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From: prankware <esavelievcode@gmail.com>
Date: Tue, 30 Jun 2026 16:48:26 +0300
Message-ID: 
 <CAF=hKRCX9sf5Occjdft51sWwztW_MyRN-bnVvs05yeCbBLMPNQ@mail.gmail.com>
Subject: Re: COALESCE patch
To: pgsql-hackers@lists.postgresql.org
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rebase and refactor format for cfbot

=D0=B2=D1=82, 30 =D0=B8=D1=8E=D0=BD. 2026=E2=80=AF=D0=B3. =D0=B2 14:26, pra=
nkware <esavelievcode@gmail.com>:
>
> Hi everyone,
>
> The planner ignores column statistics when an equality has a COALESCE
> expression on one side. For a clause like COALESCE(a, b) =3D $1, or a joi=
n on
> COALESCE(t1.a, t1.b) =3D COALESCE(t2.c, t2.d), there are no statistics on=
 the
> COALESCE node itself, so eqsel() and eqjoinsel() return the generic 0.005
> estimate while the per-column stats for a, b, c and d sit unused. The onl=
y way
> around this today is an expression index or extended statistics on that e=
xact
> expression, which doesn't scale across many different COALESCE clauses.
> estimate_hash_bucket_stats() has the same gap: a COALESCE hash key gets a
> default ndistinct and therefore a default bucket size. Since these expres=
sions
> are common in joins and filters over nullable or fallback columns, the de=
fault
> estimate can be far enough off to flip the join order or join method.
>
> The idea is to estimate straight from the existing per-column stats, with=
 no
> extra statistics object. COALESCE(arg_1, ..., arg_n) returns arg_i only w=
hen
> arg_1 .. arg_{i-1} are all NULL, so the chance of reaching branch i is th=
e
> product of stanullfrac over the earlier branches. Selectivity of
> COALESCE(l_1..l_M) =3D COALESCE(r_1..r_N) is then the sum over branch pai=
rs of
> P(reach l_i) * P(reach r_j) * sel(l_i =3D r_j), and each sel(l_i =3D r_j)=
 is a
> recursive call back into eqsel()/eqjoinsel(). A non-COALESCE side is trea=
ted as
> a one-branch list, so scalar COALESCE(a, b) =3D const falls out of the sa=
me code,
> and the same decomposition feeds estimate_hash_bucket_stats(). If any bra=
nch is
> missing stats, the code bails and today's behavior is unchanged.
>
> A minimal example:
>
>     CREATE TABLE t (a int, b int);
>     INSERT INTO t
>       SELECT CASE WHEN i % 5 < 2 THEN NULL ELSE i END, i
>       FROM generate_series(1, 1000) i;
>     ANALYZE t;
>
>     EXPLAIN SELECT * FROM t WHERE COALESCE(a, b) =3D 42;
>
> After ANALYZE, a is NULL in 400 of the 1000 rows (stanullfrac 0.4, ndisti=
nct
> 600) and b has no NULLs (stanullfrac 0, ndistinct 1000). COALESCE(a, b) i=
s
> unique, so exactly one row matches. Each branch is weighted by the probab=
ility
> of reaching it, the product of stanullfrac over the branches before it:
>
>     branch a:  reach 1.0,  sel(a =3D 42) =3D (1 - 0.4) / 600  =3D 0.001
>     branch b:  reach 0.4,  sel(b =3D 42) =3D (1 - 0.0) / 1000 =3D 0.001
>
>     selectivity =3D 1.0 * 0.001 + 0.4 * 0.001 =3D 0.0014  ->  ~1 row out =
of 1000
>
> The patch lands on ~1 row, matching reality. The 0.005 default (5 rows) i=
s not
> derived from the table at all: it is the 1/DEFAULT_NUM_DISTINCT constant =
the
> planner falls back to with no statistics on the expression, so it stays 5=
 rows
> regardless of the null fraction or the ndistinct of a and b.
>
> Feedback is welcome.
>
> Regards,
> Egor Savelev,
> Tantor Labs LLC,
> https://tantorlabs.com/

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