Re: [PERFORM] DELETE with filter on ctid

2007-04-10 Thread Tom Lane
"Spiegelberg, Greg" <[EMAIL PROTECTED]> writes: > Below is, I believe, everything pertinent to this problem. First is the > table in question, second is the problematic and original query, and > final is the transaction that I have working today with the CTID > implementation. So the basic issue

Re: [PERFORM] DELETE with filter on ctid

2007-04-10 Thread Spiegelberg, Greg
ECTED] Sent: Monday, April 09, 2007 5:58 PM To: Spiegelberg, Greg Cc: pgsql-performance@postgresql.org Subject: Re: [PERFORM] DELETE with filter on ctid Spiegelberg, Greg wrote: > We have a query which generates a small set of rows (~1,000) which are > to be used in a DELETE on the same

Re: [PERFORM] DELETE with filter on ctid

2007-04-10 Thread Spiegelberg, Greg
nel=# DELETE FROM sid2.data_id_table AS dd WHERE dd.point_id=2 AND dd.dtype_id=3 AND dd.deleted AND NOT dd.persist; DELETE 0 Time: 0.960 ms cranel=# COMMIT; Time: 20.500 ms -Original Message- From: Tom Lane [mailto:[EMAIL PROTECTED] Sent: Monday, April 09, 2007 4:55 PM To: Spiegelb

Re: [PERFORM] DELETE with filter on ctid

2007-04-09 Thread Craig A. James
Spiegelberg, Greg wrote: We have a query which generates a small set of rows (~1,000) which are to be used in a DELETE on the same table. The problem we have is that we need to join on 5 different columns and it takes far too long. You may have encountered the same problem I did: You *must*

Re: [PERFORM] DELETE with filter on ctid

2007-04-09 Thread Tom Lane
"Spiegelberg, Greg" <[EMAIL PROTECTED]> writes: > We have a query which generates a small set of rows (~1,000) which are > to be used in a DELETE on the same table. The problem we have is that > we need to join on 5 different columns and it takes far too long. I > have a solution but I'm not sure

[PERFORM] DELETE with filter on ctid

2007-04-09 Thread Spiegelberg, Greg
We have a query which generates a small set of rows (~1,000) which are to be used in a DELETE on the same table. The problem we have is that we need to join on 5 different columns and it takes far too long. I have a solution but I'm not sure it's the right one. Instead of joining on 5 columns in