Re: Improve choose_custom_plan for initial partition prune case - Mailing list pgsql-hackers

Hi Amit:

  Very glad to see your comment!

On Fri, Oct 2, 2020 at 4:21 PM Amit Langote <amitlangote09@gmail.com> wrote:

Hi Andy,

On Fri, Oct 2, 2020 at 1:04 AM Andy Fan <zhihui.fan1213@gmail.com> wrote:
>
> Given the plan example:
>
> CREATE TABLE measurement (
>     city_id         int not null,
>     logdate         date not null,
>     peaktemp        int,
>     unitsales       int
> ) PARTITION BY RANGE (logdate);
>
> CREATE TABLE measurement_y2006m02 PARTITION OF measurement
>     FOR VALUES FROM ('2006-02-01') TO ('2006-03-01');
>
> CREATE TABLE measurement_y2006m03 PARTITION OF measurement
>     FOR VALUES FROM ('2006-03-01') TO ('2006-04-01');
>
> prepare s as select * from measurement where logdate = $1;
> execute s('2006-02-01').
>
> The generic plan will probably not be chosen because it doesn't reduce the cost
> which can be reduced at initial_prune while the custom plan reduces such cost
> at  planning time. which makes the cost comparison not fair.

I agree that there is something to be done here.  Actually, I think we
should try to find a solution that will allow us to consider not just
"initial" pruning, but also "execution-time" pruning.   The latter
will allow a nested loop join whose inner side scans a partitioned
table using a parameterized scan on the partition key to be favored
over other join plans, because that parameterized scan can use
execution-time pruning which can make the inner scan very cheap.

This looks like to resolve another important issue of partition prune, which

may happen at planning time totally (no generic plan or custom plan involved). 

for example between choosing a Nest Loop plan which can use

some run-time partition prune and hash join which can't.  I "repeat" your idea

just to  make sure I understand you correctly. 

 

>  I'm thinking if we can
> get an estimated cost reduction of initial_prunne for generic plan based on the
> partition pruned at plan time from custom plan and then reducing
> such costs from the generic plan.  I just went through the related code but
> didn't write anything now.  I'd like to see if this is a correct direction to go.

That's an interesting idea, that is, to try to do this totally outside
the planner.  When I was thinking about this a little while ago, I was
trying to find a way to adjust the cost of the plan in the planner
itself by looking at the runtime pruning info in the nodes that
support it, that is, Append, MergeAppend.  Actually, such an approach
had also come up in the original run-time pruning discussion [1].

 

Thank you for your comments. Looks like your approach can be helpful

for the both cases, and I did think a bit for that as well, However, that looks

complex (for me) AND I am prefer to guess how many partitions can be

pruned with real data even it is the real data in the past (I assume that 

will not cause too much difference in practice). 

I'm not sure if I should treat Robert's comments as an opposed idea[1] , 

but I think there are some little differences.  I'd like to implement my idea

soon, and I'm glad to see any opposed idea at any time, of course the sooner 

the better:) 

After some day's coding in this direction, I find a very upsetting situation.

The main idea here is if we have N partition survived for custom plan after

plan time partition prune, then I assume we can get the similar partition 

survived for generic plan after initial partition prune.  Then we should reduce

such costs from generic plans.

However the hard part in implementation is we can't associate the Append 

node in the generic plan with the survived partition information from the 

custom plan even Append node has apprelids in it.

1. Associate them with rtindex. The final rtindex is impacted by glob->finalrtable,

 however the glob->finalrtable includes the child partitions, we will get less 

finalrtable in the custom plan so rtindex can't be matched.

2. Associate them with RelationOid, and we can record such information in the

 Append node as well. The bad part is the same relation Oid may appear multiple

 times in a query. for example: SELECT .. FROM p p1,  p p2 where p1.partkey1 = $1
 AND p2.partkey2 = $2;