema({
name: String,
...
});
mongoose.model('User', UserSchema);
var ReviewSchema = new Schema({
created: {
type: Date,
default: Date.now
},
document: {
type: Schema.ObjectId,
ref: 'Document'
},
reviewer: {
type: Schema.ObjectId,
ref: 'User'
},
title: String,
body: String
});
Then, you could efficiently query the Reviews to get all reviews for a User, or for a Document.
Hope this helps someone.
I'm new to mongodb and nosql databases. I would really appreciate some input/help with my schema design so I don't shoot myself in the foot.
Data: I need to model Quotes. A Quote contains many Ttems. Each Item contains many Orders. Each Order is tied to a specific fiscal quarter. Ex. I have a Quote containing an Item which has Orders in Q3-14, Q4-14, Q1-15. Orders only go max 12 quarters (3 years) into the future. Specifically, I'm having trouble with modelling the Order-quarter binding. I'm trying to denormalize the data and embed Quote <- Items <- Orders for performance.
Attempts/Ideas:
Have an Order schema containing year and qNum fields. Embed an array of Orders in every Item. Could also create virtual qKey field for setting/getting via string like Q1-14
Create a hash that embeds a Orders into an Item using keys like Q1-14. This would be nice, but isn't supported natively in Mongoose.
Store the current (base) quarter in each Quote, and have each Item contain an array of Orders, but have them indexed by #quarters offset from the base quarter. I.e. if It's currently Q1-14, and an order comes in for Q4-14, store it in array position 2.
Am I totally off the marker? Any advice is appreciated as I struggle to use Mongo effectively. Thank you
Disclaimer: I've embarked on this simply as a challenge to myself. See the <rant> below for an explanation as to why I disagree with your approach.
First step to getting a solid grasp on No-SQL is throwing out terms like "denormalize" – they simply do not apply in a document based data store. Another important concept to understand is there are no JOINS in MongoDB, so you have to change the way you think about your data completely to adjust.
The best way to solve your problem with mongoose is to setup collections for Quotes and Items separately. Then we can set up references between these collections to "link" the documents together.
var mongoose = require('mongoose');
var Schema = mongoose.Schema;
var quoteSchema = new Schema({
items: [{ type: Schema.Types.ObjectId, ref: 'Item' }]
});
var itemSchema = new Schema({});
That handles your Quotes -> Items "relationship". To get the Orders setup, you could use an array of embedded documents like you've indicated, but if you ever decided to start querying/indexing Orders, you'd be up a certain creek without a paddle. Again, we can solve this with references:
var itemSchema = new Schema({
orders: [{ type: Schema.Types.ObjectId, ref: 'Order' }]
});
var orderSchema = new Schema({
quarter: String
});
Now you can use population to get what you need:
Item
.findById(id)
.populate({
path: 'orders',
match: { quarter: 'Q1-14' }
})
.exec(function (err, item) {
console.log(item.orders); // logs an array of orders from Q1-14
});
Trouble with references is that you are actually hitting the DB with a read instruction twice, once to find the parent document, and then once to populate its references.
You can read more about refs and population here: http://mongoosejs.com/docs/populate.html
<rant>
I could go on for hours why you should stick to an RDBMS for this kind of data. Especially when the defense for the choice is a lack of an ORM and Mongo being "all the rage." Engineers pick the best tech for the solution, not because a certain tech is trending. Its the difference between weekend hackery and creating Enterprise level products. Don't get me wrong, this is not to trash No-SQL – the largest codebase I maintain is built on NodeJS and MongoDB. However, I chose those technologies because they were the right technologies for my document based problem. If my data had been a relational ordering system like yours, I'd ditch Mongo in a heartbeat.
</rant>