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
theywere 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
successfullyconverted 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
similarto '[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
usea 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
>
--
Adrian Klaver
adrian.klaver@gmail.com