Given the following setup:
regress=> CREATE SCHEMA A;
CREATE SCHEMA
regress=> CREATE SCHEMA B;
CREATE SCHEMA
regress=> SET search_path = B, public;
SET
regress=> CREATE TABLE bar(email text);
CREATE TABLE
CREATE UNIQUE INDEX index_bar_on_email ON bar USING btree (email);
CREATE INDEX
I cannot reproduce the problem you report in PostgreSQL 9.2:
regress=> SET search_path = A, B;
SET
regress=> CREATE TABLE bar(email text);
CREATE TABLE
regress=> CREATE UNIQUE INDEX index_bar_on_email ON bar USING btree (email);
CREATE INDEX
However, rather than using the search_path
, it's safer to use explicit schema-qualification. For example, I'd re-write the above as:
regress=> RESET search_path;
RESET
regress=> SHOW search_path ;
search_path
----------------
"$user",public
(1 row)
CREATE TABLE B.bar(email text);
CREATE UNIQUE INDEX b.index_bar_on_email ON b.bar USING btree (email);
CREATE TABLE A.bar(email text);
CREATE UNIQUE INDEX index_bar_on_email ON A.bar USING btree (email);
The indexes are automatically created in the schema of their associated table; see:
regress=> \di B.
List of relations
Schema | Name | Type | Owner | Table
--------+--------------------+-------+-------+-------
b | index_bar_on_email | index | craig | bar
(1 row)
regress=> \di A.
List of relations
Schema | Name | Type | Owner | Table
--------+--------------------+-------+-------+-------
a | index_bar_on_email | index | craig | bar
(1 row)
Update based on question change:
Yes, what you've shown does look like a Rails adapter issue. It's checking to see whether the index exists in any schema. It should be checking to see whether the first table of the given name in the search_path
has the named index.
I would write the query differently. I'd leave off the join on pg_class
entirely, instead using a cast to regclass
to handle search_path
resolution for me. I'd use the resulting oid to search for the index. Compare original, then updated, below. Note that the updated query does require search_path
to be set first.
regress=> SELECT DISTINCT i.relname, d.indisunique, d.indkey, t.oid, am.amname
FROM pg_class t, pg_class i, pg_index d, pg_am am
WHERE i.relkind = 'i'
AND d.indexrelid = i.oid
AND d.indisprimary = 'f'
AND t.oid = d.indrelid
AND t.relname = 'bar'
AND i.relnamespace IN (SELECT oid FROM pg_namespace WHERE nspname IN ('b','a') )
AND i.relam = am.oid
ORDER BY i.relname
;
relname | indisunique | indkey | oid | amname
--------------------+-------------+--------+-------+--------
index_bar_on_email | t | 1 | 28585 | btree
index_bar_on_email | t | 1 | 28592 | btree
(2 rows)
regress=> SELECT DISTINCT i.relname, d.indisunique, d.indkey, 'bar'::regclass::oid, am.amname
FROM pg_class i, pg_index d, pg_am am
WHERE i.relkind = 'i'
AND d.indexrelid = i.oid
AND d.indisprimary = 'f'
AND 'bar'::regclass = d.indrelid
AND i.relam = am.oid
ORDER BY i.relname
;
relname | indisunique | indkey | regclass | amname
--------------------+-------------+--------+----------+--------
index_bar_on_email | t | 1 | 28585 | btree
(1 row)
Best Answer
have a look at liquibase - it's a great tool, and sounds like what you are looking for. You could use it to create SQL statements using the updateSQL command or apply changes directly to the DB.
for example:
will output the required changes to the
scripts.sql
file.It supports many db servers including Postgres, and you can model your schema in XML, JSON or any way you like.
See: XML changeset
It's open source and actively maintained.
We've been using it on multiple projects and dbs - highly recommended :)