MySQL Partitions with Partition limit

I don't see a lot of opportunity for improvement.

The index you added was probably a big help, because it's being used for the range matching on the WHERE clause (type => range, key => tran_date), and it's being used as a covering index (extra => using index), avoiding the need to seek into the table to fetch the row data.

But since you're using functions to construct the financial_year value for the group by, both the "using filesort" and "using temporary" can't be avoided. But, those aren't the real problem. The real problem is that you're evaluating MONTH(tran_date) 346,485 times and YEAR(tran_date) at least that many times... ~700,000 function calls in one second doesn't seem too bad.

Plan B: I am definitely not a fan of storing redundant data, and I'm dead-set against making the application responsible for maintaining it... but one option I might be tempted to try would be to create a dashboard_stats_by_financial_year table, and use after-insert/update/delete triggers on the transactions1 table to manage keeping those stats current.

That option has a cost, of course -- adding to the amount of time it takes to update/insert/delete a transaction... but, waiting > 1200 milliseconds for stats for your dashboard is a cost, too. So it may come down to whether you want to pay for it now or pay for it later.

I hate to state the obvious but I'd say test both scenarios and run your production queries against all 3 scenarios (scenario 1 being the current non partitioned one). The reason I state this is because I don't know what your code is querying. Do they actually have a benefit of being sorted in the base table by the identity column as opposed to the other column? For example, are your queries actually looking for the row ID often? If you're not sure, you might be surprised by getting some performance benefits. The general idea of using ID as the clustered key was for range scans, but in our case, we scan by customerID and Date, so it worked out perfectly for us, and perhaps you. Check out this article by Kim Tripp: http://www.sqlskills.com/blogs/kimberly/post/The-Clustered-Index-Debate-Continues.aspx

"What is often cited as the “reason” for IDENTITY PRIMARY KEY clustered index definitions is its monotonic nature, thus minimizing page splits. However, I argue that this is the only “reason” for defining the clustered index as such, and is the poorest reason in the list. Page Splits are managed by proper FILLFACTOR not increasing INSERTS. Range Scans are the most important “reason” when evaluating clustered index key definitions and IDENTITies do not solve this problem.Moreover, although clustering the IDENTITY surrogate key will minimize page splits and logical fragmentation due to its monotonic nature, it will not reduce EXTENT FRAGMENTATION, which can cause just as problematic query performance as page splitting. In short, the argument runs shallow "

Typically you want your clustered index to be as narrow as possible, unique, and non nullable as it get's carried into all other indexes. I have a table with roughly 10 billion rows and we partition off the datetime column, which has worked out great.