Thanks Thomas :)

On Tue, Feb 15, 2011 at 11:16 AM, Thomas Weholt <thomas.weh...@gmail.com>wrote:

> FYI: release version 0.5.0 of DSE yesterday. Source is available at
> https://bitbucket.org/weholt/dse and pypi.
>
> Regards,
> Thomas Weholt
>
> On Tue, Feb 15, 2011 at 10:10 AM, Sithembewena Lloyd Dube
> <zebr...@gmail.com> wrote:
> > Hi Everyone,
> >
> > Coming back weeks later, to say thank you for your contributions. I got
> > quite sidetracked from this task, but I should report back on this soon.
> >
> > Thank you!
> >
> > On Wed, Jan 19, 2011 at 10:05 AM, Thomas Weholt <thomas.weh...@gmail.com
> >
> > wrote:
> >>
> >> Bulk inserts are the way the go if you can. When inserting a bunch of
> >> data, avoid using the django orm. Do it in plain SQL. The overhead of
> >> creating django orm model instances is way too expensive. Alltough it
> >> may not be bulk insert the sense Nick mentioned above I wrote DSE [
> >> http://pypi.python.org/pypi/dse/0.3.1 ] for that exact purpose, to
> >> insert or update a bunch of data using plain SQL, but it hasn`t been
> >> tested much so don`t use it in production. The thing it solves, can be
> >> done in simple SQL;
> >>
> >> Use cursor.executemany("<prepared insert statement>", <list of tuples
> >> with params>).
> >>
> >> DSE takes care of creating SQL-statements for insert and updates based
> >> on your models, handles any default values you might have defined in
> >> your model, caches lists of params and executes cursor.executemany
> >> when the list of cached items reaches a specified limit. My experience
> >> is that the performance gain of this solution or a similar one is
> >> huge. Using cursor.executemany might be what Nick meant by bulk
> >> insert, but I think different DB backends handles it differently. I
> >> don`t know. Anyway, I've inserted many thousands of records using DSE
> >> and it takes a fraction of the time when compared to doing it with the
> >> orm.
> >>
> >>
> >> NB! DSE is a proof-of-concept project more than anything else. It
> >> needs a good re-write, extensive testing and docs, but it might be
> >> helpful.
> >>
> >> Thomas
> >>
> >>
> >>
> >>
> >>
> >> On Wed, Jan 19, 2011 at 2:35 AM, Nick Arnett <nick.arn...@gmail.com>
> >> wrote:
> >> >
> >> >
> >> > On Tue, Jan 18, 2011 at 12:04 PM, Sithembewena Lloyd Dube
> >> > <zebr...@gmail.com> wrote:
> >> >>
> >> >> Hi all,
> >> >>
> >> >> I am building a search app. that will query an API. The app. will
> also
> >> >> store search terms in a very simple table structure.
> >> >>
> >> >> Big question: if the app. eventually hit 10 million searches and I
> was
> >> >> storing every single search term, would the table hold or would I run
> >> >> into
> >> >> issues?
> >> >
> >> > As someone else said, 10 million records is no big deal for MySQL, in
> >> > principle.
> >> > However, you probably would do better to avoid all the overhead of a
> >> > database transaction for storing each of these.  I'm going to assume
> >> > that
> >> > there will be duplicates, especially if you normalize the queries.  It
> >> > would
> >> > make a lot more sense to log the queries into a text file, which has
> >> > extremely low overhead.  Then you'd periodically process the log
> files,
> >> > normalizing and eliminating duplicates, producing a bulk insert to
> load
> >> > into
> >> > the database.  Bulk inserts will be FAR more efficient than using
> >> > Django.
> >> > Nick
> >> >
> >> > --
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> >> >
> >>
> >>
> >>
> >> --
> >> Mvh/Best regards,
> >> Thomas Weholt
> >> http://www.weholt.org
> >>
> >> --
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> >>
> >
> >
> >
> > --
> > Regards,
> > Sithembewena Lloyd Dube
> >
> > --
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> >
>
>
>
> --
> Mvh/Best regards,
> Thomas Weholt
> http://www.weholt.org
>
> --
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>


-- 
Regards,
Sithembewena Lloyd Dube

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