Postgres – Fetch Exact Value When All Conditions Are Met

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Here are the table structure and sample data.

CREATE TABLE public.product (
                id serial NOT NULL,
                opid int4 NULL,
                opvalue int4 NULL,
                info varchar NULL,
                CONSTRAINT product_pkey PRIMARY KEY (id)
            );

INSERT INTO product (id,opid,opvalue,info) VALUES 
            (1,1,1,'s1')
            ,(2,1,1,'s2')
            ,(3,2,1,'s2')
            ,(4,1,1,'s3')
            ,(6,3,2,'s3')
            ,(5,2,1,'s3')
            ;

Now I want query if info value satisfied all it's condition value then it will be returned.
Ex.If I pass opid=1 and opvalue=1 then only s1 should be returned not s2 because s2 have it's different condition. s1 should be returned when I pass (opid=1 and opvalue =1) and (opid=2 and opvalue =1)

Best Answer

I think this does what you want:

select *
from product p
where opid = 1 and opvalue = 1
and not exists (
  select *
  from product x
  where x.info = p.info
  and (x.opid != p.opid or x.opvalue != p.opvalue)
);

https://dbfiddle.uk/?rdbms=postgres_12&fiddle=1efcb7a125d52c27b2c386307d37da5b

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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

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You should be able to do something like this with a writable CTE:

WITH i AS (
   INSERT INTO host (hostname, hostrole) VALUES ('foobar', 'Virtual') RETURNING id
)
INSERT INTO interface (name, mac, host)
SELECT 'eth0', '00:50:56:9d:34:d4', id
FROM i

(untested, but it should be something like that)

Writable CTE is in PostgreSQL 9.1 and up.

Best Answer

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pgAdmin timing

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