Thread: Optimizing count(), but Explain estimates wildly off

Dear pgsqlers,

I'm trying to optimize simple queries on two tables (tenders & items) with a couple million records.  Besides the resulting records, the app also displays the count of total results.  Doing count() takes as much time as the other query (which can be 30+ secs), so it's an obvious target for optimization.  I'm already caching count() results for the most common conditions (country & year) in a material table, which practically halves response time.  The tables are updated sparingly, and only with bulk COPYs.  Now I'm looking for ways to optimize queries with other conditions.

Reading around, seems many people are still using this 2005 snippet to obtain the row count estimate from Explain:

CREATE FUNCTION count_estimate(query text) RETURNS integer AS $$
DECLARE  rec   record;  rows  integer;
BEGIN  FOR rec IN EXECUTE 'EXPLAIN ' || query LOOP    rows := substring(rec."QUERY PLAN" FROM ' rows=([[:digit:]]+)');    EXIT WHEN rows IS NOT NULL;  END LOOP;  RETURN rows;
END;
$$ LANGUAGE plpgsql VOLATILE STRICT;

Is this still the current best practice?  Any tips to increase precision?  Currently it can estimate the actual number of rows for over or under a million, as seen on the sample queries (1,955,297 instead of 1,001,200; 162,080 instead of 1,292,010).

Any other tips to improve the query are welcome, of course.  There's a big disparity between the two sample queries plans even though only the filtered country changes.

I already raised default_statistics_target up to 2k (the planner wasn't using indexes at all with low values).  Gotta get it even higher? These are my custom settings:

shared_buffers = 256MB                  # min 128kB

work_mem = 128MB                                # min 64kB

maintenance_work_mem = 254MB            # min 1MB

effective_cache_size = 2GB

default_statistics_target = 2000

random_page_cost = 1.0                  # same scale as above

Sample query:

Explain Analyze Select * from tenders inner join items on transaction_id = tender_transaction_id where country = 'Colombia' and "date" >= '2023-01-01' and "date" < '2024-01-01'
QUERY PLAN
Gather  (cost=253837.99..1506524.32 rows=1955297 width=823) (actual time=51433.592..63239.809 rows=1001200 loops=1)   Workers Planned: 2   Workers Launched: 2   ->  Parallel Hash Join  (cost=252837.99..1309994.62 rows=814707 width=823) (actual time=51361.920..61729.142 rows=333733 loops=3)         Hash Cond: (items.tender_transaction_id = tenders.transaction_id)         ->  Parallel Seq Scan on items  (cost=0.00..1048540.46 rows=3282346 width=522) (actual time=1.689..56887.108 rows=2621681 loops=3)         ->  Parallel Hash  (cost=247919.56..247919.56 rows=393475 width=301) (actual time=2137.473..2137.476 rows=333733 loops=3)               Buckets: 1048576  Batches: 1  Memory Usage: 219936kB               ->  Parallel Bitmap Heap Scan on tenders  (cost=16925.75..247919.56 rows=393475 width=301) (actual time=385.315..908.865 rows=333733 loops=3)                     Recheck Cond: ((country = 'Colombia'::text) AND (date >= '2023-01-01'::date) AND (date < '2024-01-01'::date))                     Heap Blocks: exact=24350                     ->  Bitmap Index Scan on tenders_country_and_date_index  (cost=0.00..16689.67 rows=944339 width=0) (actual time=423.213..423.214 rows=1001200 loops=1)                           Index Cond: ((country = 'Colombia'::text) AND (date >= '2023-01-01'::date) AND (date < '2024-01-01'::date))
Planning Time: 12.784 ms
JIT:
Functions: 33
Options: Inlining true, Optimization true, Expressions true, Deforming true
Timing: Generation 14.675 ms, Inlining 383.349 ms, Optimization 1023.521 ms, Emission 651.442 ms, Total 2072.987 ms
Execution Time: 63378.033 ms

Explain Analyze Select * from tenders inner join items on transaction_id = tender_transaction_id where country = 'Mexico' and "date" >= '2023-01-01' and "date" < '2024-01-01'
QUERY PLAN
Gather  (cost=1000.99..414258.70 rows=162080 width=823) (actual time=52.538..7006.128 rows=1292010 loops=1)   Workers Planned: 2   Workers Launched: 2   ->  Nested Loop  (cost=0.99..397050.70 rows=67533 width=823) (actual time=40.211..4087.081 rows=430670 loops=3)         ->  Parallel Index Scan using tenders_country_and_date_index on tenders  (cost=0.43..45299.83 rows=32616 width=301) (actual time=4.376..59.760 rows=1218 loops=3)               Index Cond: ((country = 'Mexico'::text) AND (date >= '2023-01-01'::date) AND (date < '2024-01-01'::date))         ->  Index Scan using items_tender_transaction_id_index on items  (cost=0.56..10.67 rows=11 width=522) (actual time=0.321..3.035 rows=353 loops=3655)               Index Cond: (tender_transaction_id = tenders.transaction_id)
Planning Time: 7.808 ms
JIT:
Functions: 27
Options: Inlining false, Optimization false, Expressions true, Deforming true
Timing: Generation 17.785 ms, Inlining 0.000 ms, Optimization 5.080 ms, Emission 93.274 ms, Total 116.138 ms
Execution Time: 7239.427 ms

Thanks in advance!