*Hola Lista* *Ya que en las últimas versiones de PostgreSQL contamos con muchas más herramientas para la optimización de las consultas (estadísticas, paralelismo, JIT, etc, etc,etc ) pues hoy me dio por probar la cláusula INCLUDE en los índices, con el fin de indagar por su correcto uso y/o beneficios, hice este pequeño laboratorio:*
drop table test create table test(mes text,cantidad int); insert into test(mes,cantidad) select b.mes, trunc(1000000*random()) FROM generate_series(1,300000) as a cross join (values('ENE'),('FEB'),('MAR'),('ABR'),('MAY'),('JUN'),('JUL'),('AGO'),('SEP'),('OCT'),('NOV'),('DIC')) as b(mes); analyze test; *-- sin indices* explain (ANALYZE,BUFFERS,TIMING) select sum(cantidad) from test where mes='JUN'; --- Finalize Aggregate (cost=23742.83..23742.83 rows=1 width=8) (actual time=174.405..174.406 rows=1 loops=1) Buffers: shared read=15930 -> Gather (cost=23742.62..23742.83 rows=2 width=8) (actual time=174.299..178.505 rows=3 loops=1) Workers Planned: 2 Workers Launched: 2 Buffers: shared read=15930 -> Partial Aggregate (cost=22742.62..22742.63 rows=1 width=8) (actual time=168.675..168.676 rows=1 loops=3) Buffers: shared read=15930 -> Parallel Seq Scan on test (cost=0.00..22680.00 rows=125250 width=4) (actual time=0.044..160.487 rows=100000 loops=3) Filter: (mes = 'JUN'::text) Rows Removed by Filter: 1100000 Buffers: shared read=15930 Planning Time: 0.149 ms Execution Time: 178.545 ms *-- indice solo por mes* create index concurrently idx_test_mes on test(mes); explain (ANALYZE,BUFFERS,TIMING) select sum(cantidad) from test where mes='JUN'; Aggregate (cost=18830.72..18830.73 rows=1 width=8) (actual time=238.116..238.116 rows=1 loops=1) Buffers: shared read=16752 -> Bitmap Heap Scan on test (cost=1385.12..18679.16 rows=303120 width=4) (actual time=28.007..206.884 rows=300000 loops=1) Recheck Cond: (mes = 'JUN'::text) Heap Blocks: exact=15930 Buffers: shared read=16752 -> Bitmap Index Scan on idx_test_mes (cost=0.00..1369.97 rows=303120 width=0) (actual time=25.312..25.312 rows=300000 loops=1) Index Cond: (mes = 'JUN'::text) Buffers: shared read=822 Planning Time: 0.321 ms Execution Time: 238.150 ms *-- indice por mes incluye cantidad* create index concurrently idx_test_mes2 on test(mes) include (cantidad); explain (ANALYZE,BUFFERS,TIMING) select sum(cantidad) from test where mes='JUN'; Aggregate (cost=18830.72..18830.73 rows=1 width=8) (actual time=227.678..227.678 rows=1 loops=1) Buffers: shared read=16752 -> Bitmap Heap Scan on test (cost=1385.12..18679.16 rows=303120 width=4) (actual time=26.342..198.513 rows=300000 loops=1) Recheck Cond: (mes = 'JUN'::text) Heap Blocks: exact=15930 Buffers: shared read=16752 -> Bitmap Index Scan on idx_test_mes2 (cost=0.00..1369.97 rows=303120 width=0) (actual time=23.680..23.680 rows=300000 loops=1) Index Cond: (mes = 'JUN'::text) Buffers: shared read=822 Planning Time: 0.540 ms Execution Time: 227.710 ms *-- consulta filtrando mes y cantidad* explain (ANALYZE,BUFFERS,TIMING) select sum(cantidad) from test where mes='JUN' and cantidad between 1000 and 40000 Aggregate (cost=18973.69..18973.69 rows=1 width=8) (actual time=352.304..352.304 rows=1 loops=1) Buffers: shared read=16752 -> Bitmap Heap Scan on test (cost=1370.56..18967.72 rows=11932 width=4) (actual time=29.374..350.099 rows=11687 loops=1) Recheck Cond: (mes = 'JUN'::text) Filter: ((cantidad >= 1000) AND (cantidad <= 40000)) Rows Removed by Filter: 288313 Heap Blocks: exact=15930 Buffers: shared read=16752 -> Bitmap Index Scan on idx_test_mes2 (cost=0.00..1369.97 rows=303120 width=0) (actual time=26.412..26.412 rows=300000 loops=1) Index Cond: (mes = 'JUN'::text) Buffers: shared read=822 Planning Time: 0.684 ms Execution Time: 352.349 ms *-- indice compuesto por mes y cantidad* create index concurrently idx_test_mes3 on test(mes,cantidad); explain (ANALYZE,BUFFERS,TIMING) select sum(cantidad) from test where mes='JUN'; Aggregate (cost=18830.72..18830.73 rows=1 width=8) (actual time=234.626..234.627 rows=1 loops=1) Buffers: shared read=16752 -> Bitmap Heap Scan on test (cost=1385.12..18679.16 rows=303120 width=4) (actual time=31.220..203.525 rows=300000 loops=1) Recheck Cond: (mes = 'JUN'::text) Heap Blocks: exact=15930 Buffers: shared read=16752 -> Bitmap Index Scan on idx_test_mes3 (cost=0.00..1369.97 rows=303120 width=0) (actual time=28.165..28.165 rows=300000 loops=1) Index Cond: (mes = 'JUN'::text) Buffers: shared read=822 Planning Time: 0.191 ms Execution Time: 234.656 ms * -- consulta filtrando mes y cantidad * explain (ANALYZE,BUFFERS,TIMING) select sum(cantidad) from test where mes='JUN' and cantidad between 1000 and 40000 Aggregate (cost=9046.67..9046.67 rows=1 width=8) (actual time=174.658..174.659 rows=1 loops=1) Buffers: shared read=8403 -> Bitmap Heap Scan on test (cost=66.81..9040.70 rows=11932 width=4) (actual time=6.184..171.275 rows=11687 loops=1) Recheck Cond: ((mes = 'JUN'::text) AND (cantidad >= 1000) AND (cantidad <= 40000)) Heap Blocks: exact=8368 Buffers: shared read=8403 -> Bitmap Index Scan on idx_test_mes3 (cost=0.00..66.22 rows=11932 width=0) (actual time=4.535..4.535 rows=11687 loops=1) Index Cond: ((mes = 'JUN'::text) AND (cantidad >= 1000) AND (cantidad <= 40000)) Buffers: shared read=35 Planning Time: 0.732 ms Execution Time: 174.706 ms *-- tamaños de la tabla e indices creados* SELECT nspname,relname,pg_relation_size(c.oid),pg_size_pretty(pg_relation_size(c.oid)) as "size" from pg_class c left join pg_namespace n on ( n.oid=c.relnamespace) where nspname not in ('pg_catalog','information_schema') and relname ilike '%test%' order by pg_relation_size(c.oid) desc; nspname;relname; pg_relation_size;size public;test;130498560;124 MB public;idx_test_mes;80887808;77 MB public;idx_test_mes2;80887808;77 MB public;idx_test_mes3;80887808;77 MB *La pregunta es, en qué situaciones se debe emplear o se justifica un include versus, por ejemplo, un índice compuesto? de antemano gracias* -- Cordialmente, Ing. Hellmuth I. Vargas S.