Question

Is it possible to transform the returned data from a Find query in MongoDB?

As an example, I have a first and last field to store a user’s first and last name. In certain queries, I wish to return the first name and last initial only (e.g. ‘Joe Smith’ returned as ‘Joe S’). In MySQL a SUBSTRING() function could be used on the field in the SELECT statement.

Are there data transformations or string functions in Mongo like there are in SQL? If so can you please provide an example of usage. If not, is there a proposed method of transforming the data aside from looping through the returned object?

Answer 1

It is possible to do just about anything server-side with mongodb. The reason you will usually hear “no” is you sacrifice too much speed for it to make sense under ordinary circumstances. One of the main forces behind PyMongo, Mike Dirolf with 10gen, has a good blog post on using server-side javascript with pymongo here: http://dirolf.com/2010/04/05/stored-javascript-in-mongodb-and-pymongo.html. His example is for storing a javascript function to return the sum of two fields. But you could easily modify to return the first letter of your user name field. The gist would be something like:

db.system_js.first_letter = "function (x) { return x.charAt(0); }"

Understand first, though, that mongodb is made to be really good at retrieving your data, not really good at processing it. The recommendation (see for example 50 tips and tricks for mongodb developers from Kristina Chodorow by Oreilly) is to do what Andrew tersely alluded to doing above: make a first letter column and return that instead. Any processing can be more efficiently done in the application.

But if you feel that even querying for the fullname before returning fullname[0] from your ‘view’ is too much of a security risk, you don’t need to do everything the fastest possible way. I’d avoided map-reduce in mongodb for awhile because of all the public concerns about speed. Then I ran my first map reduce and twiddled my thumbs for .1 seconds as it processed 80,000 10k documents. I realize in the scheme of things, that’s tiny. But it illustrates that just because it’s bad for a massive website to take a performance hit on some server side processing, doesn’t mean it would matter to you. In my case, I imagine it would take me slightly longer to migrate to Hadoop than to just eat that .1 seconds every now and then. Good luck with your site