当我遇到性能问题时，我想找到一种方法来优化包含简历的物化视图的全文搜索。任何最佳做法将不胜感激。
我的查询如下：
select
r.id,
r.first_name,
r.last_name
from user.candidates_mv r
where r.ts_resume @@ to_tsquery('simple', 'nurse | doctor')
这大约需要1或2分钟才能运行，重新运行将降至1.5秒。我不太可能依靠缓存，因为tsquery是由正在搜索的最终用户提供的，并且通常是新鲜的。
长tsquery的示例：
'((mechanical <-> design) | (mechanical <-> engineering) | (mechanical <-> engineer) | (development <-> engineer) | (senior <-> design) | (principal <-> design) | (principle <-> design) | (lead <-> design) | (chief <-> design) | (senior <-> mechanical) | (principal <-> mechanical) | (principle <-> mechanical) | (chief <-> mechanical) | (lead <-> mechanical) | (product <-> design) | (senior <-> product) | (principal <-> product) | (principle <-> product) | (lead <-> product) | (chief <-> product)) & ((solidworks) | (solid <-> works)) & ((special <-> purpose <-> machinery) | (special <-> purpose <-> machine) | (special <-> purpose <-> machines) | (high <-> speed <-> machinery) | (high <-> speed <-> machines) | (high <-> speed <-> machines) | (high-speed <-> machine) | (high-speed <-> machines) | (high-speed <-> machinery) | (automated <-> machinery) | (automated <-> machine) | (automated <-> machinery) | (automated <-> machine) | (automated <-> machines) | (automation <-> machinery) | (automation <-> solution) | (automation <-> solutions) | (automated <-> solution) | (automated <-> solutions) | (conveyor <-> system) | (conveyor <-> systems) | (motors) | (servo) | (gearbox) | (gearboxes) | (drive <-> system) | (drive <-> systems) | (test <-> rig) | (test-rig) | (test <-> rigs) | (test-rigs))'
结合起来，这似乎为数据库减少了大约1万个结果的工作量。
任何帮助，替代策略或附加条款的地方。
我也可以增加RAM / HDD并更新任何相关的pg_settings。当前统计数据为：8GB RAM和100GB HD空间，设置已根据pg_tune决定
编辑：添加了解释查询，仅供参考，因为我以前运行过搜索，因此已缓存
Bitmap Heap Scan on entities.candidates_mv c (cost=10000001184.01..10000001191.96 rows=2 width=8) (actual time=187.902..233.306 rows=2656 loops=1)
Output: c.id
Recheck Cond: (c.ts_description @@ '( ''design'' <-> ''engineer'' | ''mechanical'' <-> ''design'' | ''mechanical'' <-> ''engineering'' | ''mechanical'' <-> ''engineer'' | ''development'' <-> ''engineer'' | ''senior'' <-> ''design'' | ''principal'' <-> ''design'' | ''principle'' <-> ''design'' | ''lead'' <-> ''design'' | ''chief'' <-> ''design'' | ''senior'' <-> ''mechanical'' | ''principal'' <-> ''mechanical'' | ''principle'' <-> ''mechanical'' | ''chief'' <-> ''mechanical'' | ''lead'' <-> ''mechanical'' | ''product'' <-> ''design'' | ''senior'' <-> ''product'' | ''principal'' <-> ''product'' | ''principle'' <-> ''product'' | ''lead'' <-> ''product'' | ''chief'' <-> ''product'' ) & ( ''solidworks'' | ''solid'' <-> ''works'' ) & ( ''injection'' | ''injected'' ) & ( ''mold'' | ''mould'' | ''molds'' | ''moulds'' | ''molding'' | ''moulding'' | ''moldings'' | ''mouldings'' | ''moldable'' | ''mouldable'' | ''molded'' | ''moulded'' )'::tsquery)
Rows Removed by Index Recheck: 288
Heap Blocks: exact=2471
Buffers: shared hit=18560
-> Bitmap Index Scan on candidates_mv_ts_description_idx (cost=0.00..1184.01 rows=2 width=0) (actual time=186.334..186.334 rows=2944 loops=1)
Index Cond: (c.ts_description @@ '( ''design'' <-> ''engineer'' | ''mechanical'' <-> ''design'' | ''mechanical'' <-> ''engineering'' | ''mechanical'' <-> ''engineer'' | ''development'' <-> ''engineer'' | ''senior'' <-> ''design'' | ''principal'' <-> ''design'' | ''principle'' <-> ''design'' | ''lead'' <-> ''design'' | ''chief'' <-> ''design'' | ''senior'' <-> ''mechanical'' | ''principal'' <-> ''mechanical'' | ''principle'' <-> ''mechanical'' | ''chief'' <-> ''mechanical'' | ''lead'' <-> ''mechanical'' | ''product'' <-> ''design'' | ''senior'' <-> ''product'' | ''principal'' <-> ''product'' | ''principle'' <-> ''product'' | ''lead'' <-> ''product'' | ''chief'' <-> ''product'' ) & ( ''solidworks'' | ''solid'' <-> ''works'' ) & ( ''injection'' | ''injected'' ) & ( ''mold'' | ''mould'' | ''molds'' | ''moulds'' | ''molding'' | ''moulding'' | ''moldings'' | ''mouldings'' | ''moldable'' | ''mouldable'' | ''molded'' | ''moulded'' )'::tsquery)
Buffers: shared hit=2379
Planning time: 0.300 ms
Execution time: 233.996 ms