Question

I’m logging different actions users make on our website. Each action can be of different type : a comment, a search query, a page view, a vote etc… Each of these types has its own schema and common infos. For instance :

comment : {"_id":(mongoId), "type":"comment", "date":4/7/2012, 
           "user":"Franck", "text":"This is a sample comment"}

search : {"_id":(mongoId), "type":"search", "date":4/6/2012, 
          "user":"Franck", "query":"mongodb"} etc...

Basically, in OOP or RDBMS, I would design an Action class / table and a set of inherited classes / tables (Comment, Search, Vote).

As MongoDb is schema less, I’m inclined to set up a unique collection (“Actions”) where I would store these objects instead of multiple collections (collection Actions + collection Comments with a link key to its parent Action etc…).

My question is : what about performance / response time if I try to search by specific columns ?

As I understand indexing best practices, if I want “every users searching for mongodb”, I would index columns “type” + “query”. But it will not concern the whole set of data, only those of type “search”.

Will MongoDb engine scan the whole table or merely focus on data having this specific schema ?

Answer 1

If you create sparse indexes mongo will ignore any rows that don’t have the key. Though there is the specific limitation of sparse indexes that they can only index one field.

However, if you are only going to query using common fields there’s absolutely no reason not to use a single collection.

I.e. if an index on user+type (or date+user+type) will satisfy all your querying needs – there’s no reason to create multiple collections

Tip: use date objects for dates, use object ids not names where appropriate.