Is there a standard DSL for data integrity validation?
Can you imagine a DSL that would do it? How will the rules look like? 
Several months ago I worked on such  problem - in the end it turned out to be harder than it seemed first.

The first step was obvious - all
rows were parsed and placed to the
special data stuctures so I could
work with them; the ones with
missing fields were thrown out. 
Every row had its current "strategy"
property, and a list of possible
strategies (Default action, Ignore,
Force, Overwrite etc.)  
At first all rows had their "strategy"
property set to "Default". 
Row processor checked that operation was
possible, creating list of errors
and warnings. 
After processing
and analyzing results every row that
caused problems was given a list of
alternate strategies the user could
choose; 

So, if there were any problems, user could change the row strategy (or just simply use "Ignore") and go back to step 4.
So, I'm curious at what step would such a DSL work?
I am faced with CSV files which come from clients and which can contain hundreds of thousands of rows. Is there a DSL (or wildly popular library in Java or Python) which can efficiently run calculations on this information, applying various rules to issue warnings and errors (user-configurable, of course)?