SELECT COUNT (*) can impact your Backend Application Performance, here is why

SELECT COUNT (*) can impact your Backend Application Performance, here is why

SELECT COUNT (*) can impact your Backend Application Performance, here is why. Aggregating large entries in the database (to perform a count for example) is a lot of work. The database has to sort through a large number of records whether in an index or in the table itself. Doing this too often can impact the performance of both your database and your application, let us discuss why count can be slow and an alternative if you want an estimate of the count.

aggregating large entries in the database (to perform a count for example) is a lot of work.

The database has to sort through a large number of records whether in an index or in the table itself.

Doing this too often can impact the performance of both your database and your application, let us discuss why count can be slow and an alternative if you want an estimate of the count.

0:00 intro

0:30 SELECT COUNT(G) //index scan because we have to fetch g and check if its null select count(g) from grades where id between 1000 and 4000;

2:50 SELECT COUNT() //index only scan because we don’t have to jump back to heap select count() from grades where id between 1000 and 4000;

4:00 SELECT COUNT(*) WITH UPDATE //do an update update grades set g = 10 where id between 1000 and 4000;

//index only scan but with heap fetches .. (slower) select count(*) from grades where id between 1000 and 4000;

7:00 COUNT gets slower more rows Estimate count explain (format json) select * from grades; analze grades

8:00 Return Count estimate

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