MongoDb - Modeling storage of users & post in a webapp - mongodb

I'm quite new to nosql world.
If I have a very simple webapp with users authenticating & publishing posts, what's the mongodb(nosql) way to store users & posts on the nosql db?
Do I have (like in relationnal databases) to store users & posts each one in his own collection? Or store them in the same collection, on different documents? Or, finally with a redondant user infos (credentials) on each post he has published?

A way you could do it is to use two collection, a posts collection and a authors collection. They could look like the following:
Posts
{
title: "Post title",
body: "Content of the post",
author: "author_id",
date: "...",
comments: [
{
name: "name of the commenter",
email: "...",
comment: "..."
}],
tags: [
"tag1", "tag2, "tag3
]
}
Authors
{
"_id": "author_id",
"password": "..."
}
Of course, you can put it in a single collection, but #jcrade mentioned a reason why you would/should use two collections. Remember, that's NoSQL. You should design your database from an application point of you, that means ask yourself what data is consumed and how.

This post says it all:
https://www.mongodb.com/blog/post/6-rules-of-thumb-for-mongodb-schema-design-part-1
It really depends on your application, and how many posts you expect your users to have: if it's a one-to-few relationship, then probably using embedded documents (inside your users model) is the way to go. If it's one to many (up to a couple of thousands) then just embed an array of IDs in your users model. If it's more than that, then use the answer provided by Horizon_Net.
Read the post, and you get a pretty good idea of what you will have to do. Good luck!

When you are modeling nosql database you should think in 3 basic ideas
Desnormalization
Copy same data on multiple documents. in order to simplify/optimize query processing or to fit the user’s data into a particular data model
Aggregation
Embed data into documents for example (blog post and coments) in order to impact updates both in performance and consistency because mongo has one document consistency at time
Application level Joins
Create applicaciton level joins when its not good idea to agregate information (for example each post as idependent document will be really bad because we need to accces to the same resource)
to answer your question
Create two document one is blogPost with all the comments, and tags on it and user ui. Second User with all user information.

Related

MongoDB design decision for Documents

I'm building an API for a small social network and I came across a design decision that I have to make. I'm working with Express and MongoDB with mongoose to deal with the database.
I have two Documents: Users and Posts. I want the Users to be able to mark Posts as their favorites. I came up with two different ways for the Implementation:
Option A: Saving the favorites in the User Document. It makes it easy to show all favorite posts of an user. But how would I query the users, that have favorited a specific Post?
UserSchema:
favorite_posts: [
{
type: mongoose.Schema.Types.ObjectId,
ref: "posts"
}
]
Option B: Saving the Users, that hit the favorite button in the Post Document. The benefit would be, that you can easily display all Users, that have favorited a Post. But how do I list all Posts that one specific User has marked as favorites.
PostSchema:
users_favorited: [
{
type: mongoose.Schema.Types.ObjectId,
ref: "users"
}
]
Can somebody explain me how to query such things? I'm not getting smarter from the documentation... :(
As already mentioned in the comments your best bet would be a join-table to make a n:m relation work. Mongoose does emulate the sql inner-join functionality through the populate() functionality in regular queries or the $lookup-step in an aggregation. So basically create a table called "likes" that only holds refs to the user and the post. Using the aggregation framework, you can then easily query for all likes of a user or all likes on a post by first using the $match operator, then $group by either the user or the post and $push to create an array of all likes of a user or vice versa and then join the needed data on it using the $lookup step.
However, you could, as you've decribed, put all the favorites in a array on either the user- or the post-documents, but unless you know for sure that these arrays won't grow large, I'd recommend against it, as mongoDb is not designed for this kind of usage and you'll very quickly run into performance problems. See http://www.askasya.com/post/largeembeddedarrays/ for more.
If you are gonna query a lot by userid, you can just add a userid column on the favorites document. This would save queries/joins/aggregations

How to avoid inconsistent embedded documents

Having a bit of trouble understanding when and why to use embedded documents in a mongo database.
Imagine we have three collections: users, rooms and bookings.
I have a few questions about a situation like this:
1) How would you update the embedded document? Would it be the responsibility of the application developer to find all instances of kevin as a embedded document and update it?
2) If the solution is to use document references, is that as heavy as a relational db join? Is this just a case of the example not being a good fit for Mongo?
As always let me know if I'm being a complete idiot.
Imho, you overdid it. Given the question from you use cases are
For a given reservation, what room is booked by which user?
For a given user, what are his or her details?
How many beds does a given room provide?
I would go with the following model for rooms
{
_id: 1001,
beds: 2
}
for users
{
_id: new ObjectId(),
username: "Kevin",
mobile:"12345678"
}
and for reservations
{
_id: new ObjectId(),
date: new ISODate(),
user: "Kevin",
room: 1001
}
Now in a reservation overview, you can have all relevant information ("who", "when" and "which") by simply querying reservations, without any overhead to answer the first question from you use cases. In a reservation details view, admittedly you would have to do two queries, but they are lightning fast with proper indexing and depending on your technology can be done asynchronously, too. Note that I saved an index by using the room number as id. How to answer the remaining questions should be obvious.
So as per your original question: embedding is not necessary here, imho.

Mongodb Storing Friends Relationship

I am using MongoDb for one of the mobile app that we are developing. It has a feature of sync contacts.
I wanted to know the ideal way of storing the relationships(friends relationship and not RDBMS kind of relationship) in mongodb. I want to know the architecture for the same.
I have thought of the following user collection structure:
{
_id: ObjectID(abc),
name: "abc",
contacts: ["def", "ghi"]
}
In the above collection I am considering "def" and "ghi" as object ids of friends of user abc. Is this the correct way of doing it or can someone suggest me a better and right way that they might have implemented?
All I am concerned about is I should not get stuck or hit the performance when retrieving data specific the user's friends in future.
Consider If I want to get all the activities from collection Activities done by my friends.
I think you could use advantage of noSql structure and save/serve some more info about friend
{
_id: ObjectID(abc),
name: "abc",
contacts: [{id:"def" name:"John"}, {id:"ghi", name:"Sari"} ]
}
To display basic list you will need just one get query, and then having name (or other important related details) - check for activities.
The extra overhead with this structure is a need to update name (and other details) every time when user updates it's name - but this is not a hammer - who changes its name frequently?

Many to many relationship on Mongodb based e-learning webapp?

I am relatively new to No-SQL databases. I am designing a data structure for an e-learning web app. There would be X quantity of courses and Y quantity of users.
Every user will be able to take any number of courses.
Every course will be compound of many sections (each section may be a video or a quiz).
I will need to keep track of every section a user takes, so I think the whole course should be part of the user set (for each user), like so:
{
_id: "ed",
name: "Eduardo Ibarra",
courses: [
{
name: "Node JS",
progress: "100%",
section: [
{name: "Introdiction", passed:"100%", field3:"x", field4:""},
{name: "Quiz 1", passed:"75%", questions:[...], field3:"x", field4:""},
]
},
{
name: "MongoDB",
progress: "65%",
...
}
]
}
Is this the best way to do it?
I would say that design your database depending upon your queries. One thing is for sure.. You will have to do some embedding.
If you are going to perform more queries on what a user is doing, then make user as the primary entity and embed the courses within it. You don't need to embed the entire course info. The info about a course is static. For ex: the data about Node JS course - i.e. the content, author of the course, exercise files etc - will not change. So you can keep the courses' info separately in another collection. But how much of the course a user has completed is dependent on the individual user. So you should only keep the id of the course (which is stored in the separate 'course' collection) and for each user you can store the information that is related to that (User, Course) pair embedded in the user collection itself.
Now the most important question - what to do if you have to perform queries which require 'join' of user and course collections? For this you can use javascript to first get the courses (and maybe store them in an array or list etc) and then fetch the user for each of those courses from the courses collection or vice-versa. There are a few drivers available online to help you accomplish this. One is UnityJDBC which is available here.
From my experience, I understand that knowing what you are going to query from MongoDB is very helpful in designing your database because the NoSQL nature of MongoDB implies that you have no correct way for designing. Every way is incorrect if it does not allow you in accomplishing your task. So clearly, knowing beforehand what you will do (i.e. what you will query) with the database is the only guide.

Mongodb real basic use case

I'm approaching the noSQL world.
I studied a little bit around the web (not the best way to study!) and I read the Mongodb documentation.
Around the web I wasn't able to find a real case example (only fancy flights on big architectures not well explained or too basic to be real world examples).
So I have still some huge holes in my understanding of a noSQL and Mongodb.
I try to summarise one of them, the worst one actually, here below:
Let's imagine the data structure for a post of a simple blog structure:
{
"_id": ObjectId(),
"title": "Title here",
"body": "text of the post here",
"date": ISODate("2010-09-24"),
"author": "author_of_the_post_name",
"comments": [
{
"author": "comment_author_name",
"text": "comment text",
"date": ISODate("date")
},
{
"author": "comment_author_name2",
"text": "comment text",
"date": ISODate("date")
},
...
]
}
So far so good.
All works fine if the author_of_the_post does not change his name (not considering profile picture and description).
The same for all comment_authors.
So if I want to consider this situation I have to use relationships:
"authorID": <author_of_the_post_id>,
for post's author and
"authorID": <comment_author_id>,
for comments authors.
But MongoDB does not allow joins when querying. So there will be a different query for each authorID.
So what happens if I have 100 comments on my blog post?
1 query for the post
1 query to retrieve authors informations
100 queries to retrieve comments' authors informations
**total of 102 queries!!!**
Am I right?
Where is the advantage of using a noSQL here?
In my understanding 102 queries VS 1 bigger query using joins.
Or am I missing something and there is a different way to model this situation?
Thanks for your contribution!
Have you seen this?
http://www.sarahmei.com/blog/2013/11/11/why-you-should-never-use-mongodb/
It sounds like what you are doing is NOT a good use case for NoSQL. Use relational database for basic data storage to back applications, use NoSQL for caching and the like.
NoSQL databases are used for storage of non-sensitive data for instance posts, comments..
You are able to retrieve all data with one query. Example: Don't care about outdated fields as author_name, profile_picture_url or whatever because it's just a post and in the future this post will not be visible as newer ones. But if you want to have updated fields you have two options:
First option is to use some kind of worker service. If some user change his username or profile picture you will give some kind of signal to your service to traverse all posts and comments and update all fields his new username.
Second option use authorId instead of author name, and instead of 2 query you will make N+2 queries to query for comment_author_profile. But use pagination, instead of querying for 100 comments take 10 and show "load more" button/link, so you will make 12 queries.
Hope this helps.