According to the MongoDB documentation, the _id field (if not specified) is automatically assigned a 12 byte ObjectId.
It says a unique index is created on this field on the creation of a collection, but what I want to know is how likely is it that two documents in different collections but still in the same database instance will have the same ID, if that can even happen?
I want my application to be able to retrieve a document using just the _id field without knowing which collection it is in, but if I cannot guarantee uniqueness based on the way MongoDB generates one, I may need to look for a different way of generating Id's.
Short Answer for your question is : Yes that's possible.
below post on similar topic helps you in understanding better:
Possibility of duplicate Mongo ObjectId's being generated in two different collections?
You are not required to use a BSON ObjectId for the id field. You could use a hash of a timestamp and some random number or a field with extremely high cardinality (an US SSN for example) in order to make it close to impossible that two objects in the world will share the same id
The _id_index requires the idto be unique per collection. Much like in an RDBMS, where two objects in two tables may very likely have the same primary key when it's an auto incremented integer.
You can not retrieve a document solely by it's _id. Any driver I am aware of requires you to explicitly name the collection.
My 2 cents: The only thing you could do is to manually iterate over the existing collections and query for the _id you are looking for. Which is... ...inefficient, to put it polite. I'd rather semantically distinguish the documents in question by an additional field than by the collection they belong to. And remember, mongoDB uses dynamic schemas, so there is no reason to separate documents which semantically belong together but have a different set of fields. I'd guess there is something seriously, dramatically wrong with you schema. Please elaborate so that we can help you with that.
Related
Objective is to find field values which exists in more than one collection in a single mongodb database. Assume, each collection has similar document model on basis of type or number of fields within.
Note . There is a unique id field in every collection whose value may or may not differ in fellow collections. Aim is to deduce all those collections which have these unique id values in common.
One solution is that if I follow brute force technique.
Solution.. traverse entire collection one by one and match every unique id values with each of those in other collections...
Are there any better solutions available?
There is no solution to this in MongoDB. Things are supposed to be embedded and there's usually no real correlation between collections. Even $lookup was introduced with some reluctance. I believe your solution is already the best there is.
We are currently using MongoDB to allow tenants in a SaaS application to define entities that they can use in the application. We do not know know how each tenant is going to define the fields for the entities that they are creating upfront. Each entity will have a collection dynamically created for it in a separate database that belongs to the tenant.
For example, One tenant might define a Customer as First Name, Last Name, Email. Another tenant might define Shipment as Shipment Ref, Ship Date, Owner etc... Each tenant will have many entities/collections in their tenant database.
We have one field (ID) which we will always force the user to include in each entity/collection. We will index this field upfront when creating the collection.
However, how do we handle the case where we want to allow the tenant to sort/search/order/query large collections/entities quickly when/if the dataset becomes too large?
That is, since we do not know upfront what fields the user will be sorting/filtering/ordering by, what is the indexing strategy to use in this case with Mongo?
First of all Mongo requires you to have _id for each document and it indexes it automatically. You should take advantage of this and not create yet another ID field in case you require your clients to have ID field. I'm not sure if that's the case in your application.
What you are asking for can't have a perfect solution or even the most optimal one, but I can suggest couple options:
Create single field index for each field in the document. Let Mongo query optimizer decide which index to use depending on query. Disadvantages - takes lots of space on disk and in memory. Makes inserts slower. Mongo can use only 1 index in condition clause, so it will not be able to use compound index. You can easily extract schema with a tool like this. I wrote this little prototype that analyzes and prints Mongo schema.
Let your application learn what indexes to create. Get slow queries from Mongo profiler (in Mongo log), analyze common parts (automatically?) and create indexes on most commonly used fields. That's not so easy to implement and efficiency might change with time if your client changes queries or data. Application will be slow in the start until it learns about itself :).
Would just like to emphasize in choosing your design that the ID and not _id field you mention is actually some unique entity identifier then you are better of putting this in _id.
The reason here is that the performance trade-off for using another unique index over the required _id is a considerable overhead. Thinking about this, since _id is required it is the first thing that MongoDB looks for when determining which index to use. Otherwise consider a compound _id field containing your entity information and some other useful uniqueness.
As for the user defined fields, which is kind of the essence of mongo documents, for my money I would make it part of the API to set up indexes as required. Depending on the type of searching that is happening you'll probably want compound indexes and generated queries that make sense to these.
Simply indexing every field will probably have limited use as only one index is going to be picked for the find anyhow, and the query optimizer is going to try all of them. As has been mentioned, a long option could be to set indexes according to the usage patterns. But it could take some work to do.
I want to have a friendlier facing ids (ie Youtube style: /posts/cxB6Ey6) than MongoDB's ObjectID.
I read that for scalability its best to leave _id as an ObjectID so I thought about two solutions:
1) add an indexed postid field to each document
2) create a mapping collection between _id and the postid
in both cases use something like https://github.com/dylang/shortid to generate the short id, and while generating make sure that the id is unique by querying the database.
(can this query-generate-insert be an atomic operation?)
will those solutions have a noticeable impact on performance ?
what's the best strategy for doing this ?
The normal method of doing this is to base64 encode a unique id but:
add an indexed postid field to each document
You definitely want to go for this method. Out of the two I would say this method is easily the most scalable and performant, for one it would only need one round trip to get a short URLs details where as the second option would take 2. Another consideration is the shortage of index overhead of maintaining an extra collection, this is a bit of a no-brainer.
I would not replace the _id field within the document either since the default ObjectId could still be useful in the foreseeable future.
So this limits it down to a separate field and index (unique key) for the short code of a URL.
The next thing is that you don't want an ID which forces you to query the database for uniqueness prior to every insert. This is where the ObjectId shines. The ObjectId is good at being made within the client application while being unique in the database without having to specifically query those assumptions.
Unique ids that do not require querying the database first are normally time based. In PHP ( http://php.net/manual/en/function.uniqid.php ) and in the MongoDB Drivers ( http://docs.mongodb.org/manual/core/object-id/ ) and even the plug-in you linked on github ( https://github.com/dylang/shortid/blob/master/lib/shortid.js#L50 ) they all use time as a basis for being unique.
Considering the plug-in you linked does not query the database to check its own IDs uniqueness I would say that this plug-in probably is quite performant and if you use it with the first solution you stated you should get a good benchmark out of it.
If you want to replace build-in ObjectID with custom user-friendly short id's then do it. You can either use build-in _id field or add a new unique-indexed field id for your custom ids. The benefit of using build-in ObjectID's is than they won't duplicate even if your database is extremely large. So, by replacing them with short id's you take the risk of id duplication.
Now about the performance. I think that the best solution is not to query DB for id's, because with properly adjusted ids length the probability of duplication is extremely small. So, the best way to handle ids duplication in this model is to check Mongo responses. If it responded with "duplicate key error" then you shall generate a new one.
And now about scaling. To scale your custom ids you can just add a few more symbols to it. "Duplicate key error" shall be a trigger for making that change. Normally there shall be no such errors. So, if they started to appear then its time to scale.
I don't think that generating ObjectId for _id field affect directly scalability or performance. Whereby this can be happen?
Main difference is that ObjectIds are created by MongoDB and you don't burden yourself with responsibility for this. Otherwise you must by yourself to determine optimal size of id and to ensure unique value for each _id field of documents stored in collection. It's required because _id used as primary key. This can be justified if you have not very big collection and custom value of identifier is need for you.
But you have such additional benefits with _id field that stores ObjectId values as opportunity to create object id's from time and use this fact to your advantage in queries. Also you can get timestamp of ObjectId’s creation with getTimestamp() method. And sorting on _id in this case is equivalent to sorting by creation time.
But if you're going to use ObjectId in URLs or HTML then for security concerns you can encrypt it. To prevent leakage of information and access to object's creation time. It may be security risk.
About your solutions:
1) I suppose this's very convenient and flexible solution. In this case you can specify any value in postId which doesn't depend directly on _id.
But little disadvantage of this solution is that you have to have extra field and to create extra index. While _id is automatically indexed.
2) I don't think this's good solution from the point of view of performance and philosophy of noSQL approach.
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.
How to make better use of objectId generate by MongoDB. I am not an expert user, but so far i ended up creating seperate id for my object (userid, postid) etc because the object id is too long and makes the url ugly if use as the main ID. I keep the _id intact as it help indexing etc. I was wondering about any better strategy so that one can use mongo objectId as more url friendly and easy to remember key. I read the key was a combination of date etc, so any of the part can be used unique within a collection for this purpose.
thanks,
bsr/
If you have an existing ID (say from an existing data set), then it's perfectly OK to override _id with the one you have.
...keeo the _id intact as it help indexing etc
MongoDB indexes the _id field by default. If you start putting integers in the _id field, they will be indexed like everything else.
So most RDBMs provide an "auto-increment" ID. This is nice for small datasets, but really poor in terms of scalability. If you're trying to insert data to 20 servers at once, how do you keep the "auto-increment" intact?
The normal answer is that you don't. Instead, you end up using things like GUIDs for those IDs. In the case of MongoDB, the ObjectId is already provided.
I was wondering about any better strategy so that one can use mongo objectId as more url friendly and easy to remember key
So the problem here is that "easy to remember" ID doesn't really mesh with "highly scalable database". When you have a billion documents, the IDs are not really "easy to remember".
So you have to make the trade-off here. If you have a table that can get really big, I suggest using the ObjectId. If you have a table that's relatively small and doesn't get updated often, (like a "lookup" table) then you can build your own auto-increment.
The choice is really up to you.
You can overwrite the _id yourself. There is no obligation for using the auto-generated object id. What is the problem with overriding _id inside your app according to your own needs?