参数 postgres 的不同值查询速度较慢
Query Slower with different value for a parameter postgress
我遇到了休眠在现有视图上生成以下查询的问题。
select
count(proclistvw0_.proc_id) as col_0_0_
from proc_list_vw proclistvw0_
where 1=1
and ( proclistvw0_.sub_group_edp_company =
or
proclistvw0_.sub_group_edp_company =
)
and (proclistvw0_.proc_country in ())
and proclistvw0_.sub_group_edp_company =
;
将参数 1、2 和 4 保持为常量，仅更改 3 来自
'ESP' 到 'BRA'
查询将 return 几乎相同数量的结果，但这样做的时间将从 3 秒增加到 5 分钟
对于慢速查询，我无法理解的一件事是，出于某种原因，它似乎在 7 秒内完成了所有工作，但它在其余时间挂起。
这里是慢查询的分析计划
Aggregate (cost=165310.40..165310.41 rows=1 width=8) (actual time=379605.458..379605.486 rows=1 loops=1)
-> Nested Loop (cost=10712.71..165310.40 rows=1 width=4) (actual time=2385.256..379605.125 rows=146 loops=1)
-> Nested Loop (cost=10712.56..165310.24 rows=1 width=8) (actual time=2385.225..379603.816 rows=146 loops=1)
-> Nested Loop (cost=10712.29..165309.94 rows=1 width=13) (actual time=2385.178..379600.458 rows=146 loops=1)
Join Filter: (pp.id = pqr.proc_id)
Rows Removed by Join Filter: 32081164
-> Nested Loop Left Join (cost=10711.28..19598.32 rows=1 width=8) (actual time=308.508..7085.120 rows=146 loops=1)
Join Filter: (pp.id = d.proc_id)
Rows Removed by Join Filter: 394052
-> Hash Join (cost=10710.10..15633.72 rows=1 width=8) (actual time=262.425..350.010 rows=146 loops=1)
Hash Cond: (t4cp_1.proc_id = pp.id)
-> HashAggregate (cost=10696.18..12872.36 rows=217618 width=36) (actual time=262.094..333.606 rows=219734 loops=1)
Group Key: t4cp_1.proc_id
Batches: 1 Memory Usage: 28689kB
-> Hash Right Join (cost=6055.89..10131.17 rows=226002 width=4) (actual time=45.110..178.231 rows=261886 loops=1)
Hash Cond: (t4cp_1.per_id = t4.id)
-> Seq Scan on process_person t4cp_1 (cost=0.00..3482.02 rows=226002 width=8) (actual time=0.012..15.687 rows=226012 loops=1)
-> Hash (cost=3579.72..3579.72 rows=198093 width=4) (actual time=44.427..44.428 rows=198124 loops=1)
Buckets: 262144 Batches: 1 Memory Usage: 9014kB
-> Index Only Scan using person_id_index1 on person t4 (cost=0.42..3579.72 rows=198093 width=4) (actual time=0.011..15.006 rows=198124 loops=1)
Heap Fetches: 448
-> Hash (cost=13.91..13.91 rows=1 width=4) (actual time=0.276..0.279 rows=146 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 14kB
-> Bitmap Heap Scan on process pp (cost=12.79..13.91 rows=1 width=4) (actual time=0.125..0.258 rows=146 loops=1)
Recheck Cond: (((country_cd)::text = 'BRA'::text) AND ((sub_group_edp_company_cd)::text = 'EDPR'::text))
" Filter: ((COALESCE(status_cd, ' '::character varying))::text <> 'CANCELLED'::text)"
Rows Removed by Filter: 26
Heap Blocks: exact=107
-> BitmapAnd (cost=12.79..12.79 rows=1 width=0) (actual time=0.111..0.113 rows=0 loops=1)
-> Bitmap Index Scan on process_country_cd_index1 (cost=0.00..2.75 rows=180 width=0) (actual time=0.023..0.023 rows=172 loops=1)
Index Cond: ((country_cd)::text = 'BRA'::text)
-> Bitmap Index Scan on process_sub_group_edp_company_cd_index1 (cost=0.00..9.79 rows=1120 width=0) (actual time=0.084..0.084 rows=1121 loops=1)
Index Cond: ((sub_group_edp_company_cd)::text = 'EDPR'::text)
-> Subquery Scan on d (cost=1.18..3962.26 rows=187 width=4) (actual time=0.077..45.913 rows=2699 loops=146)
Filter: (d.seq = 1)
Rows Removed by Filter: 34680
-> WindowAgg (cost=1.18..3495.04 rows=37378 width=379) (actual time=0.076..43.617 rows=37379 loops=146)
-> Incremental Sort (cost=1.18..2654.03 rows=37378 width=17) (actual time=0.073..19.633 rows=37379 loops=146)
" Sort Key: tb.proc_id, tb.period_year DESC, tb.period_id DESC"
Presorted Key: tb.proc_id
Full-sort Groups: 132568 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
-> Index Only Scan using total_balance_idx_2 on total_balance tb (cost=0.41..864.58 rows=37378 width=17) (actual time=0.018..5.726 rows=37379 loops=146)
Index Cond: (risk_type = 'PROB'::text)
Heap Fetches: 2190
-> Subquery Scan on pqr (cost=1.01..145648.77 rows=5028 width=13) (actual time=0.096..2534.723 rows=219735 loops=146)
Filter: (pqr.seq = 1)
Rows Removed by Filter: 786096
-> WindowAgg (cost=1.01..133078.51 rows=1005621 width=5109) (actual time=0.096..2466.654 rows=1005831 loops=146)
-> Incremental Sort (cost=1.01..112966.09 rows=1005621 width=25) (actual time=0.092..1305.446 rows=1005831 loops=146)
" Sort Key: qualitative_record.proc_id, qualitative_record.value_date DESC, qualitative_record.cre_dt DESC"
Presorted Key: qualitative_record.proc_id
Full-sort Groups: 4159102 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
Pre-sorted Groups: 30514 Sort Method: quicksort Average Memory: 25kB Peak Memory: 25kB
-> Index Scan using idx_pqr_proc_id on qualitative_record (cost=0.42..71733.43 rows=1005621 width=25) (actual time=0.014..1063.333 rows=1005831 loops=146)
" -> Index Only Scan using ""COMPANY_EDP_pkey"" on company_edp c (cost=0.28..0.30 rows=1 width=7) (actual time=0.015..0.015 rows=1 loops=146)"
Index Cond: (code = (pqr.comp_code)::text)
Heap Fetches: 0
-> Index Only Scan using stakeholder_id_index1 on stakeholder sh (cost=0.15..0.17 rows=1 width=4) (actual time=0.005..0.005 rows=1 loops=146)
" Index Cond: (id = COALESCE(pqr.stkh_resp, 0))"
Heap Fetches: 146
Planning Time: 3.656 ms
Execution Time: 379609.145 ms
快速查询分析
Aggregate (cost=165595.31..165595.32 rows=1 width=8) (actual time=2896.812..2896.821 rows=1 loops=1)
-> Nested Loop (cost=15971.78..165595.31 rows=3 width=4) (actual time=1501.960..2896.729 rows=160 loops=1)
-> Nested Loop (cost=15971.63..165594.81 rows=3 width=8) (actual time=1501.922..2896.228 rows=160 loops=1)
-> Merge Right Join (cost=15971.35..165593.92 rows=3 width=13) (actual time=1501.876..2895.188 rows=160 loops=1)
Merge Cond: (d.proc_id = pp.id)
-> Subquery Scan on d (cost=1.18..3962.26 rows=187 width=4) (actual time=0.076..48.049 rows=2693 loops=1)
Filter: (d.seq = 1)
Rows Removed by Filter: 34680
-> WindowAgg (cost=1.18..3495.04 rows=37378 width=379) (actual time=0.075..45.719 rows=37373 loops=1)
-> Incremental Sort (cost=1.18..2654.03 rows=37378 width=17) (actual time=0.064..21.045 rows=37374 loops=1)
" Sort Key: tb.proc_id, tb.period_year DESC, tb.period_id DESC"
Presorted Key: tb.proc_id
Full-sort Groups: 907 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
-> Index Only Scan using total_balance_idx_2 on total_balance tb (cost=0.41..864.58 rows=37378 width=17) (actual time=0.027..5.981 rows=37378 loops=1)
Index Cond: (risk_type = 'PROB'::text)
Heap Fetches: 14
-> Materialize (cost=15970.18..161631.17 rows=3 width=17) (actual time=1482.552..2846.829 rows=160 loops=1)
-> Merge Join (cost=15970.18..161631.17 rows=3 width=17) (actual time=1482.551..2846.750 rows=160 loops=1)
Merge Cond: (pqr.proc_id = pp.id)
-> Subquery Scan on pqr (cost=1.01..145648.77 rows=5028 width=13) (actual time=0.111..2496.949 rows=219605 loops=1)
Filter: (pqr.seq = 1)
Rows Removed by Filter: 785840
-> WindowAgg (cost=1.01..133078.51 rows=1005621 width=5109) (actual time=0.110..2427.881 rows=1005445 loops=1)
-> Incremental Sort (cost=1.01..112966.09 rows=1005621 width=25) (actual time=0.101..1265.385 rows=1005446 loops=1)
" Sort Key: qualitative_record.proc_id, qualitative_record.value_date DESC, qualitative_record.cre_dt DESC"
Presorted Key: qualitative_record.proc_id
Full-sort Groups: 28476 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
Pre-sorted Groups: 209 Sort Method: quicksort Average Memory: 25kB Peak Memory: 25kB
-> Index Scan using idx_pqr_proc_id on qualitative_record (cost=0.42..71733.43 rows=1005621 width=25) (actual time=0.015..1019.817 rows=1005471 loops=1)
-> Sort (cost=15969.17..15969.48 rows=126 width=8) (actual time=337.498..337.561 rows=160 loops=1)
Sort Key: pp.id
Sort Method: quicksort Memory: 32kB
-> Hash Join (cost=11041.15..15964.77 rows=126 width=8) (actual time=270.708..337.422 rows=160 loops=1)
Hash Cond: (t4cp_1.proc_id = pp.id)
-> HashAggregate (cost=10696.18..12872.36 rows=217618 width=36) (actual time=269.564..323.144 rows=219734 loops=1)
Group Key: t4cp_1.proc_id
Batches: 1 Memory Usage: 28689kB
-> Hash Right Join (cost=6055.89..10131.17 rows=226002 width=4) (actual time=54.069..184.369 rows=261886 loops=1)
Hash Cond: (t4cp_1.per_id = t4.id)
-> Seq Scan on process_person t4cp_1 (cost=0.00..3482.02 rows=226002 width=8) (actual time=0.011..15.682 rows=226012 loops=1)
-> Hash (cost=3579.72..3579.72 rows=198093 width=4) (actual time=53.309..53.310 rows=198124 loops=1)
Buckets: 262144 Batches: 1 Memory Usage: 9014kB
-> Index Only Scan using person_id_index1 on person t4 (cost=0.42..3579.72 rows=198093 width=4) (actual time=0.016..17.161 rows=198124 loops=1)
Heap Fetches: 448
-> Hash (cost=343.39..343.39 rows=127 width=4) (actual time=0.889..0.890 rows=160 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 14kB
-> Index Scan using process_sub_group_edp_company_cd_index1 on process pp (cost=0.29..343.39 rows=127 width=4) (actual time=0.027..0.865 rows=160 loops=1)
Index Cond: ((sub_group_edp_company_cd)::text = 'EDPR'::text)
" Filter: (((COALESCE(status_cd, ' '::character varying))::text <> 'CANCELLED'::text) AND ((country_cd)::text = 'ESP'::text))"
Rows Removed by Filter: 960
" -> Index Only Scan using ""COMPANY_EDP_pkey"" on company_edp c (cost=0.28..0.30 rows=1 width=7) (actual time=0.005..0.005 rows=1 loops=160)"
Index Cond: (code = (pqr.comp_code)::text)
Heap Fetches: 0
-> Index Only Scan using stakeholder_id_index1 on stakeholder sh (cost=0.15..0.17 rows=1 width=4) (actual time=0.002..0.002 rows=1 loops=160)
" Index Cond: (id = COALESCE(pqr.stkh_resp, 0))"
Heap Fetches: 160
Planning Time: 3.860 ms
Execution Time: 2900.956 ms
计划者认为country_cd和sub_group_edp_company_cd是独立的，但实际上它们不是，因为几乎所有country_cd = 'BRA'也有sub_group_edp_company_cd = 'EDPR'。所以它认为会有 1 个符合条件的行，而实际上有 146 个。这导致计划中其他地方的选择不当。如果它知道它需要执行 146 次“对 pqr 的子查询扫描”而不是一次，那么它会采取措施使其更快，例如对其进行哈希处理或具体化。
在这两列上创建 multicolumn statistics 可能 足以解决问题。
for some reason it seems to do all the work in 7 seconds but it hangs for the rest of the time.
你误解了这个计划。但是不知道为什么你这么想，我不知道你误会了哪一部分。
只是为了分享我的发现，
最后，在我的例子中，解决方案是在视图中按 id 左连接之前的临时表上的“按 id 排序”。这样，时间稳定在2.500毫秒左右。
希望这对以后的人有所帮助。
我遇到了休眠在现有视图上生成以下查询的问题。
select
count(proclistvw0_.proc_id) as col_0_0_
from proc_list_vw proclistvw0_
where 1=1
and ( proclistvw0_.sub_group_edp_company =
or
proclistvw0_.sub_group_edp_company =
)
and (proclistvw0_.proc_country in ())
and proclistvw0_.sub_group_edp_company =
;
将参数 1、2 和 4 保持为常量，仅更改 3 来自 'ESP' 到 'BRA' 查询将 return 几乎相同数量的结果，但这样做的时间将从 3 秒增加到 5 分钟 对于慢速查询，我无法理解的一件事是，出于某种原因，它似乎在 7 秒内完成了所有工作，但它在其余时间挂起。
这里是慢查询的分析计划
Aggregate (cost=165310.40..165310.41 rows=1 width=8) (actual time=379605.458..379605.486 rows=1 loops=1)
-> Nested Loop (cost=10712.71..165310.40 rows=1 width=4) (actual time=2385.256..379605.125 rows=146 loops=1)
-> Nested Loop (cost=10712.56..165310.24 rows=1 width=8) (actual time=2385.225..379603.816 rows=146 loops=1)
-> Nested Loop (cost=10712.29..165309.94 rows=1 width=13) (actual time=2385.178..379600.458 rows=146 loops=1)
Join Filter: (pp.id = pqr.proc_id)
Rows Removed by Join Filter: 32081164
-> Nested Loop Left Join (cost=10711.28..19598.32 rows=1 width=8) (actual time=308.508..7085.120 rows=146 loops=1)
Join Filter: (pp.id = d.proc_id)
Rows Removed by Join Filter: 394052
-> Hash Join (cost=10710.10..15633.72 rows=1 width=8) (actual time=262.425..350.010 rows=146 loops=1)
Hash Cond: (t4cp_1.proc_id = pp.id)
-> HashAggregate (cost=10696.18..12872.36 rows=217618 width=36) (actual time=262.094..333.606 rows=219734 loops=1)
Group Key: t4cp_1.proc_id
Batches: 1 Memory Usage: 28689kB
-> Hash Right Join (cost=6055.89..10131.17 rows=226002 width=4) (actual time=45.110..178.231 rows=261886 loops=1)
Hash Cond: (t4cp_1.per_id = t4.id)
-> Seq Scan on process_person t4cp_1 (cost=0.00..3482.02 rows=226002 width=8) (actual time=0.012..15.687 rows=226012 loops=1)
-> Hash (cost=3579.72..3579.72 rows=198093 width=4) (actual time=44.427..44.428 rows=198124 loops=1)
Buckets: 262144 Batches: 1 Memory Usage: 9014kB
-> Index Only Scan using person_id_index1 on person t4 (cost=0.42..3579.72 rows=198093 width=4) (actual time=0.011..15.006 rows=198124 loops=1)
Heap Fetches: 448
-> Hash (cost=13.91..13.91 rows=1 width=4) (actual time=0.276..0.279 rows=146 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 14kB
-> Bitmap Heap Scan on process pp (cost=12.79..13.91 rows=1 width=4) (actual time=0.125..0.258 rows=146 loops=1)
Recheck Cond: (((country_cd)::text = 'BRA'::text) AND ((sub_group_edp_company_cd)::text = 'EDPR'::text))
" Filter: ((COALESCE(status_cd, ' '::character varying))::text <> 'CANCELLED'::text)"
Rows Removed by Filter: 26
Heap Blocks: exact=107
-> BitmapAnd (cost=12.79..12.79 rows=1 width=0) (actual time=0.111..0.113 rows=0 loops=1)
-> Bitmap Index Scan on process_country_cd_index1 (cost=0.00..2.75 rows=180 width=0) (actual time=0.023..0.023 rows=172 loops=1)
Index Cond: ((country_cd)::text = 'BRA'::text)
-> Bitmap Index Scan on process_sub_group_edp_company_cd_index1 (cost=0.00..9.79 rows=1120 width=0) (actual time=0.084..0.084 rows=1121 loops=1)
Index Cond: ((sub_group_edp_company_cd)::text = 'EDPR'::text)
-> Subquery Scan on d (cost=1.18..3962.26 rows=187 width=4) (actual time=0.077..45.913 rows=2699 loops=146)
Filter: (d.seq = 1)
Rows Removed by Filter: 34680
-> WindowAgg (cost=1.18..3495.04 rows=37378 width=379) (actual time=0.076..43.617 rows=37379 loops=146)
-> Incremental Sort (cost=1.18..2654.03 rows=37378 width=17) (actual time=0.073..19.633 rows=37379 loops=146)
" Sort Key: tb.proc_id, tb.period_year DESC, tb.period_id DESC"
Presorted Key: tb.proc_id
Full-sort Groups: 132568 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
-> Index Only Scan using total_balance_idx_2 on total_balance tb (cost=0.41..864.58 rows=37378 width=17) (actual time=0.018..5.726 rows=37379 loops=146)
Index Cond: (risk_type = 'PROB'::text)
Heap Fetches: 2190
-> Subquery Scan on pqr (cost=1.01..145648.77 rows=5028 width=13) (actual time=0.096..2534.723 rows=219735 loops=146)
Filter: (pqr.seq = 1)
Rows Removed by Filter: 786096
-> WindowAgg (cost=1.01..133078.51 rows=1005621 width=5109) (actual time=0.096..2466.654 rows=1005831 loops=146)
-> Incremental Sort (cost=1.01..112966.09 rows=1005621 width=25) (actual time=0.092..1305.446 rows=1005831 loops=146)
" Sort Key: qualitative_record.proc_id, qualitative_record.value_date DESC, qualitative_record.cre_dt DESC"
Presorted Key: qualitative_record.proc_id
Full-sort Groups: 4159102 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
Pre-sorted Groups: 30514 Sort Method: quicksort Average Memory: 25kB Peak Memory: 25kB
-> Index Scan using idx_pqr_proc_id on qualitative_record (cost=0.42..71733.43 rows=1005621 width=25) (actual time=0.014..1063.333 rows=1005831 loops=146)
" -> Index Only Scan using ""COMPANY_EDP_pkey"" on company_edp c (cost=0.28..0.30 rows=1 width=7) (actual time=0.015..0.015 rows=1 loops=146)"
Index Cond: (code = (pqr.comp_code)::text)
Heap Fetches: 0
-> Index Only Scan using stakeholder_id_index1 on stakeholder sh (cost=0.15..0.17 rows=1 width=4) (actual time=0.005..0.005 rows=1 loops=146)
" Index Cond: (id = COALESCE(pqr.stkh_resp, 0))"
Heap Fetches: 146
Planning Time: 3.656 ms
Execution Time: 379609.145 ms
快速查询分析
Aggregate (cost=165595.31..165595.32 rows=1 width=8) (actual time=2896.812..2896.821 rows=1 loops=1)
-> Nested Loop (cost=15971.78..165595.31 rows=3 width=4) (actual time=1501.960..2896.729 rows=160 loops=1)
-> Nested Loop (cost=15971.63..165594.81 rows=3 width=8) (actual time=1501.922..2896.228 rows=160 loops=1)
-> Merge Right Join (cost=15971.35..165593.92 rows=3 width=13) (actual time=1501.876..2895.188 rows=160 loops=1)
Merge Cond: (d.proc_id = pp.id)
-> Subquery Scan on d (cost=1.18..3962.26 rows=187 width=4) (actual time=0.076..48.049 rows=2693 loops=1)
Filter: (d.seq = 1)
Rows Removed by Filter: 34680
-> WindowAgg (cost=1.18..3495.04 rows=37378 width=379) (actual time=0.075..45.719 rows=37373 loops=1)
-> Incremental Sort (cost=1.18..2654.03 rows=37378 width=17) (actual time=0.064..21.045 rows=37374 loops=1)
" Sort Key: tb.proc_id, tb.period_year DESC, tb.period_id DESC"
Presorted Key: tb.proc_id
Full-sort Groups: 907 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
-> Index Only Scan using total_balance_idx_2 on total_balance tb (cost=0.41..864.58 rows=37378 width=17) (actual time=0.027..5.981 rows=37378 loops=1)
Index Cond: (risk_type = 'PROB'::text)
Heap Fetches: 14
-> Materialize (cost=15970.18..161631.17 rows=3 width=17) (actual time=1482.552..2846.829 rows=160 loops=1)
-> Merge Join (cost=15970.18..161631.17 rows=3 width=17) (actual time=1482.551..2846.750 rows=160 loops=1)
Merge Cond: (pqr.proc_id = pp.id)
-> Subquery Scan on pqr (cost=1.01..145648.77 rows=5028 width=13) (actual time=0.111..2496.949 rows=219605 loops=1)
Filter: (pqr.seq = 1)
Rows Removed by Filter: 785840
-> WindowAgg (cost=1.01..133078.51 rows=1005621 width=5109) (actual time=0.110..2427.881 rows=1005445 loops=1)
-> Incremental Sort (cost=1.01..112966.09 rows=1005621 width=25) (actual time=0.101..1265.385 rows=1005446 loops=1)
" Sort Key: qualitative_record.proc_id, qualitative_record.value_date DESC, qualitative_record.cre_dt DESC"
Presorted Key: qualitative_record.proc_id
Full-sort Groups: 28476 Sort Method: quicksort Average Memory: 27kB Peak Memory: 27kB
Pre-sorted Groups: 209 Sort Method: quicksort Average Memory: 25kB Peak Memory: 25kB
-> Index Scan using idx_pqr_proc_id on qualitative_record (cost=0.42..71733.43 rows=1005621 width=25) (actual time=0.015..1019.817 rows=1005471 loops=1)
-> Sort (cost=15969.17..15969.48 rows=126 width=8) (actual time=337.498..337.561 rows=160 loops=1)
Sort Key: pp.id
Sort Method: quicksort Memory: 32kB
-> Hash Join (cost=11041.15..15964.77 rows=126 width=8) (actual time=270.708..337.422 rows=160 loops=1)
Hash Cond: (t4cp_1.proc_id = pp.id)
-> HashAggregate (cost=10696.18..12872.36 rows=217618 width=36) (actual time=269.564..323.144 rows=219734 loops=1)
Group Key: t4cp_1.proc_id
Batches: 1 Memory Usage: 28689kB
-> Hash Right Join (cost=6055.89..10131.17 rows=226002 width=4) (actual time=54.069..184.369 rows=261886 loops=1)
Hash Cond: (t4cp_1.per_id = t4.id)
-> Seq Scan on process_person t4cp_1 (cost=0.00..3482.02 rows=226002 width=8) (actual time=0.011..15.682 rows=226012 loops=1)
-> Hash (cost=3579.72..3579.72 rows=198093 width=4) (actual time=53.309..53.310 rows=198124 loops=1)
Buckets: 262144 Batches: 1 Memory Usage: 9014kB
-> Index Only Scan using person_id_index1 on person t4 (cost=0.42..3579.72 rows=198093 width=4) (actual time=0.016..17.161 rows=198124 loops=1)
Heap Fetches: 448
-> Hash (cost=343.39..343.39 rows=127 width=4) (actual time=0.889..0.890 rows=160 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 14kB
-> Index Scan using process_sub_group_edp_company_cd_index1 on process pp (cost=0.29..343.39 rows=127 width=4) (actual time=0.027..0.865 rows=160 loops=1)
Index Cond: ((sub_group_edp_company_cd)::text = 'EDPR'::text)
" Filter: (((COALESCE(status_cd, ' '::character varying))::text <> 'CANCELLED'::text) AND ((country_cd)::text = 'ESP'::text))"
Rows Removed by Filter: 960
" -> Index Only Scan using ""COMPANY_EDP_pkey"" on company_edp c (cost=0.28..0.30 rows=1 width=7) (actual time=0.005..0.005 rows=1 loops=160)"
Index Cond: (code = (pqr.comp_code)::text)
Heap Fetches: 0
-> Index Only Scan using stakeholder_id_index1 on stakeholder sh (cost=0.15..0.17 rows=1 width=4) (actual time=0.002..0.002 rows=1 loops=160)
" Index Cond: (id = COALESCE(pqr.stkh_resp, 0))"
Heap Fetches: 160
Planning Time: 3.860 ms
Execution Time: 2900.956 ms
计划者认为country_cd和sub_group_edp_company_cd是独立的，但实际上它们不是，因为几乎所有country_cd = 'BRA'也有sub_group_edp_company_cd = 'EDPR'。所以它认为会有 1 个符合条件的行，而实际上有 146 个。这导致计划中其他地方的选择不当。如果它知道它需要执行 146 次“对 pqr 的子查询扫描”而不是一次，那么它会采取措施使其更快，例如对其进行哈希处理或具体化。
在这两列上创建 multicolumn statistics 可能 足以解决问题。
for some reason it seems to do all the work in 7 seconds but it hangs for the rest of the time.
你误解了这个计划。但是不知道为什么你这么想，我不知道你误会了哪一部分。
只是为了分享我的发现， 最后，在我的例子中，解决方案是在视图中按 id 左连接之前的临时表上的“按 id 排序”。这样，时间稳定在2.500毫秒左右。
希望这对以后的人有所帮助。