Interesting, thank you for the reply.

Two questions though...

Why should created_at come before question_id in the primary key?  In other words, why (user_id, created_at, question_id) instead of (user_id, question_id, created_at)?

Given this setup, all a user's answers (all 10k) will be stored in a single C* (internal, not cql) row?  I thought having "fat" or "big" rows was bad.  I worked with Cassandra 0.6 at my previous job and given the nature of our work, we would sometimes generate these "fat" rows... at which point Cassandra would basically shit the bed.

Thanks for the help.

On Wed, Jun 19, 2013 at 12:26 PM, David McNelis <> wrote:
I think you'd just be better served with just a little different primary key.

If your primary key was (user_id, created_at)  or (user_id, created_at, question_id), then you'd be able to run the above query without a problem.

This will mean that the entire pantheon of a specific user_id will be stored as a 'row' (in the old style C* vernacular), and then the information would be ordered by the 2nd piece of the primary key (or 2nd, then 3rd if you included question_id). 

You would certainly want to include any field that makes a record unique in the primary key.  Another thing to note is that if a field is part of the primary key you can not create a secondary index on that field.  You can work around that by storing the field twice, but you might want to rethink your structure if you find yourself doing that often.

On Wed, Jun 19, 2013 at 12:05 PM, Christopher J. Bottaro <> wrote:

We are considering using Cassandra and I want to make sure our use case fits Cassandra's strengths.  We have the table like:

user_id | question_id | result | created_at

Where our most common query will be something like:

SELECT * FROM answers WHERE user_id = 123 AND created_at > '01/01/2012' AND created_at < '01/01/2013'

Sometimes we will also limit by a question_id or a list of question_ids.

Secondary indexes will be created on user_id and question_id.  We expect the upper bound of number of answers for a given user to be around 10,000.

Now my understanding of how Cassandra will run the aforementioned query is that it will load all the answers for a given user into memory using the secondary index, then scan over that set filtering based on the dates.

Considering that that will be our most used query and it will happen very often, is this a bad use case for Cassandra?

Thanks for the help.