Thanks! Well, it is time to upgrade my PostgreSQL 7.4.2. :) Sophie -----Original Message----- From: "Igor Katrayev" <igor ( dot ) katrayev ( at ) nprb ( dot ) org> To: <pgsql-general ( at ) postgresql ( dot ) org> Subject: Re: Set Membership operator -- test group membership Date: Tue, 14 Jun 2005 11:27:30 -0800 -------------------------------------------------------------------------------- Sophie, The sql like this: select * from tbl1 where (a, b) in ((1, 20), (2, 30), (3, 50)); works very well in PostgreSQL 8, Sincerely, Igor Katrayev, Data Systems Manager North Pacific Research Board 1007 West Third Avenue, Suite 100 Anchorage, AK 99501 Phone: 907-644-6700 Fax: 907-644-6780 igor ( dot ) katrayev ( at ) nprb ( dot ) org -----Original Message----- From: pgsql-general-owner ( at ) postgresql ( dot ) org [mailto:pgsql-general-owner ( at ) postgresql ( dot ) org] On Behalf Of Sophie Yang Sent: Tuesday, June 14, 2005 11:09 AM To: pgsql-general ( at ) postgresql ( dot ) org Cc: pgsql-novice ( at ) postgresql ( dot ) org; pgsql-sql ( at ) postgresql ( dot ) org Subject: Set Membership operator -- test group membership Say I have a table tbl1 with two columns: tbl1(a integer, b integer, c integer) I want to select the rows in which a and b are members of a list of integer pairs. The SQL in my mind is something like: select * from tbl1 where (a, b) in ((1, 20), (2, 30), (3, 50)); I know the SQL above does not work in PostgreSQL. I wonder what is the proper way to use in PostgreSQL. I tried "select * from tbl1 where (a, b) in ('{{1, 20}, {2, 30}, {3, 50}}')", and it doesn't work either. Thanks! Sophie __________________________________ Yahoo! Mail Mobile Take Yahoo! Mail with you! Check email on your mobile phone. http://mobile.yahoo.com/learn/mail __________________________________________________ Do You Yahoo!? Tired of spam? Yahoo! Mail has the best spam protection around http://mail.yahoo.com ---------------------------(end of broadcast)--------------------------- TIP 9: the planner will ignore your desire to choose an index scan if your joining column's datatypes do not match
