# Why is count(x.*) slower than count(*)?

## All we need is an easy explanation of the problem, so here it is.

``````explain select count(x.*) from customer x;
...
->  Partial Aggregate  (cost=27005.45..27005.46 rows=1 width=8)
->  Parallel Seq Scan on customer x  (cost=0.00..26412.56 rows=237156 width=994)
``````

``````explain select count(*) from customer x;
...

->  Partial Aggregate  (cost=27005.45..27005.46 rows=1 width=8)
->  Parallel Seq Scan on customer x  (cost=0.00..26412.56 rows=237156 width=0)
``````

The `COUNT(x.*)` here makes the `width` in the explain result read unnecessary row data.

I thought they should be identical, but it seems not, why?

## How to solve :

I know you bored from this bug, So we are here to help you! Take a deep breath and look at the explanation of your problem. We have many solutions to this problem, But we recommend you to use the first method because it is tested & true method that will 100% work for you.

### Method 1

Logically, both are identical – because `x.*` always counts, even when all columns are `NULL`.
But Postgres has a separate implementation for `count(*)`.

It does not bother with any expression at all and only considers the existence of live rows. That’s slightly faster, which sums up to a relevant difference over many rows.
The performance penalty for `count(x.*)` grows with the number of columns / width of rows, and will be rather substantial for wide rows like yours (`width=994`).

It’s even documented explicitly:

`count` ( `*` ) → `bigint`

Computes the number of input rows.

`count` ( `"any"` ) → `bigint`

Computes the number of input rows in which the input value is not
null.

The gist of it: whenever you don’t care whether an expression is `NULL`, use `count(*)` instead.

Related:

Some other RDBMS do not have the same fast path for `count(*)`. OTOH, counting all rows in a table is comparatively slow in Postgres due to its MVCC model that forces checking row visibility. See:

Note: Use and implement method 1 because this method fully tested our system.
Thank you 🙂