1. 建表
2. 插入测试数据
- postgres=# create table tb_index_test(id serial primary key,name character varying);
- CREATE TABLE
- postgres=#
- postgres=# \d tb_index_test;
- Table "public.tb_index_test"
- Column | Type | Modifiers
- --------+-------------------+------------------------------------------------------------
- id | integer | not null default nextval('tb_index_test_id_seq'::regclass)
- name | character varying |
- Indexes:
- "tb_index_test_pkey" PRIMARY KEY,btree (id)
3. index only scan的启动成本
- postgres=# insert into tb_index_test values(generate_series(1,10000),'john');
- INSERT 0 10000
对于IndexOnlyScan节点,虽然是从index输出结果,但是还要先检查visibility MAP,因此startup_cost也大于0. 但是,它的启动成本计算并未计入这部分开销. 而是和普通的index scan计算方法一样.当你新建表之后,没有进行过vacuum和autovacuum操作,这时还没有VM文件,加上索引并没有保存记录的版本信息,索引index only scan还是需要扫描数据块来获取版本信息,这个时候可能比index scan要慢了。
4. 当筛选的数据集变大到一定程度的时候,优化器还是会选择全表扫描
- postgres=# explain(analyze,verbose,buffers)select count(0) from tb_index_test where id<400;
- QUERY PLAN
- ---------------------------------------------------------------------------------------------------------------------------------------------------------
- Aggregate (cost=22.29..22.30 rows=1 width=0) (actual time=0.127..0.127 rows=1 loops=1)
- Output: count(0)
- Buffers: shared hit=6
- -> Index Only Scan using tb_index_test_pkey on public.tb_index_test (cost=0.29..21.29 rows=400 width=0) (actual time=0.021..0.088 rows=399 loops=1)
- Output: id
- Index Cond: (tb_index_test.id < 400)
- <span style="color:#ff0000;">Heap Fetches: 399 --没有visibility map文件之前,需要fetch所有的heap page。</span>
- Buffers: shared hit=6
- Total runtime: 0.150 ms
- (9 rows)
- postgres=# explain(analyze,buffers)select id from tb_index_test where id<8000;
- QUERY PLAN
- ----------------------------------------------------------------------------------------------------------------------
- Seq Scan on public.tb_index_test (cost=0.00..180.00 rows=8000 width=4) (actual time=0.009..1.526 rows=7999 loops=1)
- Output: id
- Filter: (tb_index_test.id < 8000)
- Rows Removed by Filter: 2001
- Buffers: shared hit=55
- Total runtime: 1.886 ms
- (6 rows)
- postgres=# set enable_seqscan =off;
- SET
- postgres=# explain(analyze,buffers)select id from tb_index_test where id<8000;
- QUERY PLAN
- ------------------------------------------------------------------------------------------------------------------------------------------------------
- Index Only Scan using tb_index_test_pkey on public.tb_index_test (cost=0.29..236.28 rows=8000 width=4) (actual time=0.028..2.342 rows=7999 loops=1)
- Output: id
- Index Cond: (tb_index_test.id < 8000)
- Heap Fetches: 0
- Buffers: shared hit=24
- Total runtime: 3.439 ms
- (6 rows)
如果把Seq Scan关闭,强制让优化器使用index only scan,发现成本比全表扫描的大。
5. 这个时候执行min(id),max(id)效率是很高的。
因为索引是按顺序存储的,只需访问一个索引块就可以得到min(id),max(id)也是一样的。
- postgres=# explain(analyze,buffers)select min(id),max(id) from tb_index_test;
- QUERY PLAN
- ----------------------------------------------------------------------------------------------------------------------------------------------------------
- Result (cost=0.63..0.64 rows=1 width=0) (actual time=0.024..0.024 rows=1 loops=1)
- Output: $0,$1
- Buffers: shared hit=6
- InitPlan 1 (returns $0)
- -> Limit (cost=0.29..0.31 rows=1 width=4) (actual time=0.017..0.017 rows=1 loops=1)
- Output: tb_index_test.id
- Buffers: shared hit=3
- -> Index Only Scan using tb_index_test_pkey on public.tb_index_test (cost=0.29..295.29 rows=10000 width=4) (actual time=0.015..0.015 rows=1 loops=1)
- Output: tb_index_test.id
- Index Cond: (tb_index_test.id IS NOT NULL)
- Heap Fetches: 0
- Buffers: shared hit=3
- InitPlan 2 (returns $1)
- -> Limit (cost=0.29..0.31 rows=1 width=4) (actual time=0.005..0.005 rows=1 loops=1)
- Output: tb_index_test_1.id
- Buffers: shared hit=3
- -> Index Only Scan Backward using tb_index_test_pkey on public.tb_index_test tb_index_test_1 (cost=0.29..295.29 rows=10000 width=4) (actual time=0.005..0.005 rows=1 loops=1)
- Output: tb_index_test_1.id
- Index Cond: (tb_index_test_1.id IS NOT NULL)
- Heap Fetches: 0
- Buffers: shared hit=3
- Total runtime: 0.061 ms
- (22 rows)