I'm looking for a better way to handle it. My documents I designed to store all comments and votes (like a confirmation thats stores picture and text information as well) using arrays inside a document. The issue I'm concerning is about the size limit of a document (16 Mb so far), If a document keeps a lot of comments and specially votes in internal arrays, very probably it will be broken reaching the size limit, on the other hand, keep this strategy I can ensure faster queries as well.
What do I have to do? Do like a relational DB and keep these kind of information and different collections and docs? It will decrease search speed, otherwise I'll keep it safe and unbroken.
It all depends on how you plan on using the data. If you get a huge number of comments on a single blog post would you really want to query for the post and get all the comments back?
No real life webpage that shows you a blog post actually does that. They show you the first few comments and then fetch more either as you scroll through those or when you click "show more". That's probably the best (hybrid) model. Store what you need when you first display a blog post in the blog post document but keep everything else that you can query for later in a separate collection where every comment references the post that it belongs to. Then you can get the additional comments with a single indexed read (probably index it on post_id and date posted?). You can also use the "bucketing" technique and store comments grouped by post and chunk of time so that you can fetch entire "next page of comments" document.
If you architect this correctly rather than reducing your search speed it will likely increase your search and reading speed for base documents and save you a lot of network bandwidth too.
So, I have been watching this video in order to learn MongoDB data modeling. In the one to many relationship, the speaker talks about three different kinds:
Embedded array / array keys: In a particular document you would have a field that would be an array that references other documents (for example, blog_posts attribute in the user document would store all the ids of the blog posts that the user has created)
Embedded tree: Rather than having an array with references to other things, we have documents in documents, completely embedded.
Normalized: Which you have two collections and references between each other.
So, what would be the difference between the embedded array keys and the normalized kind? Isn't the embedded array also doing references two another collection?
The difference is simple (and unfortunately a bit confusingly presented in that video).
Imagine modeling a blog post (Post) and comments (Comment).
Embedded array: the Post document contains an array of all of the IDs of all of the Comment documents. The Comment is stored in a separate document (and/or collection).
Tree: The Post document contains embedded Comments. They aren't stored in distinct documents or in their own collection. While this performs very well, the size limit of BSON documents being 16MB makes this potentially more difficult to work with.
Normalized: A Post document, and Comments are stored separately. The Comment document in this case however has a foreign-key like reference back to the Post. So, it might have a field called postId for example. It would reference the Post related to the Comment. This pattern is different from #1 as the Post document does not contain a list of Comments. So, while this option makes it so that the number of Comments is essentially unbounded/unlimited, it could make retrieval of comments more inefficient without specific indexes being built (like a postId, commentDate might be useful).
I'd like to code a web app where most of the sections are dependent on the user profile (for example different to-do lists per person etc) and I'd love to use MongoDB. I was thinking of creating about 10 embedabble documents for the main profile document and keep everything related to one user inside his own document.
I don't see a clear way of using foreign keys for mongodb, the only way would be to create a field to_do_id with the type of ObjectId for example, but they would be totally unrelated internally, just happen to have the same Ids I'd have to query for.
Is there a limit on the number of embedded document types inside a top level document that could degrade performance?
How do you guys solve the issue of having a central profile document that most of the documents have to relate to in presenting a view per person?
Do you use semi foreign keys inside MongoDb and have fields with ObjectId types that would have some other document's unique Id instead of embedding them?
I cannot feel what approach should be taken when. Thank you very much!
There is no special limit with respect to performance. The larger the document, though, the longer it takes to transmit over the wire. The whole document is always retrieved.
I do it with references. You can choose between simple manual references and the database DBRef as per this page: http://www.mongodb.org/display/DOCS/Database+References
The link above documents how to have references in a document in a semi-foreign key way. The DBRef might be good for what you are trying to do, but the simple manual reference is very efficient.
I am not sure a general rule of thumb exists for which reference approach is best. Since I use Java or Groovy mostly, I like the fact that I get a DBRef object returned. I can check for this datatype and use that to decide how to handle the reference in a generic way.
So I tend to use a simple manual reference for references to different documents in the same collection, and a DBRef for references across collections.
I hope that helps.
I'm slightly embarrassed to admit it, but I'm having trouble conceptualizing how to architect data in a non-relational world. Especially given that most document/KV stores have slightly different features.
I'd like to learn from a concrete example, but I haven't been able to find anyone discussing how you would architect, for example, a blog using CouchDB/Redis/MongoDB/Riak/etc.
There are a number of questions which I think are important:
Which bits of data should be denormalised (e.g. tags probably live with the document, but what about users)
How do you link between documents?
What's the best way to create aggregate views, especially ones which require sorting (such as a blog index)
First of all I think you would want to remove redis from the list as it is a key-value store instead of a document store. Riak is also a key-value store, but you it can be a document store with library like Ripple.
In brief, to model an application with document store is to figure out:
What data you would store in its own document and have another document relate to it. If that document is going to be used by many other documents, then it would make sense to model it in its own document. You also must consider about querying the documents. If you are going to query it often, it might be a good idea to store it in its own document as you would find it hard to query over embedded document.
For example, assuming you have multiple Blog instance, a Blog and Article should be in its own document eventhough an Article may be embedded inside Blog document.
Another example is User and Role. It makes make sense to have a separate document for these. In my case I often query over user and it would be easier if it is separated as its own document.
What data you would want to store (embed) inside another document. If that document only solely belongs to one document, then it 'might' be a good option to store it inside another document.
Comments sometimes would make more sense to be embedded inside another document
{ article : { comments : [{ content: 'yada yada', timestamp: '20/11/2010' }] } }
Another caveat you would want to consider is how big the size of the embedded document will be because in mongodb, the maximum size of embedded document is 5MB.
What data should be a plain Array. e.g:
Tags would make sense to be stored as an array. { article: { tags: ['news','bar'] } }
Or if you want to store multiple ids, i.e User with multiple roles { user: { role_ids: [1,2,3]}}
This is a brief overview about modelling with document store. Good luck.
Deciding which objects should be independent and which should be embedded as part of other objects is mostly a matter of balancing read/write performance/effort - If a child object is independent, updating it means changing only one document but when reading the parent object you have only ids and need additional queries to get the data. If the child object is embedded, all the data is right there when you read the parent document, but making a change requires finding all the documents that use that object.
Linking between documents isn't much different from SQL - you store an ID which is used to find the appropriate record. The key difference is that instead of filtering the child table to find records by parent id, you have a list of child ids in the parent document. For many-many relationships you would have a list of ids on both sides rather than a table in the middle.
Query capabilities vary a lot between platforms so there isn't a clear answer for how to approach this. However as a general rule you will usually be setting up views/indexes when the document is written rather than just storing the document and running ad-hoc queries later as you would with SQL.
Ryan Bates made a screencast a couple of weeks ago about mongoid and he uses the example of a blog application: http://railscasts.com/episodes/238-mongoid this might be a good place for you to get started.
I'm interested in document-oriented databases, and I'd like to play with MongoDB. So I started a fairly simple project (an issue tracker), but am having hard times thinking in a non-relational way.
My problems:
I have two objects that relate to each other (e.g. issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}} - here I have a user related to the issue). Should I create another document 'user' and reference it in 'issue' document by its id (like in relational databases), or should I leave all the user's data in the subdocument?
If I have objects (subdocuments) in a document, can I update them all in a single query?
I'm totally new to document-oriented databases, and right now I'm trying to develop sort of a CMS using node.js and mongodb so I'm facing the same problems as you.
By trial and error I found this rule of thumb: I make a collection for every entity that may be a "subject" for my queries, while embedding the rest inside other objects.
For example, comments in a blog entry can be embedded, because usually they're bound to the entry itself and I can't think about a useful query made globally on all comments. On the other side, tags attached to a post might deserve their own collection, because even if they're bound to the post, you might want to reason globally about all the tags (for example making a list of trending topics).
In my mind this is actually pretty simple. Embedded documents can only be accessed via their master document. If you can envision a need to query an object outside the context of the master document, then don't embed it. Use a ref.
For your example
issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}}
I would make issue and reporter each their own document, and reference the reporter in the issue. You could also reference a list of issues in reporter. This way you won't duplicate reporters in issues, you can query them each separately, you can query reporter by issue, and you can query issues by reporter. If you embed reporter in issue, you can only query the one way, reporter by issue.
If you embed documents, you can update them all in a single query, but you have to repeat the update in each master document. This is another good reason to use reference documents.
The beauty of mongodb and other "NoSQL" product is that there isn't any schema to design. I use MongoDB and I love it, not having to write SQL queries and awful JOIN queries! So to answer your two questions.
1 - If you create multiple documents, you'll need make two calls to the DB. Not saying it's a bad thing but if you can throw everything into one document, why not? I recall when I used to use MySQL, I would create a "blog" table and a "comments" table. Now, I append the comments to the record in the same collection (aka table) and keep building on it.
2 - Yes ...
The schema design in Document-oriented DBs can seems difficult at first, but building my startup with Symfony2 and MongoDB I've found that the 80% of the time is just like with a relational DB.
At first, think it like a normal db:
To start, just create your schema as you would with a relational Db:
Each Entity should have his own Collection, especially if you'll need to paginate the documents in it.
(in Mongo you can somewhat paginate nested document arrays, but the capabilities are limited)
Then just remove overly complicated normalization:
do I need a separate category table? (simply write the category in a column/property as a string or embedded doc)
Can I store comments count directly as an Int in the Author collection? (then update the count with an event, for example in Doctrine ODM)
Embedded documents:
Use embedded documents only for:
clearness (nested documents like: addressInfo, billingInfo in the User collection)
to store tags/categories ( eg: [ name: "Sport", parent: "Hobby", page: "/sport"
] )
to store simple multiple values (for eg. in User collection: list of specialties, list of personal websites)
Don't use them when:
the parent Document will grow too large
when you need to paginate them
when you feel the entity is important enough to deserve his own collection
Duplicate values across collection and precompute counts:
Duplicate some columns/attributes values from a Collection to another if you need to do a query with each values in the where conditions. (remember there aren't joins)
eg: In the Ticket collection put also the author name (not only the ID)
Also if you need a counter (number of tickets opened by user, by category, ecc), precompute them.
Embed references:
When you have a One-to-Many or Many-to-Many reference, use an embedded array with the list of the referenced document ids (see MongoDB DB Ref).
You'll need to use an Event again to remove an id if the referenced document get deleted.
(There is an extension for Doctrine ODM if you use it: Reference Integrity)
This kind of references are directly managed by Doctrine ODM: Reference Many
Its easy to fix errors:
If you find late that you have made a mistake in the schema design, its quite simply to fix it with few lines of Javascript to run directly in the Mongo console.
(stored procedures made easy: no need of complex migration scripts)
Waring: don't use Doctrine ODM Migrations, you'll regret that later.
Redid this answer since the original answer took the relation the wrong way round due to reading incorrectly.
issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}}
As to whether embedding some important information about the user (creator) of the ticket is a wise decision or not depends upon the system specifics.
Are you giving these users the ability to login and report issues they find? If so then it is likely you might want to factor that relation off to a user collection.
On the other hand, if that is not the case then you could easily get away with this schema. The one problem I see here is if you wish to contact the reporter and their job role has changed, that's somewhat awkward; however, that is a real world dilemma, not one for the database.
Since the subdocument represents a single one-to-one relation to a reporter you also should not suffer fragmentation problems mentioned in my original answer.
There is one glaring problem with this schema and that is duplication of changing repeating data (Normalised Form stuff).
Let's take an example. Imagine you hit the real world dilemma I spoke about earlier and a user called Nigel wants his role to reflect his new job position from now on. This means you have to update all rows where Nigel is the reporter and change his role to that new position. This can be a lengthy and resource consuming query for MongoDB.
To contradict myself again, if you were to only have maybe 100 tickets (aka something manageable) per user then the update operation would likely not be too bad and would, in fact, by manageable for the database quite easily; plus due to the lack of movement (hopefully) of the documents this would be a completely in place update.
So whether this should be embedded or not depends heavily upn your querying and documents etc, however, I would say this schema isn't a good idea; specifically due to the duplication of changing data across many root documents. Technically, yes, you could get away with it but I would not try.
I would instead split the two out.
If I have objects (subdocuments) in a document, can I update them all in a single query?
Just like the relation style in my original answer, yes and easily.
For example, let's update the role of Nigel to MD (as hinted earlier) and change the ticket status to completed:
db.tickets.update({'reporter.username':'Nigel'},{$set:{'reporter.role':'MD', status: 'completed'}})
So a single document schema does make CRUD easier in this case.
One thing to note, stemming from your English, you cannot use the positional operator to update all subdocuments under a root document. Instead it will update only the first found.
Again hopefully that makes sense and I haven't left anything out. HTH
Original Answer
here I have a user related to the issue). Should I create another document 'user' and reference it in 'issue' document by its id (like in relational databases), or should I leave all the user's data in the subdocument?
This is a considerable question and requires some background knowledge before continuing.
First thing to consider is the size of a issue:
issue = {code:"asdf-11", title:"asdf", reporter:{username:"qwer", role:"manager"}}
Is not very big, and since you no longer need the reporter information (that would be on the root document) it could be smaller, however, issues are never that simple. If you take a look at the MongoDB JIRA for example: https://jira.mongodb.org/browse/SERVER-9548 (as a random page that proves my point) the contents of a "ticket" can actually be quite considerable.
The only way you would gain a true benefit from embedding the tickets would be if you could store ALL user information in a single 16 MB block of contigious sotrage which is the maximum size of a BSON document (as imposed by the mongod currently).
I don't think you would be able to store all tickets under a single user.
Even if you was to shrink the ticket to, maybe, a code, title and a description you could still suffer from the "swiss cheese" problem caused by regular updates and changes to documents in MongoDB, as ever this: http://www.10gen.com/presentations/storage-engine-internals is a good reference for what I mean.
You would typically witness this problem as users add multiple tickets to their root user document. The tickets themselves will change as well but maybe not in a drastic or frequent manner.
You can, of course, remedy this problem a bit by using power of 2 sizes allocation: http://docs.mongodb.org/manual/reference/command/collMod/#usePowerOf2Sizes which will do exactly what it says on the tin.
Ok, hypothetically, if you were to only have code and title then yes, you could store the tickets as subdocuments in the root user without too many problems, however, this is something that comes down to specifics that the bounty assignee has not mentioned.
If I have objects (subdocuments) in a document, can I update them all in a single query?
Yes, quite easily. This is one thing that becomes easier with embedding. You could use a query like:
db.users.update({user_id:uid,'tickets.code':'asdf-1'}, {$set:{'tickets.$.title':'Oh NOES'}})
However, to note, you can only update ONE subdocument at a time using the positional operator. As such this means you cannot, in a single atomic operation, update all ticket dates on a single user to 5 days in the future.
As for adding a new ticket, that is quite simple:
db.users.update({user_id:uid},{$push:{tickets:{code:asdf-1,title:"Whoop"}}})
So yes, you can quite simply, depending on your queries, update the entire users data in a single call.
That was quite a long answer so hopefully I haven't missed anything out, hope it helps.
I like MongoDB, but I have to say that I will use it a lot more soberly in my next project.
Specifically, I have not had as much luck with the Embedded Document facility as people promise.
Embedded Document seems to be useful for Composition (see UML Composition), but not for aggregation. Leaf nodes are great, anything in the middle of your object graph should not be an embedded document. It will make searching and validating your data more of a struggle than you'd want.
One thing that is absolutely better in MongoDB is your many-to-X relationships. You can do a many-to-many with only two tables, and it's possible to represent a many-to-one relationship on either table. That is, you can either put 1 key in N rows, or N keys in 1 row, or both. Notably, queries to accomplish set operations (intersection, union, disjoint set, etc) are actually comprehensible by your coworkers. I have never been satisfied with these queries in SQL. I often have to settle for "two other people will understand this".
If you've ever had your data get really big, you know that inserts and updates can be constrained by how much the indexes cost. You need fewer indexes in MongoDB; an index on A-B-C can be used to query for A, A & B, or A & B & C (but not B, C, B & C or A & C). Plus the ability to invert a relationship lets you move some indexes to secondary tables. My data hasn't gotten big enough to try, but I'm hoping that will help.