Nat*_*ner 5 postgresql cte postgresql-9.5
我正在 PostgreSQL 9.5 中处理从两个视图中提取的 SQL 查询。单独来看，这些视图需要 93 毫秒和 530 毫秒来执行，分别产生 ~1500 和 ~6200 行。鉴于处理进入视图，这似乎是合理的，其中包括与 PostGIS 的一些空间交叉点。但是，当我执行下面的查询时，大约需要 5 秒才能执行。
据我所知， usingWITH应该强制子查询在下面的查询中的评估之前执行一次，这应该导致总时间不到一秒而不是五秒。
如果我通过 ODBC/MS Access 链接到两个视图并使用 MS Access 在没有 的情况下执行查询WITH，它会在不到一秒的时间内执行。这让我认为，当我在 pgAdmin 中执行子查询时，在加入之前不会每次都执行一次。
视图中没有其他 CTE，只有子查询。
有没有更好的方法来做到这一点，或者强制执行顺序的黑客？
WITH
eu AS (
SELECT
e.sample_pk,
.....
FROM
public.samples_exp_unit AS e
),
sr AS (
SELECT
r.sample_pk,
.....
FROM
public.sample_results AS r
)
SELECT
sr.sample_pk,
eu.inventory_pk,
.....
FROM sr INNER JOIN eu
ON sr.sample_pk = eu.sample_pk
全查询的执行计划：
"Hash Join (cost=963.49..1007.02 rows=9 width=120) (actual time=40.508..54.209 rows=45392 loops=1)"
" Hash Cond: (sr.sample_pk = eu.sample_pk)"
" CTE eu"
" -> Nested Loop (cost=41.81..50.67 rows=1 width=24) (actual time=1.296..8.307 rows=1538 loops=1)"
" Join Filter: (lil.locations_pk = l.locations_pk)"
" -> Nested Loop (cost=41.67..48.22 rows=1 width=28) (actual time=1.289..6.582 rows=1538 loops=1)"
" -> Nested Loop (cost=41.53..47.92 rows=1 width=32) (actual time=1.283..4.852 rows=1538 loops=1)"
" -> Hash Join (cost=41.38..47.66 rows=1 width=28) (actual time=1.275..3.079 rows=1480 loops=1)"
" Hash Cond: (lil.locations_pk = eu_1.locations_pk)"
" Join Filter: ((((sd.sample_depth_bottom)::double precision - eu_1.poc_top) > '-0.0001'::double precision) AND ((eu_1.poc_bottom - (sd.sample_depth_top)::double precision) > '-0.0001'::double precision))"
" Rows Removed by Join Filter: 371"
" -> Hash Join (cost=40.23..46.36 rows=5 width=29) (actual time=1.252..1.402 rows=610 loops=1)"
" Hash Cond: (sd.inventory_pk = i.inventory_pk)"
" -> Seq Scan on sample_description sd (cost=0.00..5.25 rows=225 width=17) (actual time=0.004..0.049 rows=225 loops=1)"
" -> Hash (cost=40.19..40.19 rows=3 width=16) (actual time=1.245..1.245 rows=418 loops=1)"
" Buckets: 1024 Batches: 1 Memory Usage: 28kB"
" -> Hash Join (cost=35.92..40.19 rows=3 width=16) (actual time=1.109..1.194 rows=418 loops=1)"
" Hash Cond: (i.inv_loc_pk = lil.inv_loc_pk)"
" -> Seq Scan on inv i (cost=0.00..3.63 rows=163 width=8) (actual time=0.004..0.025 rows=163 loops=1)"
" -> Hash (cost=35.88..35.88 rows=3 width=8) (actual time=1.102..1.102 rows=390 loops=1)"
" Buckets: 1024 Batches: 1 Memory Usage: 24kB"
" -> Subquery Scan on lil (cost=35.82..35.88 rows=3 width=8) (actual time=1.002..1.056 rows=390 loops=1)"
" -> HashAggregate (cost=35.82..35.85 rows=3 width=8) (actual time=1.001..1.037 rows=390 loops=1)"
" Group Key: "*SELECT* 1".locations_pk, "*SELECT* 1".inv_loc_pk"
" -> Append (cost=0.14..35.81 rows=3 width=8) (actual time=0.876..0.929 rows=390 loops=1)"
" -> Result (cost=0.14..34.78 rows=2 width=8) (actual time=0.876..0.918 rows=389 loops=1)"
" -> HashSetOp Except (cost=0.14..34.78 rows=2 width=8) (actual time=0.876..0.892 rows=389 loops=1)"
" -> Append (cost=0.14..34.77 rows=3 width=8) (actual time=0.028..0.800 rows=389 loops=1)"
" -> Subquery Scan on "*SELECT* 1" (cost=0.14..33.75 rows=2 width=8) (actual time=0.028..0.785 rows=389 loops=1)"
" -> Nested Loop (cost=0.14..33.73 rows=2 width=8) (actual time=0.026..0.759 rows=389 loops=1)"
" -> Seq Scan on locations l_1 (cost=0.00..2.37 rows=37 width=36) (actual time=0.003..0.012 rows=38 loops=1)"
" -> Index Scan using sidx_inv_loc_geom on inv_loc i_1 (cost=0.14..0.84 rows=1 width=36) (actual time=0.008..0.018 rows=10 loops=38)"
" Index Cond: (geom && l_1.geom)"
" Filter: _st_intersects(geom, l_1.geom)"
" Rows Removed by Filter: 0"
" -> Subquery Scan on "*SELECT* 2" (cost=0.00..1.02 rows=1 width=8) (actual time=0.003..0.003 rows=0 loops=1)"
" -> Seq Scan on loc_inv_adjust a (cost=0.00..1.01 rows=1 width=8) (actual time=0.003..0.003 rows=0 loops=1)"
" Filter: (include = 0)"
" Rows Removed by Filter: 1"
" -> Seq Scan on loc_inv_adjust b (cost=0.00..1.01 rows=1 width=8) (actual time=0.002..0.002 rows=1 loops=1)"
" Filter: (include = 1)"
" -> Hash (cost=1.07..1.07 rows=7 width=24) (actual time=0.009..0.009 rows=11 loops=1)"
" Buckets: 1024 Batches: 1 Memory Usage: 9kB"
" -> Seq Scan on exp_unit eu_1 (cost=0.00..1.07 rows=7 width=24) (actual time=0.004..0.006 rows=11 loops=1)"
" -> Index Scan using bysampledescription on sample s (cost=0.14..0.25 rows=1 width=8) (actual time=0.001..0.001 rows=1 loops=1480)"
" Index Cond: (sample_description_pk = sd.sample_description_pk)"
" -> Index Only Scan using inv_loc_pkey on inv_loc il (cost=0.14..0.29 rows=1 width=4) (actual time=0.001..0.001 rows=1 loops=1538)"
" Index Cond: (inv_loc_pk = i.inv_loc_pk)"
" Heap Fetches: 1538"
" -> Index Only Scan using pk_locations on locations l (cost=0.14..2.44 rows=1 width=4) (actual time=0.001..0.001 rows=1 loops=1538)"
" Index Cond: (locations_pk = eu_1.locations_pk)"
" Heap Fetches: 1538"
" CTE sr"
" -> WindowAgg (cost=848.77..894.49 rows=1829 width=92) (actual time=31.316..35.704 rows=6234 loops=1)"
" -> Sort (cost=848.77..853.34 rows=1829 width=92) (actual time=31.312..31.621 rows=6234 loops=1)"
" Sort Key: sub_query_union.sample_pk, sub_query_union.analyte_pk, sub_query_union.type_priority, sub_query_union.num_priority"
" Sort Method: quicksort Memory: 1069kB"
" -> Subquery Scan on sub_query_union (cost=713.08..749.66 rows=1829 width=92) (actual time=26.511..28.164 rows=6234 loops=1)"
" -> HashAggregate (cost=713.08..731.37 rows=1829 width=106) (actual time=26.510..27.750 rows=6234 loops=1)"
" Group Key: "*SELECT* 1_1".sample_pk, "*SELECT* 1_1".analyte_pk, "*SELECT* 1_1".results_pk, (1), "*SELECT* 1_1".result, "*SELECT* 1_1".units_pk, (NULL::double precision), (NULL::double precision), ('Rep_Conc'::character varying), (...)"
" -> Append (cost=46.85..658.21 rows=1829 width=106) (actual time=3.748..22.017 rows=6234 loops=1)"
" -> Subquery Scan on "*SELECT* 1_1" (cost=46.85..62.83 rows=1 width=24) (actual time=3.748..5.539 rows=134 loops=1)"
" -> Nested Loop (cost=46.85..62.82 rows=1 width=24) (actual time=3.746..5.485 rows=134 loops=1)"
" Join Filter: (lil_1.locations_pk = l_2.locations_pk)"
" -> Nested Loop (cost=46.71..62.60 rows=1 width=32) (actual time=3.736..4.981 rows=134 loops=1)"
" -> Nested Loop (cost=46.57..62.31 rows=1 width=40) (actual time=3.727..4.584 rows=134 loops=1)"
" -> Hash Join (cost=46.42..62.05 rows=1 width=40) (actual time=3.718..4.177 rows=128 loops=1)"
" Hash Cond: (rc.locations_pk = lil_1.locations_pk)"
" Join Filter: ((((sd_1.sample_depth_bottom)::double precision - rc.depth_top) > '-0.0001'::double precision) AND ((rc.depth_bottom - (sd_1.sample_depth_top)::double precision) > '-0.0001'::doub (...)"
" Rows Removed by Join Filter: 94"
" -> Seq Scan on rep_conc rc (cost=0.00..13.60 rows=360 width=40) (actual time=0.005..0.006 rows=1 loops=1)"
" -> Hash (cost=46.36..46.36 rows=5 width=25) (actual time=3.683..3.683 rows=610 loops=1)"
" Buckets: 1024 Batches: 1 Memory Usage: 43kB"
" -> Hash Join (cost=40.23..46.36 rows=5 width=25) (actual time=3.124..3.444 rows=610 loops=1)"
" Hash Cond: (sd_1.inventory_pk = i_2.inventory_pk)"
" -> Seq Scan on sample_description sd_1 (cost=0.00..5.25 rows=225 width=17) (actual time=0.006..0.093 rows=225 loops=1)"
" -> Hash (cost=40.19..40.19 rows=3 width=16) (actual time=3.111..3.111 rows=418 loops=1)"
" Buckets: 1024 Batches: 1 Memory Usage: 28kB"
" -> Hash Join (cost=35.92..40.19 rows=3 width=16) (actual time=2.780..2.976 rows=418 loops=1)"
" Hash Cond: (i_2.inv_loc_pk = lil_1.inv_loc_pk)"
" -> Seq Scan on inv i_2 (cost=0.00..3.63 rows=163 width=8) (actual time=0.007..0.059 rows=163 loops=1)"
" -> Hash (cost=35.88..35.88 rows=3 width=8) (actual time=2.761..2.761 rows=390 loops=1)"
" Buckets: 1024 Batches: 1 Memory Usage: 24kB"
" -> Subquery Scan on lil_1 (cost=35.82..35.88 rows=3 width=8) (actual time=2.522..2.651 rows=390 loops=1)"
" -> HashAggregate (cost=35.82..35.85 rows=3 width=8) (actual time=2.522..2.600 rows=390 loops=1)"
" Group Key: "*SELECT* 1_2".locations_pk, "*SELECT* 1_2".inv_loc_pk"
" -> Append (cost=0.14..35.81 rows=3 width=8) (actual time=2.207..2.334 rows=390 loops=1)"
" -> Result (cost=0.14..34.78 rows=2 width=8) (actual time=2.207..2.304 rows=389 loops=1)"
" -> HashSetOp Except (cost=0.14..34.78 rows=2 width=8) (actual time=2.206..2.244 rows=389 loops=1)"
" -> Append (cost=0.14..34.77 rows=3 width=8) (actual time=0.048..1.986 rows=389 loops=1)"
" -> Subquery Scan on "*SELECT* 1_2" (cost=0.14..33.75 rows=2 width=8) (actual time=0.048..1.954 rows=389 loops=1)"
" -> Nested Loop (cost=0.14..33.73 rows=2 width=8) (actual time=0.047..1.889 rows=389 loops=1)"
" -> Seq Scan on locations l_3 (cost=0.00..2.37 rows=37 width=36) (actual time=0.005..0.020 rows=38 loops=1)"
" -> Index Scan using sidx_inv_loc_geom on inv_loc i_3 (cost=0.14..0.84 rows=1 width=36) (actual time=0.019..0.046 (...)"
" Index Cond: (geom && l_3.geom)"
" Filter: _st_intersects(geom, l_3.geom)"
" Rows Removed by Filter: 0"
" -> Subquery Scan on "*SELECT* 2_2" (cost=0.00..1.02 rows=1 width=8) (actual time=0.005..0.005 rows=0 loops=1)"
" -> Seq Scan on loc_inv_adjust a_1 (cost=0.00..1.01 rows=1 width=8) (actual time=0.005..0.005 rows=0 loops=1)"
" Filter: (include = 0)"
" Rows Removed by Filter: 1"
" -> Seq Scan on loc_inv_adjust b_1 (cost=0.00..1.01 rows=1 width=8) (actual time=0.002..0.003 rows=1 loops=1)"
" Filter: (include = 1)"
" -> Index Scan using bysampledescription on sample s_1 (cost=0.14..0.25 rows=1 width=8) (actual time=0.002..0.002 rows=1 loops=128)"
" Index Cond: (sample_description_pk = sd_1.sample_description_pk)"
" -> Index Only Scan using inv_loc_pkey on inv_loc il_1 (cost=0.14..0.29 rows=1 width=4) (actual time=0.002..0.002 rows=1 loops=134)"
" Index Cond: (inv_loc_pk = i_2.inv_loc_pk)"
" Heap Fetches: 134"
" -> Index Only Scan using pk_locations on locations l_2 (cost=0.14..0.20 rows=1 width=4) (actual time=0.002..0.002 rows=1 loops=134)"
" Index Cond: (locations_pk = rc.locations_pk)"
" Heap Fetches: 134"
" -> Subquery Scan on "*SELECT* 2_1" (cost=266.84..296.55 rows=914 width=106) (actual time=3.855..7.460 rows=1862 loops=1)"
" -> WindowAgg (cost=266.84..287.41 rows=914 width=106) (actual time=3.853..7.089 rows=1862 loops=1)"
" -> Sort (cost=266.84..269.13 rows=914 width=106) (actual time=3.844..3.959 rows=1862 loops=1)"
" Sort Key: ar.sample_pk, ar.analyte_pk, ar.result DESC"
" Sort Method: quicksort Memory: 196kB"
" -> Nested Loop (cost=44.81..221.89 rows=914 width=106) (actual time=0.309..2.041 rows=1862 loops=1)"
" -> Seq Scan on detected d (cost=0.00..1.09 rows=1 width=8) (actual time=0.004..0.007 rows=3 loops=1)"
" Filter: (detected_yn = 1)"
" Rows Removed by Filter: 4"
" -> Bitmap Heap Scan on analytical_results ar (cost=44.81..199.48 rows=2133 width=106) (actual time=0.103..0.573 rows=621 loops=3)"
" Recheck Cond: (detected_pk = d.detected_pk)"
" Heap Blocks: exact=127"
" -> Bitmap Index Scan on by_detected (cost=0.00..44.28 rows=2133 width=0) (actual time=0.088..0.088 rows=665 loops=3)"
" Index Cond: (detected_pk = d.detected_pk)"
" -> Subquery Scan on "*SELECT* 3" (cost=266.84..298.83 rows=914 width=106) (actual time=5.384..8.761 rows=4238 loops=1)"
" -> WindowAgg (cost=266.84..289.69 rows=914 width=106) (actual time=5.384..8.425 rows=4238 loops=1)"
" -> Sort (cost=266.84..269.13 rows=914 width=106) (actual time=5.379..5.477 rows=4238 loops=1)"
" Sort Key: ar_1.sample_pk, ar_1.analyte_pk, ar_1.reporting_limit, ar_1.method_detection_limit"
" Sort Method: quicksort Memory: 524kB"
"
由于public.samples_exp_unit和public.sample_results是视图，因此您在查询中添加了一个间接级别。
您可以重写为更简单：
WITH
eu AS (TABLE public.samples_exp_unit),
sr AS (TABLE public.sample_results)
SELECT
sr.sample_pk,
eu.inventory_pk,
.....
FROM sr INNER JOIN eu
ON sr.sample_pk = eu.sample_pk ;
并测试这是否会改变计划并提高效率。
要测试的另一件事是避免 CTE。特别是因为它们是优化栅栏，它们有时会导致效率较低的计划（有时会导致效率更高的计划！）在没有 CTE 的情况下重写和测试：
SELECT
sr.sample_pk,
eu.inventory_pk,
.....
FROM public.sample_results AS sr
INNER JOIN
public.samples_exp_unit AS eu
ON sr.sample_pk = eu.sample_pk ;
还可以通过 psql 尝试查询。它将显示 PgAdmin 是否是问题所在。
可能是 pgAdmin 需要很长时间来呈现查询结果，或者正在通过慢速网络进行通信，因此需要很长时间才能获取结果。也有可能 pgAdmin 正在做一些改变执行计划的事情，比如默默地将一些参数设置为非默认值，或者在执行前将查询准备到游标中。