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.
Related
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.
I have user collection which holds email_id and _id as unique. I want to store user data across various collections. I would like to use email_id as identifier in those collections. Because it is easy to query in the shell against those collections with email_id instead of complex ObjectId.
Is this right way? will it give any performance problem while creating indexes with big emailIds?
Also, don't consider this option, If you have plan to enable email_id change
option in future.
While relational databases encourage you to normalize your data and spread it over many tables, this approach is usually not the best for MongoDB. MongoDB doesn't support JOINs over multiple collections or even multiple documents from the same collection. So you should try to design your database documents in a way that each query can be statisfied by searching for a single document. That means it is usually a good idea to store all information about a user in one document.
An exception for this is when certain points of data of the user grows indefinitely (like the posts made by a user in a forum). First, MongoDB documents have a size limit and second, when the size of a document increases, the database needs to reallocate its hard drive space frequently. This slows down writes and leads to fragmentation in the database. In that case it's better to put each entity in a different collection.
The size of the fields covered by an index don't matter when you search for equality. When you have an unique index on email_id, it should be just as fast as searching by _id.
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.
Ok so the more and more I develop in Mongodb i start to wonder about the need for multiple collections vs having one large collection with indexes (since columns and fields can be different for each document unlike tabular data). If i am trying to develop in the most efficient way possible (meaning less code and reusable code) then can I use one collection for all documents and just index on a field. By having all documents in one collection with indexes then i can reuse all my form processing code and other code since it will all be inserting into the same collection.
For Example:
Lets say i am developing a contact manager and I have two types of contacts "individuals" and "businesses". My original thought was to create a collection called individuals and a second collection called businesses. But that was because im used to developing in sql where yes this would be appropriate since columns would be different for each table. The more i started to think about the flexibility of document dbs the more I started to think, "do I really need two collections for this?" If i just add a field to each document called "contact type" and index on that, do i really need two collections? Since the fields/columns in each document do not have to be the same for all (like in sql) then each document can have their own fields as long as i have a "document type" field and an index on that field.
So then i took that concept and started to think, if i only need one collection for "individuals" and "businesses" then do i even need a separate collection for "Users" or "Contact History" or any other data. In theory couldn't i build the entire solution in once collection and just have a field in each document that specifield the "type" and index on it such as "Users", "Individual Contact", "Business Contacts", "Contact History", etc, and if it is a document related to another document i can index on the "parent key/foreign" Id field...
This would allow me to code the front end dynamically since the form processing code would all be the same (inserting into the same collection). This would save a lot of coding but i want to make sure by using indexes and secondary indexes that the db would still run fast and not cause future problems as the collection grew. As you can imagine, if everything was in one collection there might be hundreds of thousands even millions of documents in this collection as the user base grows but it would have indexes and secondary indexes to optimize performance.
My question is: Is this a common method mongodb developers use? Why or why not? What are the downfalls, if any? If this is a commonly used method, please also give any positives to using this method. thank you.
This is a really big point in Mongo and the answer is a little bit more of an art than science. Having one collection full of gigantic documents is definitely an anti-pattern because it works against many of Mongo's features.
For instance, when retrieving documents, you can only retrieve a whole document out of a collection (not entirely true, but mostly). So if you have huge documents, you're retrieving huge documents each time. Also, having huge documents makes sharding less flexible since only the top level documents are indexed (and hence, sharded) in each collection. You can index values deep into a document, but the index value is associated with the top level document.
At the same time, going purely relational is also an anti-pattern because you've lost a lot of the referential integrity by going to Mongo in the first place. Also, all joins are done in application memory, so each one requires a full round-trip (slow).
So the answer is to do something in between. I'm thinking you'll probably want a collection for individuals and a different collection for businesses in this case. I say this because it seem like businesses have enough meta-data associated that it could bulk up a lot. (Also, I individual-business relationship seems like a many-to-many). However, an individual might have a Name object (with first and last properties). That would be a bad idea to make Name into a separate collection.
Some info from 10gen about schema design: http://www.mongodb.org/display/DOCS/Schema+Design
EDIT
Also, Mongo has limited support for transactions - in the form of atomic aggregates. When you insert an object into mongo, the entire object is either inserted or not inserted. So you're application domain requires consistency between certain objects, you probably want to keep them in the same document/collection.
For example, consider an application that requires that a User always has a Name object (containing FirstName, LastName, and MiddleInitial). If a User was somehow inserted with no corresponding Name, the data would be considered to be corrupted. In an RDBMS you would wrap a transaction around the operations to insert User and Name. In Mongo, we make sure Name is in the same document (aggregate) as User to achieve the same effect.
Your example is a little less clear, since I don't understand the business cases. One thing that does come to mind is that Mongo has excellent support for inheritance. It might make sense to put all users, individuals, and potentially businesses into the same collection (depending on how the application is modeled). If one individual has many contacts, you probably want individuals to have an array of IDs. If your application requires that you get a quick preview of contacts, you might consider duplicating part of an individual and storing an array of contact objects.
If you're used to RDBMS thinking, you probably think all your data always has to be consistent. The truth is, that's probably not entirely true. This concept of applying atomic aggregates to the domain has been preached heavily by the DDD community recently. When you look at your domain in depth, like your business users do, the consistency boundaries should become distinct.
MongoDB, and NoSQL in general, is about de-normalising data and about reducing joins. It goes against normal SQL thinking.
In your case, I don't see any reason why you would want to have separate collections because it introduces unnecessary complexity and performance overhead. Consider, for example, if you wanted to have a screen that displayed all contacts, in alphabetical order. If you have one single collection for contacts, then its really easy, but if you have two collections it becomes a more complicated proposition.
Where I would have multiple collections is if your application had multiple users storing contacts. I would then have one collection for each user. This makes it so easy to extract out that users contacts.
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?