怎么理解PostgreSQL全表扫描问题

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本节内容来源于PGer的一个问题:
Q:
由于多版本的存在，那么全表扫描是不是需要更长的时间了呢？

A:
关于全表扫描,不妨考虑2种极端的情况:
1.insert数据(事务已提交,下同),没有执行update/delete,没有dead tuple,全表扫描效率没有影响;
2.insert数据,执行了大量的update/delete,同时禁用了autovacuum也没有手工执行vacuum,那么存在大量的dead tuple,性能上一是需要更多的IO操作,二是需要执行额外的CPU判断(对于所有的tuple都要执行可见性判断).
其判断逻辑如下:

((Xmin == my-transaction &&　　　　　　　inserted by the current transaction　Cmin < my-command &&　　　　　　　　　　before this command, and　(Xmax is null ||　　　　　　　　　　　　the row has not been deleted, or　　(Xmax == my-transaction &&　　　　　　it was deleted by the current transaction　　　Cmax >= my-command)))　　　　　　　but not before this command,||　　　　　　　　　　　　　　　　　　　　　or　(Xmin is committed &&　　　　　　　　　　the row was inserted by a committed transaction, and　　(Xmax is null ||　　　　　　　　　　　　the row has not been deleted, or　　　(Xmax == my-transaction &&　　　　　the row is being deleted by this transaction　　　　Cmax >= my-command) ||　　　　　　but it's not deleted "yet", or　　　　(Xmax != my-transaction &&　　　　the row was deleted by another transaction　　　　　Xmax is not committed))))　　　　that has not been committed

简单做个实验,创建一张表t_fts,
1.插入数据,大小为s1,执行全表扫描,时间为m秒;
2.update所有行,大小为s2,执行全表扫描,时间为n秒.
理论上来说,n应为m的s2/s1倍左右(相对于IO时间,如果tuple数不多,CPU时间可以忽略不计).
创建数据表,插入数据:

testdb=# drop table if exists t_fts;DROP TABLEtestdb=# create table t_fts(id int,c1 varchar(200),c2 varchar(200));CREATE TABLEtestdb=# testdb=# insert into t_fts select x,lpad('c1'||x,200,'x'),lpad('c1'||x,200,'x') from generate_series(1,2000000) as x;INSERT 0 2000000testdb=# select pg_size_pretty(pg_table_size('t_fts')); pg_size_pretty ---------------- 868 MB(1 row)

禁用autovacuum,执行查询:

testdb=# alter system set autovacuum=off;ALTER SYSTEMtestdb=# show  autovacuum; autovacuum ------------ off(1 row)testdb=# explain analyze verbose select * from t_fts;                                                         QUERY PLAN                                                         ---------------------------------------------------------------------------------------------------------------------------- Seq Scan on public.t_fts  (cost=0.00..131112.16 rows=2000016 width=412) (actual time=0.048..1086.289 rows=2000000 loops=1)   Output: id, c1, c2 Planning Time: 30.762 ms Execution Time: 1181.360 ms(4 rows)

执行update:

testdb=# update t_fts set c1 = lpad('c1'||(id+1),200,id+1||''),c2 =  lpad('c1'||(id+1),200,id+1||'');UPDATE 2000000testdb=# select pg_size_pretty(pg_table_size('t_fts')); pg_size_pretty ---------------- 1737 MB(1 row)testdb=# explain analyze verbose select * from t_fts;                                                          QUERY PLAN                                                         ------------------------------------------------------------------------------------------------------------------------------- Seq Scan on public.t_fts  (cost=0.00..262223.14 rows=4000014 width=412) (actual time=3168.414..6117.780 rows=2000000 loops=1)   Output: id, c1, c2 Planning Time: 5.493 ms Execution Time: 6205.705 ms(4 rows)testdb=# explain analyze verbose select * from t_fts;                                                          QUERY PLAN                                                         ------------------------------------------------------------------------------------------------------------------------------ Seq Scan on public.t_fts  (cost=0.00..262223.14 rows=4000014 width=412) (actual time=776.660..2311.270 rows=2000000 loops=1)   Output: id, c1, c2 Planning Time: 0.426 ms Execution Time: 2391.895 ms(4 rows)testdb=# explain analyze verbose select * from t_fts;                                                          QUERY PLAN                                                         ------------------------------------------------------------------------------------------------------------------------------ Seq Scan on public.t_fts  (cost=0.00..262223.14 rows=4000014 width=412) (actual time=728.758..2293.157 rows=2000000 loops=1)   Output: id, c1, c2 Planning Time: 0.481 ms Execution Time: 2373.241 ms(4 rows)

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