【发布时间】:2015-07-20 05:14:08
【问题描述】:
我正在编写一个 node.js 应用程序来启用对 PostgreSQL 数据库的搜索。为了在搜索框中启用 twitter 预输入,我必须从数据库中处理一组关键字以在页面加载之前初始化 Bloodhound。如下所示:
SELECT distinct handlerid from lotintro where char_length(lotid)=7;
所以对于一张大桌子(lotintro)来说,这是很昂贵的;这也是愚蠢的,因为查询结果很可能在一段时间内对于不同的网络访问者保持不变。
处理这个问题的正确方法是什么?我正在考虑几个选项:
1) 将查询放入存储过程中,并从 node.js 中调用:
SELECT * from getallhandlerid()
这是否意味着查询将被编译并且数据库将自动返回相同的结果集,而实际运行的查询却不知道结果不会改变?
2) 或者,创建一个单独的表来存储不同的 handlerid 并使用每天运行的触发器更新表? (我知道理想情况下,触发器应该在每次插入/更新表时运行,但这太贵了)。
3) 按照建议创建部分索引。以下是收集的内容:
查询
SELECT distinct handlerid from lotintro where length(lotid) = 7;
索引
CREATE INDEX lotid7_idx ON lotintro (handlerid)
WHERE length(lotid) = 7;
有索引,查询耗时250ms左右,试运行
explain (analyze on, TIMING OFF) SELECT distinct handlerid from lotintro where length(lotid) = 7
"HashAggregate (cost=5542.64..5542.65 rows=1 width=6) (actual rows=151 loops=1)"
" -> Bitmap Heap Scan on lotintro (cost=39.08..5537.50 rows=2056 width=6) (actual rows=298350 loops=1)"
" Recheck Cond: (length(lotid) = 7)"
" Rows Removed by Index Recheck: 55285"
" -> Bitmap Index Scan on lotid7_idx (cost=0.00..38.57 rows=2056 width=0) (actual rows=298350 loops=1)"
"Total runtime: 243.686 ms"
无索引,查询耗时210ms左右,试运行
explain (analyze on, TIMING OFF) SELECT distinct handlerid from lotintro where length(lotid) = 7
"HashAggregate (cost=19490.11..19490.12 rows=1 width=6) (actual rows=151 loops=1)"
" -> Seq Scan on lotintro (cost=0.00..19484.97 rows=2056 width=6) (actual rows=298350 loops=1)"
" Filter: (length(lotid) = 7)"
" Rows Removed by Filter: 112915"
"Total runtime: 214.235 ms"
我在这里做错了什么?
4) 使用 alexius 建议的索引和查询:
create index on lotintro using btree(char_length(lotid), handlerid);
但这不是最佳解决方案。因为只有很少的不同值,您可以使用称为松散索引扫描的技巧,在您的情况下它应该工作得更快:
explain (analyze on, BUFFERS on, TIMING OFF)
WITH RECURSIVE t AS (
(SELECT handlerid FROM lotintro WHERE char_length(lotid)=7 ORDER BY handlerid LIMIT 1) -- parentheses required
UNION ALL
SELECT (SELECT handlerid FROM lotintro WHERE char_length(lotid)=7 AND handlerid > t.handlerid ORDER BY handlerid LIMIT 1)
FROM t
WHERE t.handlerid IS NOT NULL
)
SELECT handlerid FROM t WHERE handlerid IS NOT NULL;
"CTE Scan on t (cost=444.52..446.54 rows=100 width=32) (actual rows=151 loops=1)"
" Filter: (handlerid IS NOT NULL)"
" Rows Removed by Filter: 1"
" Buffers: shared hit=608"
" CTE t"
" -> Recursive Union (cost=0.42..444.52 rows=101 width=32) (actual rows=152 loops=1)"
" Buffers: shared hit=608"
" -> Limit (cost=0.42..4.17 rows=1 width=6) (actual rows=1 loops=1)"
" Buffers: shared hit=4"
" -> Index Scan using lotid_btree on lotintro lotintro_1 (cost=0.42..7704.41 rows=2056 width=6) (actual rows=1 loops=1)"
" Index Cond: (char_length(lotid) = 7)"
" Buffers: shared hit=4"
" -> WorkTable Scan on t t_1 (cost=0.00..43.83 rows=10 width=32) (actual rows=1 loops=152)"
" Filter: (handlerid IS NOT NULL)"
" Rows Removed by Filter: 0"
" Buffers: shared hit=604"
" SubPlan 1"
" -> Limit (cost=0.42..4.36 rows=1 width=6) (actual rows=1 loops=151)"
" Buffers: shared hit=604"
" -> Index Scan using lotid_btree on lotintro (cost=0.42..2698.13 rows=685 width=6) (actual rows=1 loops=151)"
" Index Cond: ((char_length(lotid) = 7) AND (handlerid > t_1.handlerid))"
" Buffers: shared hit=604"
"Planning time: 1.574 ms"
**"Execution time: 25.476 ms"**
========= 关于 db 的更多信息 ============================
dataloggerDB=# \d lotintro 表“public.lotintro”
Column | Type | Modifiers
--------------+-----------------------------+--------------
lotstartdt | timestamp without time zone | not null
lotid | text | not null
ftc | text | not null
deviceid | text | not null
packageid | text | not null
testprogname | text | not null
testprogdir | text | not null
testgrade | text | not null
testgroup | text | not null
temperature | smallint | not null
testerid | text | not null
handlerid | text | not null
numofsite | text | not null
masknum | text |
soaktime | text |
xamsqty | smallint |
scd | text |
speedgrade | text |
loginid | text |
operatorid | text | not null
loadboardid | text | not null
checksum | text |
lotenddt | timestamp without time zone | not null
totaltest | integer | default (-1)
totalpass | integer | default (-1)
earnhour | real | default 0
avetesttime | real | default 0
Indexes:
"pkey_lotintro" PRIMARY KEY, btree (lotstartdt, testerid)
"lotid7_idx" btree (handlerid) WHERE length(lotid) = 7
your version of Postgres, [PostgreSQL 9.2] cardinalities (how many rows?), [411K rows for table lotintro] percentage for length(lotid) = 7. [298350/411000= 73%]
============= 将所有内容移植到 PG 9.4 之后 =====================
带索引:
explain (analyze on, BUFFERS on, TIMING OFF) SELECT distinct handlerid from lotintro where length(lotid) = 7
"HashAggregate (cost=5542.78..5542.79 rows=1 width=6) (actual rows=151 loops=1)"
" Group Key: handlerid"
" Buffers: shared hit=14242"
" -> Bitmap Heap Scan on lotintro (cost=39.22..5537.64 rows=2056 width=6) (actual rows=298350 loops=1)"
" Recheck Cond: (length(lotid) = 7)"
" Heap Blocks: exact=13313"
" Buffers: shared hit=14242"
" -> Bitmap Index Scan on lotid7_idx (cost=0.00..38.70 rows=2056 width=0) (actual rows=298350 loops=1)"
" Buffers: shared hit=929"
"Planning time: 0.256 ms"
"Execution time: 154.657 ms"
无索引:
explain (analyze on, BUFFERS on, TIMING OFF) SELECT distinct handlerid from lotintro where length(lotid) = 7
"HashAggregate (cost=19490.11..19490.12 rows=1 width=6) (actual rows=151 loops=1)"
" Group Key: handlerid"
" Buffers: shared hit=13316"
" -> Seq Scan on lotintro (cost=0.00..19484.97 rows=2056 width=6) (actual rows=298350 loops=1)"
" Filter: (length(lotid) = 7)"
" Rows Removed by Filter: 112915"
" Buffers: shared hit=13316"
"Planning time: 0.168 ms"
"Execution time: 176.466 ms"
【问题讨论】:
-
"将自动返回相同的结果集而无需实际运行查询" - 不会。查询将每次运行。 2) 可以通过使用物化视图来实现 - 可能是更好的方法
-
谢谢! @a_horse_with_no_name
-
我刚刚找到了一篇很好的文章。 pgcon.org/2008/schedule/events/69.en.html
-
"查询成本大约 200 毫秒" - 查询成本不是以毫秒为单位的(实际上它根本没有单位)。使用索引的第一个查询的成本为 5542,第二个(不使用索引)的成本为 19490 - 高出 3.5 倍 - 因此索引使用效率更高。如果您想获得查询的实际运行时间(以毫秒为单位),您需要使用
explain (analyze, timing)。 -
@a_horse_with_no_name:要获得最准确的性能比较,
EXPLAIN (ANALYZE, TIMING OFF)应该是最好的(只是内部细节没有时间安排)。
标签: postgresql stored-procedures triggers twitter-typeahead bloodhound