The DISTINCT in Your COUNT
On a machine with cores to spare you would expect Postgres to throw a few parallel workers at it, the way it does for almost any large scan. That one keyword, DISTINCT, switches off parallel query for the entire statement, and the larger your table the more it costs you. No setting or index changes that; the reason is in how the aggregate has to execute.
- ▪On a machine with cores to spare you would expect Postgres to throw a few parallel workers at it, the way it does for almost any large scan.
- ▪That one keyword, DISTINCT, switches off parallel query for the entire statement, and the larger your table the more it costs you.
- ▪No setting or index changes that; the reason is in how the aggregate has to execute.
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| Original publisher | boringSQL | Supercharge your SQL & PostgreSQL powers |
| Canonical URL | https://boringsql.com/posts/distinct-in-your-count/ |
| Publication time | Thu, 06 Aug 2026 19:40:50 +0000 |
| Retrieval time | 2026-08-06T19:56:08.488Z |
| Last seen | 2026-08-06T19:56:08.488Z |
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Opening excerpt (first ~120 words) tap to expand
Table of Contents The schema Two counts, two different plans Why the planner can't split it One DISTINCT poisons the whole statement The rewrite: push the DISTINCT into a GROUP BY ORDER BY aggregates hit the same wall The harder case: per-group distinct counts When to actually care Here is a query that shows up in every analytics workload: SELECT count(DISTINCT user_id) FROM events; It looks like the cheapest possible thing: count the distinct users. On a machine with cores to spare you would expect Postgres to throw a few parallel workers at it, the way it does for almost any large scan. It does not. That one keyword, DISTINCT, switches off parallel query for the entire statement, and the larger your table the more it costs you.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at boringSQL | Supercharge your SQL & PostgreSQL powers.
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