Postgresql – Create local table and foreign table from the same SQL

postgresql

I want to build a set of PostgreSQL databases that derive from a separate structure definition. The structure is defined as a set of .sql files that will be imported using docker-entrypoint-initdb.d during start.

One of the databases will have regular tables that are created e.g. like this:

CREATE TABLE data."origin" (
    origin_id serial PRIMARY KEY,
    name text UNIQUE
);

Another database needs to be connected to this one using foreign tables that should have the same structure, e.g.

CREATE FOREIGN TABLE data."origin" (
    origin_id serial,
    name text
)
    SERVER localdb
    OPTIONS (schema_name 'data', table_name 'origin');

So the question is, whether there is an elegant way to use the original .sql files from the first database to construct the second one as well.

The only way that we have in mind is to fiddle with sed or similar magic during the image build to add the FOREIGN and the SERVER … stuff in there, remove the PRIMARY KEY etc. This will most likely break sooner or later.

Best Answer

I think I'd try to get a list of tables from the .sql file (or directly from the server to which you applied the .sql file), then feed that list of names to IMPORT FOREIGN SCHEMA ... LIMIT TO (...). That seems less error prone than what you are envisioning.

Related Solutions

Postgresql – Postgres multiple joins slow query, how to store default child record

You write:

Each customer can have multiple sites, but only one should be displayed in this list.

Yet, your query retrieves all rows. That would be a point to optimize. But you also do not define which site is to be picked.

Either way, it does not matter much here. Your EXPLAIN shows only 5026 rows for the site scan (5018 for the customer scan). So hardly any customer actually has more than one site. Did you ANALYZE your tables before running EXPLAIN?

From the numbers I see in your EXPLAIN, indexes will give you nothing for this query. Sequential table scans will be the fastest possible way. Half a second is rather slow for 5000 rows, though. Maybe your database needs some general performance tuning?

Maybe the query itself is faster, but "half a second" includes network transfer? EXPLAIN ANALYZE would tell us more.

If this query is your bottleneck, I would suggest you implement a materialized view.

After you provided more information I find that my diagnosis pretty much holds.

The query itself needs 27 ms. Not much of a problem there. "Half a second" was the kind of misunderstanding I had suspected. The slow part is the network transfer (plus ssh encoding / decoding, possibly rendering). You should only retrieve 100 rows, that would solve most of it, even if it means to execute the whole query every time.

If you go the route with a materialized view like I proposed you could add a serial number without gaps to the table plus index on it - by adding a column row_number() OVER (<your sort citeria here>) AS mv_id.

Then you can query:

SELECT *
FROM   materialized_view
WHERE  mv_id >= 2700
AND    mv_id <  2800;

This will perform very fast. LIMIT / OFFSET cannot compete, that needs to compute the whole table before it can sort and pick 100 rows.

pgAdmin timing

When you execute a query from the query tool, the message pane shows something like:

Total query runtime: 62 ms.

And the status line shows the same time. I quote pgAdmin help about that:

The status line will show how long the last query took to complete. If a dataset was returned, not only the elapsed time for server execution is displayed, but also the time to retrieve the data from the server to the Data Output page.

If you want to see the time on the server you need to use SQL EXPLAIN ANALYZE or the built in Shift + F7keyboard shortcut or Query -> Explain analyze. Then, at the bottom of the explain output you get something like this:

Total runtime: 0.269 ms

Postgresql – What happens to the index of a primary key after a DROP CONSTRAINT

Disclaimer

This is experimental and only tested rudimentarily. Proceed at your own risk. I would not use it myself and just drop / recreate constraints with standard DDL commands. If you break entries in the catalog tables you could easily mess up your database.

For all I know, there are only two differences between a PRIMARY KEY and a UNIQUE constraint in the catalog tables (the index itself is identical):

pg_index.indisprimary:
For PRIMARY KEY constraint ... TRUE
For UNIQUE constraint ... FALSE

pg_constraint.contype:
PRIMARY KEY constraint ... 'p'
UNIQUE constraint ... 'u'

You could convert constraint and index in place, from PRIMARY KEY constraint to UNIQUE constraint, my_idx being the (optionally schema-qualified) index name:

UPDATE pg_index SET indisprimary = FALSE WHERE indexrelid = 'my_idx'::regclass
UPDATE pg_constraint SET contype = 'u' WHERE conindid = 'my_idx'::regclass;

Or upgrade from UNIQUE to PRIMARY KEY:

UPDATE pg_index SET indisprimary = TRUE WHERE indexrelid = 'my_idx'::regclass;
UPDATE pg_constraint SET contype = 'p' WHERE conindid = 'my_idx'::regclass;