On 03/07/2013 05:08 PM, Natalie Wenz wrote:
Hi!I am working on updating some of our tables to use appropriate native data types; they were all defined as text when they were created years ago. What I am running into, though, is there are some records that have bad data in them, where they can't be successfully converted to int, or float, or boolean, for example. Is there a straightforward way to identify offending records? I've been able to identify some with things like "...not similar to '(0|1)'..." for the boolean fields, and "...not similar to '[0-9]{1,}'..." for int. Are regular expressions the best approach here or is there a better way? Thoughts?
My opinion, it would take more time to concoct regexes that cover all the corner cases than to write a script that walks the through the data , finds the problem data and flags them.
I've poked around on the internet and have found some people suggesting user-defined functions. I'd prefer to just use a query, since it's a one-time clean-up.
Again, most 'one time' things I have done turned out not to be:)
(I'm using postgres 9.2) Thanks! Natalie
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