postgresql-重复执行相同语句，试试 prepare！

为了生成一些示例数据，这里使用了scale factor(规模因子)为 100 的 pgbench，这在 pgbench_accounts 表中产生10,000,000 行：

bench=#pgbench -U dbmgr -h 127.0.0.1 -p 5432 -i -s 100 bench
Password: 
dropping old tables...
NOTICE:  table "pgbench_accounts" does not exist, skipping
NOTICE:  table "pgbench_branches" does not exist, skipping
NOTICE:  table "pgbench_history" does not exist, skipping
NOTICE:  table "pgbench_tellers" does not exist, skipping
creating tables...
generating data (client-side)...
10000000 of 10000000 tuples (100%) done (elapsed 19.54 s, remaining 0.00 s)
vacuuming...
creating primary keys...
done in 29.01 s (drop tables 0.00 s, create tables 0.02 s, client-side generate 20.19 s, vacuum 0.70 s, primary keys 8.09 s).

postgres@pgrec-d:~psql bench
psql (15.5 (Ubuntu 15.5-1.pgdg22.04+1))
Type "help" for help.

bench=# select count(*) from pgbench_accounts;
  count  
----------
 10000000
(1 row)
 
bench=# d pgbench_accounts
              Table "public.pgbench_accounts"
  Column  |     Type      | Collation | Nullable | Default
----------+---------------+-----------+----------+---------
 aid      | integer       |           | not null | 
 bid      | integer       |           |          | 
 abalance | integer       |           |          | 
 filler   | character(84) |           |          | 
Indexes:
    "pgbench_accounts_pkey" PRIMARY KEY, btree (aid)

简单query一下：

bench=# select count(*) from pgbench_accounts where aid = 11111;
 count
-------
     1
(1 row)

正如本文开头所述，PostgreSQL 将需要解析该语句。使用带有正确选项的 explain，您可以看到产生执行计划花费了多少时间：

                                                                    QUERY PLAN                                                                     
---------------------------------------------------------------------------------------------------------------------------------------------------
 Aggregate  (cost=4.46..4.46 rows=1 width=8) (actual time=0.041..0.042 rows=1 loops=1)
   Buffers: shared hit=4
   ->  Index Only Scan using pgbench_accounts_pkey on pgbench_accounts  (cost=0.43..4.45 rows=1 width=0) (actual time=0.030..0.032 rows=1 loops=1)
         Index Cond: (aid = 11111)
         Heap Fetches: 0
         Buffers: shared hit=4
 Planning Time: 0.125 ms
 Execution Time: 0.086 ms
(8 rows)

产生此语句的执行计划比执行它花费更多时间。现在假设您要执行同一条语句一千次：

bench=#\t
bench=#select 'select count(*) from pgbench_accounts where aid = 11111;' from generate_series(1,1000) i; \g test.sql
bench=# \! cat test.sql | head
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
select count(*) from pgbench_accounts where aid = 11111;
...

当执行该命令时，强制 PostgreSQL解析所有这 1000 条语句：

bench=# \timing
Timing is on.
bench=#\! /usr/bin/time -p psql -U dbmgr -f test.sql -d bench
real 0.76s
user 0.13s
sys 0.1s

为了避免这种情况，我们使用prepare去准备这条sql：

prepare c1 as select count(*) from pgbench_accounts where aid = 11111;
PREPARE

一旦prepare好，就可以执行它：

bench=# execute c1;
 count
-------
     1
(1 row)

explain:

bench=# explain(analyze,buffers) execute c1;
 Aggregate  (cost=4.46..4.46 rows=1 width=8) (actual time=0.041..0.042 rows=1 loops=1)
   Buffers: shared hit=4
   ->  Index Only Scan using pgbench_accounts_pkey on pgbench_accounts  (cost=0.43..4.45 rows=1 width=0) (actual time=0.030..0.032 rows=1 loops=1)
         Index Cond: (aid = 11111)
         Heap Fetches: 0
         Buffers: shared hit=4
 Planning Time: 0.007 ms
 Execution Time: 0.100 ms

注意，与未准备好的语句相比，planning time减少了不少：

bench=# explain(analyze,buffers) select count(1) from pgbench_accounts where aid=11111;
 Aggregate  (cost=4.46..4.46 rows=1 width=8) (actual time=0.076..0.077 rows=1 loops=1)
   Buffers: shared hit=4
   ->  Index Only Scan using pgbench_accounts_pkey on pgbench_accounts  (cost=0.43..4.45 rows=1 width=0) (actual time=0.057..0.059 rows=1 loops=1)
         Index Cond: (aid = 11111)
         Heap Fetches: 0
         Buffers: shared hit=4
 Planning:
   Buffers: shared hit=3
 Planning Time: 0.376 ms
 Execution Time: 0.166 ms

当现在这样执行一千次:

bench=# \t
Tuples only is off.
bench=# select 'execute c1;' from generate_series(1,1000) i; \g test.sql
bench=# \! sed -i '1s/^/prepare c1 as select count(*) from pgbench_accounts where aid = 11111;/' test.sql
bench=# \! /usr/bin/time -p psql -U dbmgr -f test.sql -d bench
real 0.55s
user 0.11s
sys 0.15s

执行时间将会缩短。在这个简单的例子中，效果不太明显，但这是因为语句本身非常简单。顺便提一下，预编译的语句只在会话期间有效，所以 sed 命令将 prepare 语句添加到文件顶部，预编译本身也需要时间。如果不预编译，执行时间会更短。
当 where 子句中的值发生变化时，可以这样做：

bench=# prepare c1 as select count(*) from pgbench_accounts where aid = $1;
PREPARE
Time: 0.387 ms

解除prepare好的语句

bench=# deallocate c1;
DEALLOCATE
Time: 0.336 ms