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 + F7
keyboard shortcut or Query -> Explain analyze
. Then, at the bottom of the explain output you get something like this:
Total runtime: 0.269 ms
If the results are not meant to be used in a subquery but by code, you may use a REFCURSOR
in a transaction.
Example:
CREATE FUNCTION example_cursor() RETURNS refcursor AS $$
DECLARE
c refcursor;
BEGIN
c:='mycursorname';
OPEN c FOR select * from generate_series(1,100000);
return c;
end;
$$ language plpgsql;
Usage for the caller:
BEGIN;
SELECT example_cursor();
[output: mycursor]
FETCH 10 FROM mycursor;
Output:
generate_series
-----------------
1
2
3
4
5
6
7
8
9
10
CLOSE mycursor;
END;
When not interested in piecemeal retrieval, FETCH ALL FROM cursorname
may also be used to stream all results to the caller in one step.
Best Answer
First off, you should take a look at Erwin Brandstetter's answer to a similar question: https://stackoverflow.com/a/23957098/835781
If the return type you want is mimicked by the structure of an existing table, you could use that existing table's regclass to define the type of the results. That method seems to be a bit overkill for your use case, if I'm understanding it correctly.
My suggestion would be to just create two functions. If you need to keep the same name, I would suggest you overload the function definition:
This results in you still having to create two function definitions. If you're going to create two separate functions, you should probably just use different names for each. If your application code is expecting the two different result sets depending on the flag provided, why not interpret that flag in your application code and use that to determine which function to call?
If you're dead-set on returning two different data structures depending on the value of a variable, you can't use the schema of an existing table to define the result type, and you're ok with the processing overhead, then you could create an array or json return type. This gives your function the flexibility to build out the result in whatever format you choose, but requires additional processing and logic handling to interpret. At the end of the day, it's usually just easier to create different functions for the different result types.