From: | "Tomi N/A" <hefest(at)gmail(dot)com> |
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To: | pgsql-general(at)postgresql(dot)org |
Subject: | Re: [Fwd: [PORTS] M$ SQL server DTS package equivalent in Postgres] |
Date: | 2007-01-26 15:14:22 |
Message-ID: | d487eb8e0701260714s47e9e4e2t190ae653268a898@mail.gmail.com |
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Lists: | pgsql-general |
> Besides being easy to schedule and very flexible, manipulating data
> with queries is extremely powerful and fairly easy to maintain
> assuming you know a little SQL -- thanks to postgresql's huge array of
> built in string manipulation functions. Your skills learned here will
> pay off using the database as well for other things.
>
> Not only that, but this approach will be fast since it is declarative
> and handles entire tables at once as opposed to DTS-ish solutions
> which tend to do processing record by record. Not to mention they are
> overcomplicated and tend to suck. (DTS does have the ability to read
> from any ODBC source which is nice...but that does not apply here).
Different strokes for different folks, it seems.
I'd argue that COPY followed by a barrage of plpgsql statements can't
be used for anything but the most trivial data migration cases (where
it's invaluable) where you have line-organized data input for a
hand-full of tables at most.
In my experience (which is probably very different from anyone
else's), most real world situations include data from a number of very
different sources, ranging from the simplest (.csv and, arguably,
.xml) to the relatively complex (a couple of proprietary databases,
lots of tables, on-the fly row merging, splitting or generating
primary keys, date format problems and general pseudo-structured,
messed up information).
Once you've got your data in your target database (say, pgsql), using
SQL to manipulate the data makes sense, but it is only the _final_
step of an average, real world data transformation.
Cheers,
t.n.a.
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