Re: Which query is less expensive / faster?

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От Tzahi Fadida
Тема Re: Which query is less expensive / faster?
Дата
Msg-id 006401c51ad7$eada8f10$0b00a8c0@llord
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Ответ на Which query is less expensive / faster?  (Postgres Coder <postgrescoder@gmail.com>)
Ответы Re: Which query is less expensive / faster?  ("Jon Asher" <jon@vagabond-software.com>)
Список pgsql-general
I am not an expert to postgres internals but in General:
if you have a btree multicolumn index on the 4 fields
then it should take around logF(4M). lets guess the F
to be 5 so its around 10 ios +1 block read.
for the same thing for a hashtable its about the same or less.

if you have any subset of the fields indexed with a btree
it costs logF(4M) + all the blocks with those subset which is still
better than a sequential scan.

another possibility which requires careful analyze of the frequencies
is intersecting all the rows from the 4 separate indices and finding 1
that matches.

In any case, when in doubt run the EXPLAIN on your query.
see the documentation.

Regards,
    tzahi.

> -----Original Message-----
> From: pgsql-general-owner@postgresql.org
> [mailto:pgsql-general-owner@postgresql.org] On Behalf Of
> Postgres Coder
> Sent: Friday, February 25, 2005 1:46 AM
> To: pgsql-general@postgresql.org
> Subject: [GENERAL] Which query is less expensive / faster?
>
>
> Hi all,
>
> I have a couple different ways to get results out of my table
> structure, but I'm unsure which way is faster or less expensive to
> run:
>
> Option 1:  Query a table of 4 million rows, on 4 indexed
> columns.  It will return 1 row:
>
> SELECT field1, field2, field3, field4
> FROM tablea
> WHERE field1 = $1 AND field2 = $2 AND field3 = $3 AND field4 = $4
>
> Option 2: Query a table of 200,000 rows on 1 indexed column.
> It will return 800 rows:
>
> SELECT *
> FROM tableb
> WHERE field1 = $1
>
> Which one is going to return results the fastest, with the
> least expense to the database server?
>
> ---------------------------(end of
> broadcast)---------------------------
> TIP 8: explain analyze is your friend
>
>



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