我在同一网络的不同计算机（X和Y）上有2个postgresql示例。Y服务器上安装了PgAdmin，并连接到两个示例。
在Y示例上，我为X上的数据库创建了FDW连接。
我的问题是当我在外部表上运行选择查询时，它花了30多秒。如果我从PgAdmin直接向X服务器运行相同的查询，只需不到1秒的时间，我认为性能低下的原因可能不是网络问题。
我用on和off对use_remote_estimate都试过了，但是由于我的外键表不断更新新数据，我决定保留它off。
我的查询如下

SELECT q_num,
    count(*)::integer AS total_calls,
    count(1) FILTER (WHERE na_code = 0 AND fail_code = 0)::integer AS answered,
    count(1) FILTER (WHERE na_code = 0 AND fail_code = 0 AND (wait + poll) <= '00:00:15'::interval)::integer AS answered_15,
    count(1) FILTER (WHERE na_code = 0 AND fail_code = 0 AND (wait + poll) <= '00:00:20'::interval)::integer AS answered_20,
    count(1) FILTER (WHERE na_code = 0 AND fail_code = 0 AND (wait + poll) <= '00:00:30'::interval)::integer AS answered_30,
    count(1) FILTER (WHERE na_code <> 0 OR fail_code <> 0)::integer AS missed,
    count(1) FILTER (WHERE na_code <> 0 OR fail_code <> 0 AND (wait + poll) > '00:00:15'::interval)::integer AS missed_15,
    count(1) FILTER (WHERE na_code <> 0 OR fail_code <> 0 AND (wait + poll) > '00:00:20'::interval)::integer AS missed_20,
    count(1) FILTER (WHERE na_code <> 0 OR fail_code <> 0 AND (wait + poll) > '00:00:30'::interval)::integer AS missed_30,
    EXTRACT(epoch FROM sum(wait + poll))::integer AS total_waiting,
    EXTRACT(epoch FROM max(wait + poll))::integer AS max_waiting
FROM foreign_table
WHERE time_start > (CURRENT_TIMESTAMP - '03:15:00'::interval)
GROUP BY q_num

字符串
time_start列在远程服务器上具有索引。
如何提高性能？
EDIT：尝试增加fetch_size，但仍需要20秒以上。
@弗兰克·海肯斯这是索引

CREATE INDEX IF NOT EXISTS original_table_time_start_idx
    ON public.original_table USING btree
    (time_start ASC NULLS LAST)
    TABLESPACE pg_default;

型
X示例上的Postgresql版本
PostgreSQL 11.9，由Visual C内部版本号1914编译，64位
Y示例上的Postgresql版本
PostgreSQL 14.5，由Visual C编译，内部版本号1914，64位
X示例上的EXPLAIN（分析、动词、缓冲区）

GroupAggregate  (cost=8.51..8.91 rows=2 width=49) (actual time=0.148..0.150 rows=1 loops=1)    
Output: q_num, (count(*))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0))))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0) AND ((wait + poll) <= '00:00:15'::interval))))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0) AND ((wait + poll) <= '00:00:20'::interval))))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0) AND ((wait + poll) <= '00:00:30'::interval))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR (fail_code <> 0))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR ((fail_code <> 0) AND ((wait + poll) > '00:00:15'::interval)))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR ((fail_code <> 0) AND ((wait + poll) > '00:00:20'::interval)))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR ((fail_code <> 0) AND ((wait + poll) > '00:00:30'::interval)))))::integer, (date_part('epoch'::text, sum((wait + poll))))::integer, (date_part('epoch'::text, max((wait + poll))))::integer
Group Key: original_table.q_num    
Buffers: shared hit=4   
->  Sort (cost=8.51..8.51 rows=3 width=45) (actual time=0.099..0.101 rows=3 loops=1) 
Output: q_num, na_code, fail_code, wait, poll 
Sort Key: original_table.q_num 
Sort Method: quicksort  
Memory: 25kB 
Buffers: shared hit=4
->  Index Scan using original_table_time_start_idx on public.original_table  (cost=0.43..8.48 rows=3 width=45) (actual time=0.052..0.060 rows=3 loops=1) 
Output: q_num, na_code, fail_code, wait, poll 
Index Cond: (original_table.time_start > (CURRENT_TIMESTAMP - '00:15:00'::interval)) 
Buffers: shared hit=4 
Planning Time: 1.383 ms 
Execution Time: 0.638 ms

型
Y示例上的EXPLAIN（分析、动词、缓冲区）

GroupAggregate  (cost=48287.41..48295.41 rows=6 width=49) (actual time=22846.842..22846.847 rows=1 loops=1)   
Output: q_num, (count(*))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0))))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0) AND ((wait + poll) <= '00:00:15'::interval))))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0) AND ((wait + poll) <= '00:00:20'::interval))))::integer, (count(1) FILTER (WHERE ((na_code = 0) AND (fail_code = 0) AND ((wait + poll) <= '00:00:30'::interval))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR (fail_code <> 0))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR ((fail_code <> 0) AND ((wait + poll) > '00:00:15'::interval)))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR ((fail_code <> 0) AND ((wait + poll) > '00:00:20'::interval)))))::integer, (count(1) FILTER (WHERE ((na_code <> 0) OR ((fail_code <> 0) AND ((wait + poll) > '00:00:30'::interval)))))::integer, (EXTRACT(epoch FROM sum((wait + poll))))::integer, (EXTRACT(epoch FROM max((wait + poll))))::integer
Group Key: foreign_table.q_num   
->  Sort  (cost=48287.41..48287.59 rows=72 width=45) (actual time=22846.755..22846.759 rows=1 loops=1)
Output: q_num, na_code, fail_code, wait, poll
Sort Key: foreign_table.q_num
Sort Method: quicksort  
Memory: 25kB
->  Foreign Scan on public.foreign_table  (cost=100.00..48285.19 rows=72 width=45) (actual time=10927.554..22846.717 rows=1 loops=1)
Output: q_num, na_code, fail_code, wait, poll
Filter: (foreign_table.time_start > (CURRENT_TIMESTAMP - '03:15:00'::interval))
Rows Removed by Filter: 720077
Remote SQL: SELECT q_num, time_start, wait, poll, na_code, fail_code FROM public.original_table 
Planning Time: 0.522 ms 
Execution Time: 22849.716 ms

型
我希望这些信息能有所帮助。