retalk PostgreSQL function's [ volatile|stable|immutable ]

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Postgresql 函数的稳定性,以前写过几篇BLOG讲述,见参考部分.
本文再细化并举例说明一下他们的差别.
首先函数稳定性分三种 :
  1. volatile
  2. stable
  3. immutable

首先创建1个测试表 :
  1. digoal=> create table test (id int, info text);
  2. CREATE TABLE
  3. digoal=> insert into test select generate_series(1,100000),random()::text;
  4. INSERT 0 100000
  5. digoal=> create index idx_test_1 on test(id);
  6. CREATE INDEX
1. volatile指函数可以修改数据库,函数参数值相同的情况下,可以返回不同的结果,所以volatile函数在执行过程中优化器对它的处理是每一行都需要执行一次volatile函数.
例如 :
  1. create or replace function f_volatile(i_id int) returns text as $$
  2. declare
  3. result text;
  4. begin
  5. -- update可以用在volatile函数中, 因为UPDATE修改数据
  6. update test set info='new' where id=i_id returning info into result;
  7. return result;
  8. end;
  9. $$ language plpgsql volatile;
执行这个函数,正常返回 :
如果是immutable或者stable的话,将报错.
  1. digoal=> select * from f_volatile(1);
  2. f_volatile
  3. ------------
  4. new
  5. (1 row)
下面的函数用来返回一个NUMERIC,然后进行sum运算.
  1. create or replace function f_test() returns numeric as $$
  2. declare
  3. begin
  4. return 1.5;
  5. end;
  6. $$ language plpgsql volatile;
10W条记录,执行f_test()耗时335毫秒.
  1. digoal=> explain analyze select f_test() from test; QUERY PLAN -------------------------------------------------------------------------------------------------------------- Seq Scan on test (cost=0.00..26638.00 rows=100000 width=0) (actual time=0.035..322.622 rows=100000 loops=1) Total runtime: 334.539 ms (2 rows) Time: 335.035 ms
记住这个执行耗时. 后面要对比f_test()改成stable和immutable后的执行耗时.
单条执行时间 :
  1. digoal=> select f_test(); f_test -------- 1.5 (1 row) Time: 0.192 ms

2. stable 函数,不允许修改数据库.
如下 :
  1. digoal=> alter function f_volatile(int) stable;
  2. ALTER FUNCTION
  3. Time: 0.660 ms
再次执行f_volatile将报错,因为stable的函数不允许执行修改数据库sql,例如UPDATE.
  1. digoal=> select * from f_volatile(1);
  2. ERROR: UPDATE is not allowed in a non-volatile function
  3. CONTEXT: sql statement "update test set info='new' where id=i_id returning info"
  4. PL/pgsql function f_volatile(integer) line 5 at sql statement
  5. Time: 0.869 ms

同样的参数值,stable函数多次执行返回的结果应该一致.
因此优化器可以选择将多次调用stable函数改为一次调用. stable函数作为where条件中的比较值是,可以使用索引. 因为走索引需要一个常量.
  1. digoal=> alter function f_test() stable;
  2. ALTER FUNCTION
  3. digoal=> explain analyze select * from test where id<=f_test()::int;
  4. QUERY PLAN
  5. ------------------------------------------------------------------------------------------------------------------
  6. Index Scan using idx_test_1 on test (cost=0.25..2.55 rows=1 width=21) (actual time=0.019..0.024 rows=2 loops=1)
  7. Index Cond: (id <= (f_test())::integer)
  8. Total runtime: 0.054 ms
  9. (3 rows)
  10. Time: 0.926 ms
改回volatile,则不允许走索引. 如下 :
  1. digoal=> explain analyze select * from test where id<=f_test()::int;
  2. QUERY PLAN
  3. ---------------------------------------------------------------------------------------------------------
  4. Seq Scan on test (cost=0.00..27138.00 rows=33333 width=21) (actual time=0.143..269.208 rows=2 loops=1)
  5. Filter: (id <= (f_test())::integer)
  6. Rows Removed by Filter: 99998
  7. Total runtime: 269.242 ms
  8. (4 rows)
  9. Time: 269.937 ms
另外一个测试是吧f_test()放到结果集部分,而不是where条件里面,stable和immutable的差别也很大 :
  1. digoal=> alter function f_test() stable;
  2. ALTER FUNCTION
  3. digoal=> explain analyze select f_test() from test;
  4. QUERY PLAN
  5. --------------------------------------------------------------------------------------------------------------
  6. Seq Scan on test (cost=0.00..26638.00 rows=100000 width=0) (actual time=0.137..268.707 rows=100000 loops=1)
  7. Total runtime: 281.684 ms
  8. (2 rows)
  9. Time: 282.248 ms
  10. 改成immutable
  11. digoal=> alter function f_test() immutable;
  12. ALTER FUNCTION
  13. Time: 0.359 ms
  14. digoal=> explain analyze select f_test() from test;
  15. QUERY PLAN
  16. ------------------------------------------------------------------------------------------------------------
  17. Seq Scan on test (cost=0.00..1638.00 rows=100000 width=0) (actual time=0.011..23.450 rows=100000 loops=1)
  18. Total runtime: 34.331 ms
  19. (2 rows)
  20. Time: 35.061 ms

3. immutable,和stable非常类似,但是immutable是指在任何情况下,只要参数一致,结果就一致. 而在事务中参数一致则结果一致可以标记为stable而请你不要把它标记为immutable.
另外的显著的区别是优化器对immutable和stable函数的处理上.
如果函数的参数是常量的情况下 :
immutable函数在优化器生成执行计划时会将函数结果替换函数. 也就是函数不在输出的执行计划中,取而代之的是一个结果常量.
stable函数则不会如此,执行计划输出后还是函数.
例如 :
  1. select * from test where id> 1+2;

+对应的操作符函数是immutable的,所以这条sql执行计划输出的是 :
  1. select * from test where id>3;

对于用户自己创建的函数也是如此 :
  1. digoal=> create or replace function f_test(i_id int) returns int as $$
  2. declare
  3. begin
  4. return i_id;
  5. end;
  6. $$ language plpgsql immutable;
  7. CREATE FUNCTION
  8. Time: 1.020 ms
immutable 测试 :
  1. digoal=> explain analyze select * from test where id<f_test(50);
  2. QUERY PLAN
  3. --------------------------------------------------------------------------------------------------------------------
  4. Index Scan using idx_test_1 on test (cost=0.00..3.15 rows=50 width=21) (actual time=0.007..0.025 rows=49 loops=1)
  5. Index Cond: (id < 50)
  6. Total runtime: 0.058 ms
  7. (3 rows)
  8. 注意这行 :
  9. Index Cond: (id < 50), f_test(50)已经替换成了结果50.
stable 测试 :
  1. digoal=> alter function f_test(int) stable;
  2. ALTER FUNCTION
  3. digoal=> explain analyze select * from test where id<f_test(50);
  4. QUERY PLAN
  5. --------------------------------------------------------------------------------------------------------------------
  6. Index Scan using idx_test_1 on test (cost=0.25..3.40 rows=50 width=21) (actual time=0.019..0.035 rows=49 loops=1)
  7. Index Cond: (id < f_test(50))
  8. Total runtime: 0.066 ms
  9. (3 rows)
  10. 注意这行 :
  11. Index Cond: (id < f_test(50)), f_test(50)没有被替换掉.
另外一组测试 :
  1. digoal=> alter function f_test(int) stable;
  2. ALTER FUNCTION
  3. digoal=> explain analyze select * from test where f_test(2)>1;
  4. QUERY PLAN
  5. -------------------------------------------------------------------------------------------------------------------
  6. Result (cost=0.25..1638.25 rows=100000 width=21) (actual time=0.146..50.367 rows=100000 loops=1)
  7. One-Time Filter: (f_test(2) > 1)
  8. -> Seq Scan on test (cost=0.25..1638.25 rows=100000 width=21) (actual time=0.014..20.646 rows=100000 loops=1)
  9. Total runtime: 61.386 ms
  10. (4 rows)
当f_test是stable 时,比immutable多One-Time Filter: (f_test(2) > 1)

而当immutable,优化器则将 f_test(2)>1这部分直接优化掉了.
  1. digoal=> alter function f_test(int) immutable;
  2. ALTER FUNCTION
  3. digoal=> explain analyze select * from test where f_test(2)>1;
  4. QUERY PLAN
  5. -------------------------------------------------------------------------------------------------------------
  6. Seq Scan on test (cost=0.00..1638.00 rows=100000 width=21) (actual time=0.011..18.801 rows=100000 loops=1)
  7. Total runtime: 29.839 ms
  8. (2 rows)

【prepare statement 注意】
prepare statement请参考 :
这里需要注意的是immutable函数,如果你的函数实际上不是immutable的. 但是你把它标记为immutable了,可能有意想不到的结果 :
  1. digoal=> create or replace function immutable_random() returns numeric as $$
  2. declare
  3. begin
  4. return random();
  5. end;
  6. $$ language plpgsql immutable;
  7. CREATE FUNCTION
创建一个prepare statement.
  1. digoal=> prepare p_test(int) as select $1,immutable_random();
  2. PREPARE
  3. Time: 0.473 ms
执行这个prepared statement :
  1. digoal=> execute p_test(1);
  2. ?column? | immutable_random
  3. ----------+-------------------
  4. 1 | 0.277766926214099
  5. (1 row)
  6. Time: 0.398 ms
  7. digoal=> execute p_test(1);
  8. ?column? | immutable_random
  9. ----------+-------------------
  10. 1 | 0.974089733790606
  11. (1 row)
  12. Time: 0.209 ms
  13. digoal=> execute p_test(1);
  14. ?column? | immutable_random
  15. ----------+-------------------
  16. 1 | 0.800415104720742
  17. (1 row)
  18. Time: 0.212 ms
  19. digoal=>
  20. digoal=> execute p_test(1);
  21. ?column? | immutable_random
  22. ----------+------------------
  23. 1 | 0.41237005777657
  24. (1 row)
  25. Time: 0.290 ms
  26. digoal=> execute p_test(1);
  27. ?column? | immutable_random
  28. ----------+--------------------
  29. 1 | 0.0541226323693991
  30. (1 row)
  31. Time: 0.211 ms
第六次开始使用generic_plan,而immutable function在plan时将被结果常量替换.
  1. digoal=> execute p_test(1);
  2. ?column? | immutable_random
  3. ----------+-------------------
  4. 1 | 0.431490630842745
  5. (1 row)
  6. Time: 0.233 ms
以后再执行这个prepare statement,immutable_random()部分都将得到同样的结果.
  1. digoal=> execute p_test(1);
  2. ?column? | immutable_random
  3. ----------+-------------------
  4. 1 | 0.431490630842745
  5. (1 row)
  6. Time: 0.165 ms
  7. digoal=> execute p_test(2);
  8. ?column? | immutable_random
  9. ----------+-------------------
  10. 2 | 0.431490630842745
  11. (1 row)
  12. Time: 0.273 ms
  13. digoal=> execute p_test(3);
  14. ?column? | immutable_random
  15. ----------+-------------------
  16. 3 | 0.431490630842745
  17. (1 row)
  18. Time: 0.149 ms
而把immutable_random()改成volatile或者stable后,immutable_random()都将产生不同的结果,不会发生以上情况.
因为他们在plan时函数不会被结果替换.
所以在prepare statement中使用immutable函数,需要特别注意这个函数到底是不是真的是immutable的.

【MVCC 注意】
这里要注意的是volatile,stable,immutable这几种函数,对数据的修改的可见性分两种情况.
volatile,调用函数sql对数据的修改,可见.
stable,immutable,调用函数sql对数据的修改,不可见.
  1. STABLE and IMMUTABLE functions use a snapshot established as of the start of the calling query,
  2. whereas VOLATILE functions obtain a fresh snapshot at the start of each query they execute.
例如 :
创建测试表 :
  1. digoal=> create table test(id int,info text);
  2. CREATE TABLE
  3. Time: 50.356 ms
  4. digoal=> insert into test select 1,random()::text from generate_series(1,1000);
  5. INSERT 0 1000
  6. Time: 5.027 ms
创建修改函数,这个函数将在另一个函数调用,用来修改ID。
因为另一个函数是用perform f_mod(int)来修改数据,所以另外一个函数可以改成volatile,immutable任意.
  1. digoal=> create or replace function f_mod(i_id int) returns void as $$
  2. declare
  3. begin
  4. update test set id=i_id+1 where id=i_id;
  5. end;
  6. $$ language plpgsql volatile;
测试稳定性的函数 :
  1. digoal=> create or replace function f_test(i_id int) returns bigint as $$
  2. declare
  3. result int8;
  4. begin
  5. perform f_mod(i_id);
  6. select count(*) into result from test where id=i_id;
  7. return result;
  8. end;
  9. $$ language plpgsql volatile;

当稳定性=volatile时,修改可以被 select count(*) into result from test where id=i_id; 看到 :
所以更新后结果为0 :
  1. digoal=> select f_test(1);
  2. f_test
  3. --------
  4. 0
  5. (1 row)
改成stable,它看到的是sql开始是的snapshot,所以对修改不可见,结果还是1000 :
  1. digoal=> alter function f_test(int) stable;
  2. ALTER FUNCTION
  3. digoal=> select f_test(2);
  4. f_test
  5. --------
  6. 1000
  7. (1 row)
改成immutable,结果还是1000 :
  1. digoal=> alter function f_test(int) immutable;
  2. ALTER FUNCTION
  3. digoal=> select f_test(3);
  4. f_test
  5. --------
  6. 1000
  7. (1 row)

还有一种情况是如果修改是来自函数体外部的修改,那是否可见?
  1. digoal=> create or replace function f_test(i_id int) returns bigint as $$
  2. declare
  3. result int8;
  4. begin
  5. select count(*) into result from test where id=i_id;
  6. return result;
  7. end;
  8. $$ language plpgsql volatile;
  9. CREATE FUNCTION
看不到with的修改 :
  1. digoal=> alter function f_test(int) immutable;
  2. ALTER FUNCTION
  3. digoal=> with t1 as (
  4. digoal(> update test set id=id+1 where id=4
  5. digoal(> )
  6. digoal-> select f_test(4);
  7. f_test
  8. --------
  9. 1000
  10. (1 row)
看不到with的修改 :
  1. digoal=> alter function f_test(int) stable;
  2. ALTER FUNCTION
  3. digoal=> with t1 as (
  4. update test set id=id+1 where id=5
  5. )
  6. select f_test(5);
  7. f_test
  8. --------
  9. 1000
  10. (1 row)
看不到with的修改 :
  1. digoal=> alter function f_test(int) volatile;
  2. ALTER FUNCTION
  3. digoal=> with t1 as (
  4. update test set id=id+1 where id=6
  5. )
  6. select f_test(6);
  7. f_test
  8. --------
  9. 1000
  10. (1 row)

在事务中时,都能看到本事务在前面做的修改 :
  1. digoal=> alter function f_test(int) immutable;
  2. ALTER FUNCTION
  3. digoal=> begin;
  4. BEGIN
  5. digoal=> update test set id=id+1 where id=13;
  6. UPDATE 1000
  7. digoal=> select f_test(13);
  8. f_test
  9. --------
  10. 0
  11. (1 row)
  12. digoal=> select f_test(14);
  13. f_test
  14. --------
  15. 1000
  16. (1 row)
  17. digoal=> end;
  18. COMMIT
volatile,stable测试略,同上。

【其他】
1. 查看函数的稳定性 :
digoal=> select proname,proargtypes,provolatile from pg_proc where proname='f_test';
proname | proargtypes | provolatile
---------+-------------+-------------
f_test | | i
f_test | 23 | i
(2 rows)
i表示immutable,s表示stable,v表示volatile.
2. 请按实际情况严格来标记一个函数的稳定性.
3. stable函数和immutable函数不能直接调用UPDATE这种修改数据库sql语句. 但是通过perform volatile function或者select volatile function还是会修改到数据,因为Postgresql不会有更深层次的检查.

【参考】

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