I'm looking for some guidance on how to model some stat tracking over time, 
bucketed to some type of interval (15 min, hour, etc).

As an example, let's say I would like to track network traffic throughput and 
bucket it to 15 minute intervals.  In our old model, using thrift I would 
create a column family set to counter, and use a timestamp ticks for the column 
name for a "total" and "count" column.  And as data was sampled, we would 
increment count by one, and increment the total with the sampled value for that 
time bucket.  The column name would give us the datetime for the values, as 
well as provide me with a convenient row slice query to get a date range for 
any given statistic.

Key                | 1215  | 1230 | 1245
NIC1:Total   | 100    | 56      |  872
NIC1:Count | 15      | 15      | 15

Then given the total/count I can show an average over time.

In CQL it seems like I can't do new counter columns at runtime unless they are 
defined in the schema first or run an ALTER statement, which may not be the 
correct way to go.  So is there a better way to model this type of data with 
the new CQL world?  Nor do I know how to query that type of data, similar to 
the row slice by column name.

Thanks,
Bryce

Reply via email to