What's a better counting algorithm for Azure Table Storage log data?

I'm using Windows Azure and venturing into Azure Table Storage for the first time in order to make my application scalable to high density traffic loads. My goal is simple, log every incoming request against a set of parameters and for reporting count or sum the data from the log. In this I have come up with 2 options and I'd like to know what more experienced people think is the better option.

Option 1: Use Boolean Values and Count the "True" rows

Because each row is written once and never updated, store each count parameter as a bool and in the summation thread, pull the rows in a query and perform a count against each set of true values to get the totals for each parameter. This would save space if there are a lot of parameters because I imagine Azure Tables store bool as a single bit value.

Option 2: Use Int Values and Sum the rows

Each row is written as above, but instead each parameter column is added as a value of 0 or 1. Summation would occur by querying all of开发者_如何学Go the rows and using a Sum operation for each column. This would be quicker because Summation could happen in a single query, but am I losing something in storing 32 bit integers for a Boolean value?

I think at this point for query speed, Option 2 is best, but I want to ask out loud to get opinions on the storage and retrieval aspect because I don't know Azure Tables that well (and I'm hoping this helps other people down the road).

Table storage doesn't do aggregation server-side, so for both options, you'd end up pulling all the rows (with all their properties) locally and counting/summing. That makes them both equally terrible for performance. :-)

I think you're better off keeping a running total, instead of re-summing everything everytime. We talked about a few patterns for that on Cloud Cover Episode 43: http://channel9.msdn.com/Shows/Cloud+Cover/Cloud-Cover-Episode-43-Scalable-Counters-with-Windows-Azure