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Comment by drbojingle | Hacker News Reader

You could ask for a count of records and divide by the page size.

Counts become incredibly slow on some databases like Postgres. It needs to do a sequential scan, which results in slow(er) performance on even a ten- thousands of rows. When operating at scale, this is very, very slow.

This seems unlikely to depend on which database software. It could easily depend on what indexes exist for the query.

From what I understand it's not slow if it can use an index, but the criteria for that are rather hard to understand as a normal user. If you vacuum often enough and the visibility map is current, it doesn't need a full table scan.

Isn't count slow on most databases? Either it ends up in table scan or index scan. But if the index is huge, then that will also take a lot of time.

I wonder how do Big Co solve this counting problem.

This is what I do, since counts should cause minimal overhead (I've never had to deal with huge databases). But neither does the N+1 records trick which OP describes, that's clever. :)

Counts can cause significant overhead on even millions of rows.

If I were to ask the number of even numbers greater than zero and less than 10 billion, you could very quickly give an exact answer. If I were to ask the exact number of prime numbers on that same range, it would take much longer to find the correct answer.

In the same way, asking for counts may or may not be a quick answer, depending on both the table structure and the query being performed. Query the number of customers who started this year, on a table indexed by start date, and it's incredibly cheap. If that same table is only indexed by last name, then counts become more expensive. I'd say that the advice to return the counts has an implicit addendum to make sure that your database is appropriately indexed such that your typical queries are cheap to perform.

So I'm coming at this from a Postgres POV, IIRC MySQL can take some shortcuts for COUNT(*). Constraining the query will help but counting is expensive as a sequential table scan is always required.

Meanwhile I can only think of one use case for pagination with exact row counts – a user facing application. If you're preallocating storage you can get by with an estimate. If you're consuming an API and want something from near the end you can flip the sort order.

Not necessarily in postgres. If an index is available it may use that, though it will still have to refer to the visibility map to see if any row is available to the current transaction (cheap check), and if it can't determine from that, then and only then does it need to also refer to the heap / actual table (slower check).

Is that a recent change? Back in 2016 the Citus guys claimed that:

  There is no single universal row count that the database could cache, so it must
  scan through all rows counting how many are visible. Performance for an exact
  count grows linearly with table size.

https://www.citusdata.com/blog/2016/10/12/count-performance/

Apologies, I should've clarified. I just meant postgres doesn't necessarily have to scan the actual table to get the count in some cases if an index is available, not that it caches the actual count.

So that's not the greatest quote but the article shows postgres having to fall back on a sequential scan for a naive COUNT(*). The author goes on to mention that as of 9.2 Postgres can do an index scan (in the context of SELECT DISTINCT):

  But now we come to a quirk, SELECT COUNT(DISTINCT n) FROM items will not use
  the index even though SELECT DISTINCT n does. As many blog posts mention (“one
  weird trick to make postgres 50x faster!”) you can guide the planner by rewriting
  count distinct as the count of a subquery

To me it seems like you can trick the query planner into doing an index scan sometimes, but that it's a bit brittle. Has this improved much since?

I think the wiki explains it well

https://wiki.postgresql.org/wiki/Index-only_scans#Is_.22coun...

It says that index only scans can be used with predicates and less often without predicates, though in my experience I've seen the index often used even without predicates.

Relevant quote:

  Index-only scans are opportunistic, in that they take advantage of a pre-existing
  state of affairs where it happens to be possible to elide heap access. However,
  the server doesn't make any particular effort to facilitate index-only scans,
  and it is difficult to recommend a course of action to make index-only scans
  occur more frequently, except to define covering indexes in response to a
  measured need

And:

  Index-only scans are only used when the planner surmises that that will reduce the
  total amount of I/O required, according to its imperfect cost-based modelling. This all
  heavily depends on visibility of tuples, if an index would be used anyway (i.e. how
  selective a predicate is, etc), and if there is actually an index available that could
  be used by an index-only scan in principle.

So yeah, I don't know if your use case is exceptionally lucky or if the documentation is just pessimistic (or both). Good to know you can coerce the query planner into doing an index scan though.

It's slow and expensive in MySQL too, assuming you mean InnoDB storage engine. Recent versions of MySQL can parallelize a COUNT(*), but that only helps so much.

The "shortcuts" you're thinking of may be from the MyISAM storage engine days. Since MyISAM doesn't have transactions or MVCC, it can maintain a row count for the table and just return that. But MyISAM is generally not used for the past decade (or more), as it just isn't really suitable for storing data that you care about.

Storage engines with transactions cannot just store a row count per table because the accurate count always depends on your transaction's isolated snapshot.

Sure, but that point you've really got to start thinking about architecture.

Do you really need to paginate millions of rows and count them? Can you distribute the database and parallelize counting? Can you save counts somewhere else? Can you use estimates?

Thanks, that's good to know (will have to perform some tests at some point). I do have a few tables (namely logs) that will have millions of rows eventually over time. But there I've also been planning on rotating them whenever that becomes a problem, so I'm not overly concerned. Or experiment with OP's solution.

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