How to insert a bulk of data with unique-violations very fast - Mailing list pgsql-performance

From Torsten Zühlsdorff
Subject How to insert a bulk of data with unique-violations very fast
Date
Msg-id hu37gm$qrl$1@news.eternal-september.org
Whole thread Raw
Responses Re: How to insert a bulk of data with unique-violations very fast  (Scott Marlowe <scott.marlowe@gmail.com>)
Re: How to insert a bulk of data with unique-violations very fast  (Cédric Villemain <cedric.villemain.debian@gmail.com>)
Re: How to insert a bulk of data with unique-violations very fast  (Andy Colson <andy@squeakycode.net>)
List pgsql-performance
Hello,

i have a set of unique data which about 150.000.000 rows. Regullary i
get a list of data, which contains multiple times of rows than the
already stored one. Often around 2.000.000.000 rows. Within this rows
are many duplicates and often the set of already stored data.
I want to store just every entry, which is not within the already stored
one. Also i do not want to store duplicates. Example:

Already stored set:
a,b,c

Given set:
a,b,a,c,d,a,c,d,b

Expected set after import:
a,b,c,d

I now looking for a faster way for the import. At the moment i import
the new data with copy into an table 'import'. then i remove the
duplicates and insert every row which is not already known. after that
import is truncated.

Is there a faster way? Should i just insert every row and ignore it, if
the unique constrain fails?

Here the simplified table-schema. in real life it's with partitions:
test=# \d urls
                          Tabelle »public.urls«
  Spalte |   Typ   |                       Attribute
--------+---------+-------------------------------------------------------
  url_id | integer | not null default nextval('urls_url_id_seq'::regclass)
  url    | text    | not null
Indexe:
     »urls_url« UNIQUE, btree (url)
     »urls_url_id« btree (url_id)

Thanks for every hint or advice! :)

Greetings from Germany,
Torsten
--
http://www.dddbl.de - ein Datenbank-Layer, der die Arbeit mit 8
verschiedenen Datenbanksystemen abstrahiert,
Queries von Applikationen trennt und automatisch die Query-Ergebnisse
auswerten kann.

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