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From: Sonnenberg-Carstens, Stefan <ssonnenberg@ophardt.com>
To: Mark Teper <mark.teper@gmail.com>
To: pgsql-sql@lists.postgresql.org <pgsql-sql@lists.postgresql.org>
Subject: AW: plpython transforms vs. arrays
Date: Mon, 6 May 2019 09:34:08 +0000
Message-ID: <18e2584b905d47409a46b385a9b91157@OPHT402P.ophardt.com> (raw)
In-Reply-To: <CAMwSyGq7rke2+32j9ZUOxx+vEa-1m3QBOXckpOi0Ry8JxSVxPg@mail.gmail.com>
References: <CAMwSyGq7rke2+32j9ZUOxx+vEa-1m3QBOXckpOi0Ry8JxSVxPg@mail.gmail.com>

Understood, a great example what is possible if the toolset is open ;-)

Mit freundlichen Grüßen
Stefan Sonnenberg-Carstens

Teamleiter Softwareentwicklung WECO / DevOps Engineer
B.Sc. Wirtschaftsinformatik

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Von: Mark Teper [mailto:mark.teper@gmail.com]
Gesendet: Montag, 6. Mai 2019 11:33
An: Sonnenberg-Carstens, Stefan; pgsql-sql@lists.postgresql.org
Betreff: Re: plpython transforms vs. arrays

Hi Stefan,

>  is the Python code running inside the PostgreSQL instance?

Yes, it is using the PL Python language so it runs in the PostgreSQL instance.  With some help from Tom, I've been able to make the change needed to allow this transform.

I need to do some more testing, but my preliminary results for the arrays I'm interested in show transforming Postgres to Numpy is about 5x faster and transforming Numpy back to Postgres about 2x faster.

Regards,
Mark


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