Обсуждение: Extend more usecase for planning time partition pruning and init partition pruning.

Hi:

 I recently found a use case like this.  SELECT * FROM p, q WHERE p.partkey =
 q.colx AND (q.colx = $1 OR q.colx = $2); Then we can't do either planning time
 partition prune or init partition prune.  Even though we have run-time
 partition pruning work at last, it is too late in some cases since we have
 to init all the plan nodes in advance.  In my case, there are 10+
 partitioned relation in one query and the execution time is short, so the
 init plan a lot of plan nodes cares a lot.

The attached patches fix this issue. It just get the "p.partkey = q.colx"
case in root->eq_classes or rel->joinlist (outer join), and then check if there
is some baserestrictinfo in another relation which can be used for partition
pruning. To make the things easier, both partkey and colx must be Var
expression in implementation.

- v1-0001-Make-some-static-functions-as-extern-and-extend-C.patch

Just some existing refactoring and extending ChangeVarNodes to be able

to change var->attno.

- v1-0002-Build-some-implied-pruning-quals-to-extend-the-us.patch

Do the real job.

Thought?

--

Best Regards

Andy Fan (https://www.aliyun.com/)

On Sun, Jan 24, 2021 at 6:34 PM Andy Fan <zhihui.fan1213@gmail.com> wrote:

Hi:

 I recently found a use case like this.  SELECT * FROM p, q WHERE p.partkey =
 q.colx AND (q.colx = $1 OR q.colx = $2); Then we can't do either planning time
 partition prune or init partition prune.  Even though we have run-time
 partition pruning work at last, it is too late in some cases since we have
 to init all the plan nodes in advance.  In my case, there are 10+
 partitioned relation in one query and the execution time is short, so the
 init plan a lot of plan nodes cares a lot.

The attached patches fix this issue. It just get the "p.partkey = q.colx"
case in root->eq_classes or rel->joinlist (outer join), and then check if there
is some baserestrictinfo in another relation which can be used for partition
pruning. To make the things easier, both partkey and colx must be Var
expression in implementation.

- v1-0001-Make-some-static-functions-as-extern-and-extend-C.patch

Just some existing refactoring and extending ChangeVarNodes to be able

to change var->attno.

- v1-0002-Build-some-implied-pruning-quals-to-extend-the-us.patch

Do the real job.

Thought?

--

Best Regards

Andy Fan (https://www.aliyun.com/)

Some results from this patch. 

create table p (a int, b int, c character varying(8)) partition by list(c);
create table p1  partition of p for values in ('000001');
create table p2  partition of p for values in ('000002');
create table p3  partition of p for values in ('000003');
create table q (a int, c character varying(8), b int) partition by list(c);
create table q1  partition of q for values in ('000001');
create table q2  partition of q for values in ('000002');
create table q3  partition of q for values in ('000003');

Before the patch:
postgres=# explain (costs off) select * from p inner join q on p.c = q.c and q.c > '000002';
                     QUERY PLAN
----------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
         ->  Seq Scan on p3 p_3
   ->  Hash
         ->  Seq Scan on q3 q
               Filter: ((c)::text > '000002'::text)
(9 rows)

After the patch:

                     QUERY PLAN
----------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Seq Scan on p3 p
   ->  Hash
         ->  Seq Scan on q3 q
               Filter: ((c)::text > '000002'::text)
(6 rows)


Before the patch:
postgres=# explain (costs off) select * from p inner join q on p.c = q.c and (q.c = '000002' or q.c = '000001');
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
         ->  Seq Scan on p3 p_3
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(12 rows)

After the patch:
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(11 rows)

Before the patch:
postgres=# explain (costs off) select * from p left join q on p.c = q.c where (q.c = '000002' or q.c = '000001');
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
         ->  Seq Scan on p3 p_3
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(12 rows)

After the patch:
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(11 rows)

--

Best Regards

Andy Fan (https://www.aliyun.com/)

On Mon, Jan 25, 2021 at 10:21 AM Andy Fan <zhihui.fan1213@gmail.com> wrote:

On Sun, Jan 24, 2021 at 6:34 PM Andy Fan <zhihui.fan1213@gmail.com> wrote:

Hi:

 I recently found a use case like this.  SELECT * FROM p, q WHERE p.partkey =
 q.colx AND (q.colx = $1 OR q.colx = $2); Then we can't do either planning time
 partition prune or init partition prune.  Even though we have run-time
 partition pruning work at last, it is too late in some cases since we have
 to init all the plan nodes in advance.  In my case, there are 10+
 partitioned relation in one query and the execution time is short, so the
 init plan a lot of plan nodes cares a lot.

The attached patches fix this issue. It just get the "p.partkey = q.colx"
case in root->eq_classes or rel->joinlist (outer join), and then check if there
is some baserestrictinfo in another relation which can be used for partition
pruning. To make the things easier, both partkey and colx must be Var
expression in implementation.

- v1-0001-Make-some-static-functions-as-extern-and-extend-C.patch

Just some existing refactoring and extending ChangeVarNodes to be able

to change var->attno.

- v1-0002-Build-some-implied-pruning-quals-to-extend-the-us.patch

Do the real job.

Thought?

--

Best Regards

Andy Fan (https://www.aliyun.com/)

Some results from this patch. 

create table p (a int, b int, c character varying(8)) partition by list(c);
create table p1  partition of p for values in ('000001');
create table p2  partition of p for values in ('000002');
create table p3  partition of p for values in ('000003');
create table q (a int, c character varying(8), b int) partition by list(c);
create table q1  partition of q for values in ('000001');
create table q2  partition of q for values in ('000002');
create table q3  partition of q for values in ('000003');

Before the patch:
postgres=# explain (costs off) select * from p inner join q on p.c = q.c and q.c > '000002';
                     QUERY PLAN
----------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
         ->  Seq Scan on p3 p_3
   ->  Hash
         ->  Seq Scan on q3 q
               Filter: ((c)::text > '000002'::text)
(9 rows)

After the patch:

                     QUERY PLAN
----------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Seq Scan on p3 p
   ->  Hash
         ->  Seq Scan on q3 q
               Filter: ((c)::text > '000002'::text)
(6 rows)


Before the patch:
postgres=# explain (costs off) select * from p inner join q on p.c = q.c and (q.c = '000002' or q.c = '000001');
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
         ->  Seq Scan on p3 p_3
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(12 rows)

After the patch:
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(11 rows)

Before the patch:
postgres=# explain (costs off) select * from p left join q on p.c = q.c where (q.c = '000002' or q.c = '000001');
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
         ->  Seq Scan on p3 p_3
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(12 rows)

After the patch:
                                         QUERY PLAN
--------------------------------------------------------------------------------------------
 Hash Join
   Hash Cond: ((p.c)::text = (q.c)::text)
   ->  Append
         ->  Seq Scan on p1 p_1
         ->  Seq Scan on p2 p_2
   ->  Hash
         ->  Append
               ->  Seq Scan on q1 q_1
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
               ->  Seq Scan on q2 q_2
                     Filter: (((c)::text = '000002'::text) OR ((c)::text = '000001'::text))
(11 rows)

--

Best Regards

Andy Fan (https://www.aliyun.com/)

Here is a performance test regarding this patch.  In the following simple case,

we can get 3x faster than before.  

create table p (a int, b int, c int) partition by list(c);
select 'create table p_'||i||' partition of p for values in (' || i || ');' from generate_series(1, 100)i; \gexec
insert into p select i, i, i from generate_series(1, 100)i;
create table m as select * from p;
analyze m;
analyze p;

test sql:  select * from m, p where m.c = p.c and m.c in (3, 10);  

With this patch:  1.1ms

Without this patch: 3.4ms 

I'm happy with the result and the implementation,  I have add this into

commitfest https://commitfest.postgresql.org/32/2975/ 

Thanks. 

--

Best Regards

Andy Fan (https://www.aliyun.com/)

On Thu, 4 Mar 2021 at 22:07, Amit Langote <amitlangote09@gmail.com> wrote:
> * Or maybe have you considered generalizing what
> build_implied_pruning_quals() does so that other places like
> indxpath.c can use the facility?

I agree with doing it another way.  There's plenty of other queries
which we could produce a better plan for if EquivalenceClass knew
about things like IN conditions and >=, >, < and <= btree ops.

It seems wrong to code anything in this regard that's specific to
partition pruning.

Please see [1] for an idea. IIRC, the implementation was not well
received and there were concerns about having to evaluate additional
needless quals. That part I think can be coded around. The trick will
be to know when and when not to use additional quals.

The show stopper for me was having a more efficient way to find if a
given Expr exists in an EquivalenceClass. This is why I didn't take
the idea further, at the time. My implementation in that patch
required lots of looping to find if a given Expr had an existing
EquivalenceMember, to which there was a danger of that becoming slow
for complex queries.

I'm unsure right now if it would be possible to build standard
EquivalenceMembers and EquivalenceFilters in the same pass.  I think
it might require 2 passes since you only can use IN and range type
quals for Exprs that actually have a EquivalenceMember. So you need to
wait until you're certain there's some equality OpExpr before adding
EquivalenceFilters. (Pass 1 can perhaps remember if anything looks
interesting and then skip pass 2 if there's not...??)

EquivalenceClass might be slightly faster now since we have
RelOptInfo.eclass_indexes. However, I've not checked to see if the
indexes will be ready in time for when you'd be building the
additional filters. I'm guessing that they wouldn't be since you'd
still be building the EquivalenceClasses at that time.  Certainly,
process_equivalence() could do much faster lookups of Exprs if there
was some global index for all EquivalenceMembers. However,
equalfuncs.c only gives us true or false if two nodes are equal().
We'd need to either have a -1, 0, +1 value or be able to hash nodes
and put things into a hash table. Else we're stuck trawling through
lists comparing each item 1-by-1. That's pretty slow. Especially with
complex queries.

Both Andres and I have previously suggested ways to improve Node
searching.  My idea is likely easier to implement, as it just changed
equalfuncs.c to add a function that returns -1, 0, +1 so we could use
a binary search tree to index Nodes. Andres' idea [2] is likely the
better of the two. Please have a look at that. It'll allow us to
easily build a function to hash nodes and put them in a hash table.

To get [1], the implementation will need to be pretty smart. There's
concern about the idea. See [3]. You'll need to ensure you're not
adding too much planner overhead and also not slowing down execution
for cases by adding additional qual evals that are redundant.

It's going to take some effort to make everyone happy here.

David

[1] https://www.postgresql.org/message-id/flat/CAKJS1f9fPdLKM6%3DSUZAGwucH3otbsPk6k0YT8-A1HgjFapL-zQ%40mail.gmail.com#024ad18e19bb9b6c022fb572edc8c992
[2] https://www.postgresql.org/message-id/flat/20190828234136.fk2ndqtld3onfrrp%40alap3.anarazel.de
[3] https://www.postgresql.org/message-id/flat/30810.1449335261@sss.pgh.pa.us#906319f5e212fc3a6a682f16da079f04