I have a script that loops over a set of records, performs some statistical calculations and updates the records. It’s a big cursor: get record, calculate statistics from embedded documents, set fields on record, save record. There’s <5k records that are being looped and each one embeds 90 history entries.
Question: would I get substantially better performance if I did this via javascript? The alternative being writing it in Ruby. My opinion (unfounded) is that since this can be done entirely in the database I will get better performance if send a chunk of js to Mongodb instead of adding Ruby in to the mix.
Related: is map/reduce appropriate for finding the median and mode of a set of values for many records?
The answer is really “it depends” – if the fields you need to do the calculations are very large, doing the calculation on the server side with JS might be a lot faster simply by cutting down on network traffic.
But, executing JS on the server side also holds a write lock, so depending on how complicated the calculations are, it might be more efficient to just do your calculations on the client side and then simply update the document.
Your best bet is to do a simple benchmark with ruby vs. server side JS. If you need to serve other database traffic at the same time, this should also be considered as well, because your lock % could be different in the two scenarios (you can monitor this with mongostat).
Also, keep in mind that using db.eval will not work with sharding, so avoid it if you are using a sharded environment or plan to in the future.