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
I would suggest that you either want a single "couple" table instead of two, if the properties of each coupling are sufficiently similar, or a couple table that the two existing types of couple "inherit" from, like so:
RC Couple Egg
---------- --------------------------- ----------------
C ID (FK) -----> C ID (PK) <----- C ID (FK)
(rc props) | (generic couple properties) (egg properties)
|
BC |
---------- |
C ID (FK) --'
(BC props)
You could still have breeding and racing details for any could in this arrangement (which might actually be fine, of course) but each egg can only be associated with one couple. You won't have problems with overlapping ID ranges as there is only one range of IDs for couples when modeled this way, and all other tables with data relating to couples only have the one FK linking to the could record.
Best Answer
I believe that the primary key constraint enforces the not null constraint. You can look at the following Fiddle
I'm not sure what it is that you want to achieve. Should the following be valid:
? If not (i.e. only one allowed null varant per product), you can use a generated column and add the constraint there:
You would, of course, need to apply that rule in any dependent tables. From a normalisation point of view, you may want to treat products and variant of products differently.
Other things that come to mind is to use a default value such as:
Edit: Another option is to change the primary key to a unique constraint, see Fiddle: