Saludos, en tu caso de ejemplo computacionalmente (depende del
hardware) 300mil registros el motor da el mismo tiempo de resultados usando
índices o búsqueda secuencial con filtros,
Cuando los registros superen los millones vas a ver la diferencia en el
tiempo usando los índices compuestos o usando el filtro.
*La pregunta es, en qué situaciones se debe emplear o se justifica un
include versus, por ejemplo, un índice compuesto? de antemano gracias*
Es un proceso de continuo análisis, si al hacer un explain vez que el
filter dura mucho tiempo de lo esperado entonces crear un índice compuesto.
El mar., 23 jun. 2020 a las 11:54, Hellmuth Vargas (<hiv...@gmail.com>)
escribió:
> Hola Diego
>
> Gracias por la respuesta, pero.. y qué ventaja tendria? pues lo mismo se
> logra con un índice compuesto e incluso este último permitirá filtrar
> además por el otro campo, e incluso el optimizador prefirió el índice
> compuesto.
>
> El mar., 23 de jun. de 2020 a la(s) 10:41, Diego (mrstephenam...@gmail.com)
> escribió:
>
>> HOla, Hellmuth / lista
>>
>> Lo que pasa es que lo que esta en el include, no se indexa.
>>
>> Es la forma de no salir del indice para buscar ese valor en particular,
>> ahorrando el pase por la tabla
>>
>> Salu2
>> On 2020-06-23 12:03, Hellmuth Vargas wrote:
>>
>> *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.
>>
>>
>
> --
> Cordialmente,
>
> Ing. Hellmuth I. Vargas S.
> Esp. Telemática y Negocios por Internet
> Oracle Database 10g Administrator Certified Associate
> EnterpriseDB Certified PostgreSQL 9.3 Associate
>
>
