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Optimize DISTINCT, ORDER BY and DISTINCT ON when Aggregation without Group By. #685

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For query which has Aggregation but without Group by clause, the DISTINCT/DISTINCT ON/ORDER BY clause could be removed as there would be one row returned at most.
And there is no necessary to do unique or sort.
This can simply the plan, and process less expressions like: Aggref nodes during planner.

DISTINCT

explain(verbose, costs off)
select distinct count(a), sum(b) from t_distinct_sort ;
                               QUERY PLAN
------------------------------------------------------------------------
 Unique
   Output: (count(a)), (sum(b))
   Group Key: (count(a)), (sum(b))
   ->  Sort
         Output: (count(a)), (sum(b))
         Sort Key: (count(t_distinct_sort.a)), (sum(t_distinct_sort.b))
         ->  Finalize Aggregate
               Output: count(a), sum(b)
               ->  Gather Motion 3:1  (slice1; segments: 3)
                     Output: (PARTIAL count(a)), (PARTIAL sum(b))
                     ->  Partial Aggregate
                           Output: PARTIAL count(a), PARTIAL sum(b)
                           ->  Seq Scan on public.t_distinct_sort
                                 Output: a, b, c
 Settings: optimizer = 'off'
 Optimizer: Postgres query optimizer
(16 rows)

After this commit:

explain(verbose, costs off)
select distinct count(a), sum(b) from t_distinct_sort ;
                                                        QUERY PLAN                                                         
---------------------------------------------------------------------------------------------------------------------------
 Finalize Aggregate
   Output: count(a), sum(b)
   ->  Gather Motion 3:1  (slice1; segments: 3)
         Output: (PARTIAL count(a)), (PARTIAL sum(b))
         ->  Partial Aggregate
               Output: PARTIAL count(a), PARTIAL sum(b)
               ->  Seq Scan on public.t_distinct_sort
                     Output: a, b, c
  Optimizer: Postgres query optimizer
(10 rows)

DISTINCT ON and ORDER BY

select distinct on(count(b), count(c)) count(a), sum(b) from t_distinct_sort order by count(c);
                           QUERY PLAN
--------------------------------------------------------------------
 Unique
   Output: (count(a)), (sum(b)), (count(c)), (count(b))
   Group Key: (count(c)), (count(b))
   ->  Sort
         Output: (count(a)), (sum(b)), (count(c)), (count(b))
         Sort Key: (count(t_distinct_sort.c)),
(count(t_distinct_sort.b))
         ->  Finalize Aggregate
               Output: count(a), sum(b), count(c), count(b)
               ->  Gather Motion 3:1  (slice1; segments: 3)
                     Output: (PARTIAL count(a)), (PARTIAL sum(b)),
(PARTIAL count(c)), (PARTIAL count(b))
                     ->  Partial Aggregate
                           Output: PARTIAL count(a), PARTIAL sum(b),
PARTIAL count(c), PARTIAL count(b)
                           ->  Seq Scan on public.t_distinct_sort
                                 Output: a, b, c

After this commit:

select distinct on(count(b), count(c)) count(a), sum(b) from t_distinct_sort order by count(c);
                      QUERY PLAN
--------------------------------------------------------
 Finalize Aggregate
   Output: count(a), sum(b)
   ->  Gather Motion 3:1  (slice1; segments: 3)
         Output: (PARTIAL count(a)), (PARTIAL sum(b))
         ->  Partial Aggregate
               Output: PARTIAL count(a), PARTIAL sum(b)
               ->  Seq Scan on public.t_distinct_sort
                     Output: a, b, c
 Optimizer: Postgres query optimizer

ORDER BY

explain(verbose, costs off)
select count(a), sum(b) from t_distinct_sort order by sum(a), count(c);
                                            QUERY PLAN
--------------------------------------------------------------------------------------------------
 Sort
   Output: (count(a)), (sum(b)), (sum(a)), (count(c))
   Sort Key: (sum(t_distinct_sort.a)), (count(t_distinct_sort.c))
   ->  Finalize Aggregate
         Output: count(a), sum(b), sum(a), count(c)
         ->  Gather Motion 3:1  (slice1; segments: 3)
               Output: (PARTIAL count(a)), (PARTIAL sum(b)), (PARTIAL sum(a)), (PARTIAL count(c))
               ->  Partial Aggregate
                     Output: PARTIAL count(a), PARTIAL sum(b), PARTIAL sum(a), PARTIAL count(c)
                     ->  Seq Scan on public.t_distinct_sort
                           Output: a, b, c
 Settings: optimizer = 'off'
 Optimizer: Postgres query optimizer
(13 rows)

After this commit:

explain(verbose, costs off)
select count(a), sum(b) from t_distinct_sort order by sum(a), count(c);
                                                        QUERY PLAN                                                         
---------------------------------------------------------------------------------------------------------------------------
 Finalize Aggregate
   Output: count(a), sum(b)
   ->  Gather Motion 3:1  (slice1; segments: 3)
         Output: (PARTIAL count(a)), (PARTIAL sum(b))
         ->  Partial Aggregate
               Output: PARTIAL count(a), PARTIAL sum(b)
               ->  Seq Scan on public.t_distinct_sort
                     Output: a, b, c
 Optimizer: Postgres query optimizer
(10 rows)

DISTINCT and ORDER BY

select distinct count(a), sum(b) from t_distinct_sort order by sum(b), count(a);
                               QUERY PLAN
------------------------------------------------------------------------
 Unique
   Output: (count(a)), (sum(b))
   Group Key: (sum(b)), (count(a))
   ->  Sort
         Output: (count(a)), (sum(b))
         Sort Key: (sum(t_distinct_sort.b)), (count(t_distinct_sort.a))
         ->  Finalize Aggregate
               Output: count(a), sum(b)
               ->  Gather Motion 3:1  (slice1; segments: 3)
                     Output: (PARTIAL count(a)), (PARTIAL sum(b))
                     ->  Partial Aggregate
                           Output: PARTIAL count(a), PARTIAL sum(b)
                           ->  Seq Scan on public.t_distinct_sort
                                 Output: a, b, c
 Settings: optimizer = 'off'
 Optimizer: Postgres query optimizer
(16 rows)

After this commit:

select distinct count(a), sum(b) from t_distinct_sort order by sum(b), count(a);
                                                        QUERY PLAN                                                         
---------------------------------------------------------------------------------------------------------------------------
 Finalize Aggregate
   Output: count(a), sum(b)
   ->  Gather Motion 3:1  (slice1; segments: 3)
         Output: (PARTIAL count(a)), (PARTIAL sum(b))
         ->  Partial Aggregate
               Output: PARTIAL count(a), PARTIAL sum(b)
               ->  Seq Scan on public.t_distinct_sort
                     Output: a, b, c
  Optimizer: Postgres query optimizer
(10 rows)

Authored-by: Zhang Mingli [email protected]

fix #ISSUE_Number


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@avamingli
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Many plan diffs, will fix later.

@avamingli
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avamingli commented Nov 4, 2024

For query which has Aggregation but without Group by clause, the DISTINCT/DISTINCT ON/ORDER BY clause could be removed as there would be one row returned at most.

SRF will break the assumption.

 select count(*), generate_series(1, 4) from t1;
 count | generate_series
-------+-----------------
     3 |               1
     3 |               2
     3 |               3
     3 |               4
(4 rows)

Fix it and Postgres' WITH ORDINALITY as well.

@fanfuxiaoran
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fanfuxiaoran commented Nov 18, 2024

I took a look at orca, it has already optimized distinct function.

explain  select  distinct(count(a)) from foo;
                                     QUERY PLAN
------------------------------------------------------------------------------------
 Finalize Aggregate  (cost=0.00..526.96 rows=1 width=8)
   ->  Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..526.96 rows=1 width=8)
         ->  Partial Aggregate  (cost=0.00..526.96 rows=1 width=8)
               ->  Seq Scan on foo  (cost=0.00..500.67 rows=3333334 width=4)
 Optimizer: Pivotal Optimizer (GPORCA)
(5 rows)

Even if with group by , the distinct also can be removed

explain  select  distinct(count(a)) from foo group by a ;
                                                       QUERY PLAN
------------------------------------------------------------------------------------------------------------------------
 Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..1395.69 rows=1000 width=8)
   ->  HashAggregate  (cost=0.00..1395.66 rows=334 width=8)
         Group Key: (count(a))
         ->  Redistribute Motion 3:3  (slice2; segments: 3)  (cost=0.00..1395.62 rows=334 width=8)
               Hash Key: (count(a))
               ->  Streaming HashAggregate  (cost=0.00..1395.61 rows=334 width=8)
                     Group Key: count(a)
                     ->  HashAggregate  (cost=0.00..985.15 rows=3333334 width=8)
                           Group Key: a
                           Planned Partitions: 16
                           ->  Redistribute Motion 3:3  (slice3; segments: 3)  (cost=0.00..567.20 rows=3333334 width=4)
                                 Hash Key: a
                                 ->  Seq Scan on foo  (cost=0.00..500.67 rows=3333334 width=4)
 Optimizer: Pivotal Optimizer (GPORCA)
(14 rows)

as distinct is a function which only works in a group.

The function called PexprRemoveSuperfluousDistinctInDQA in orca.

@avamingli
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I took a look at orca, it has already optimized distinct function.

explain  select  distinct(count(a)) from foo;
                                     QUERY PLAN
------------------------------------------------------------------------------------
 Finalize Aggregate  (cost=0.00..526.96 rows=1 width=8)
   ->  Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..526.96 rows=1 width=8)
         ->  Partial Aggregate  (cost=0.00..526.96 rows=1 width=8)
               ->  Seq Scan on foo  (cost=0.00..500.67 rows=3333334 width=4)
 Optimizer: Pivotal Optimizer (GPORCA)
(5 rows)

Even if with group by , the distinct also can be removed

explain  select  distinct(count(a)) from foo group by a ;
                                                       QUERY PLAN
------------------------------------------------------------------------------------------------------------------------
 Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..1395.69 rows=1000 width=8)
   ->  HashAggregate  (cost=0.00..1395.66 rows=334 width=8)
         Group Key: (count(a))
         ->  Redistribute Motion 3:3  (slice2; segments: 3)  (cost=0.00..1395.62 rows=334 width=8)
               Hash Key: (count(a))
               ->  Streaming HashAggregate  (cost=0.00..1395.61 rows=334 width=8)
                     Group Key: count(a)
                     ->  HashAggregate  (cost=0.00..985.15 rows=3333334 width=8)
                           Group Key: a
                           Planned Partitions: 16
                           ->  Redistribute Motion 3:3  (slice3; segments: 3)  (cost=0.00..567.20 rows=3333334 width=4)
                                 Hash Key: a
                                 ->  Seq Scan on foo  (cost=0.00..500.67 rows=3333334 width=4)
 Optimizer: Pivotal Optimizer (GPORCA)
(14 rows)

as distinct is a function which only works in a group.

The function called PexprRemoveSuperfluousDistinctInDQA in orca.

Yeah, see #677 (reply in thread)

@fanfuxiaoran
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Contributor

I took a look at orca, it has already optimized distinct function.

explain  select  distinct(count(a)) from foo;
                                     QUERY PLAN
------------------------------------------------------------------------------------
 Finalize Aggregate  (cost=0.00..526.96 rows=1 width=8)
   ->  Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..526.96 rows=1 width=8)
         ->  Partial Aggregate  (cost=0.00..526.96 rows=1 width=8)
               ->  Seq Scan on foo  (cost=0.00..500.67 rows=3333334 width=4)
 Optimizer: Pivotal Optimizer (GPORCA)
(5 rows)

Even if with group by , the distinct also can be removed

explain  select  distinct(count(a)) from foo group by a ;
                                                       QUERY PLAN
------------------------------------------------------------------------------------------------------------------------
 Gather Motion 3:1  (slice1; segments: 3)  (cost=0.00..1395.69 rows=1000 width=8)
   ->  HashAggregate  (cost=0.00..1395.66 rows=334 width=8)
         Group Key: (count(a))
         ->  Redistribute Motion 3:3  (slice2; segments: 3)  (cost=0.00..1395.62 rows=334 width=8)
               Hash Key: (count(a))
               ->  Streaming HashAggregate  (cost=0.00..1395.61 rows=334 width=8)
                     Group Key: count(a)
                     ->  HashAggregate  (cost=0.00..985.15 rows=3333334 width=8)
                           Group Key: a
                           Planned Partitions: 16
                           ->  Redistribute Motion 3:3  (slice3; segments: 3)  (cost=0.00..567.20 rows=3333334 width=4)
                                 Hash Key: a
                                 ->  Seq Scan on foo  (cost=0.00..500.67 rows=3333334 width=4)
 Optimizer: Pivotal Optimizer (GPORCA)
(14 rows)

as distinct is a function which only works in a group.
The function called PexprRemoveSuperfluousDistinctInDQA in orca.

Yeah, see #677 (reply in thread)

Orca removed the distinct expression when it is used on the agg expression even if there is group by clause, do we need to consider that?

@avamingli
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Orca removed the distinct expression when it is used on the agg expression even if there is group by clause, do we need to consider that?

We can consider that type of optimization in the future.
In line with the goals of this PR, we have optimized statements like DISTINCT, DISTINCT ON, ORDER BY, and LIMIT.
However, given the presence of GROUP BY, the optimizations for ORDER BY and LIMIT may no longer apply.
With GROUP BY clause should be another topic for optimization.

For query which has Aggregation but without Group by clause, the
DISTINCT/DISTINCT ON/ORDER BY clause could be removed as there would
be one row returned at most.
And there is no necessary to do unique or sort.
This can simply the plan, and process less Aggref nodes during planner.

select distinct on(count(b), count(c)) count(a), sum(b) from
t_distinct_sort order by count(c);
                           QUERY PLAN
--------------------------------------------------------------------
 Unique
   Output: (count(a)), (sum(b)), (count(c)), (count(b))
   Group Key: (count(c)), (count(b))
   ->  Sort
         Output: (count(a)), (sum(b)), (count(c)), (count(b))
         Sort Key: (count(t_distinct_sort.c)),
(count(t_distinct_sort.b))
         ->  Finalize Aggregate
               Output: count(a), sum(b), count(c), count(b)
               ->  Gather Motion 3:1  (slice1; segments: 3)
                     Output: (PARTIAL count(a)), (PARTIAL sum(b)),
(PARTIAL count(c)), (PARTIAL count(b))
                     ->  Partial Aggregate
                           Output: PARTIAL count(a), PARTIAL sum(b),
PARTIAL count(c), PARTIAL count(b)
                           ->  Seq Scan on public.t_distinct_sort
                                 Output: a, b, c

After this commit:

select distinct on(count(b), count(c)) count(a), sum(b) from
t_distinct_sort order by count(c);
                      QUERY PLAN
--------------------------------------------------------
 Finalize Aggregate
   Output: count(a), sum(b)
   ->  Gather Motion 3:1  (slice1; segments: 3)
         Output: (PARTIAL count(a)), (PARTIAL sum(b))
         ->  Partial Aggregate
               Output: PARTIAL count(a), PARTIAL sum(b)
               ->  Seq Scan on public.t_distinct_sort
                     Output: a, b, c
 Optimizer: Postgres query optimizer

Authored-by: Zhang Mingli [email protected]
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