kenyon=# select count(1) from dba.website ; --普通堆栈表,无任何索引约束
count
-------
20
(1 row)
kenyon=# explain select * from dba.website ;
QUERY PLAN
--------------------------------------------------------
Seq Scan on website (cost=0.00..1.20 rows=20 width=4)
(1 row)
--relpages磁盘页,reltuples是行数(与实际不一定相符,一般略小)
kenyon=# select relpages,reltuples from pg_class where relname = 'website';
relpages | reltuples
----------+-----------
1 | 20
(1 row)
kenyon=# select 1*1+20*0.01;
--cost = relpages * seq_page_cost + reltuples * cpu_tuple_cost
?column?
----------
1.20
(1 row)
kenyon=# show cpu_tuple_cost ;
cpu_tuple_cost
----------------
0.01
(1 row)
kenyon=# show seq_page_cost;
seq_page_cost
---------------
1
(1 row)
--加限制条件的执行计划
kenyon=# select count(1) from dba.website where hits >15;
count
-------
5
(1 row)
kenyon=# explain select * from dba.website where hits >15;
QUERY PLAN
-------------------------------------------------------
Seq Scan on website (cost=0.00..1.25 rows=5 width=4)
Filter: (hits > 15)
(2 rows)
kenyon=# show cpu_operator_cost ;
cpu_operator_cost
-------------------
0.0025
(1 row)
因为扫描的总数是20行,不变的,所以COST不会下降,相反反而增加了0.05,这是因为额外消耗了CPU的时间去检查符合约束条件数据,即cost 在原来的基础上再增加 20 * 0.0025 = 0.05 (reltuples * cpu_operator_cost)
--加索引的执行计划
kenyon=# select count(1) from dba.website_2 ;
count
-------
8000
(1 row)
kenyon=# explain select * from dba.website_2 ;
QUERY PLAN
--------------------------------------------------------------
Seq Scan on website_2 (cost=0.00..112.00 rows=8000 width=4)
(1 row)
kenyon=# select relpages,reltuples from pg_class where relname = 'website_2';
relpages | reltuples
----------+-----------
32 | 8000
(1 row)
kenyon=# explain select * from dba.website_2 where hits >7900; --走的索引
QUERY PLAN
----------------------------------------------------------------------------------
Index Scan using ind_website_2 on website_2 (cost=0.00..10.00 rows=100 width=4)
Index Cond: (hits > 7900)
(2 rows)
()
kenyon=# explain select * from dba.website_2 where hits >10; --未走索引(不满足索引条件,full scan)
QUERY PLAN
--------------------------------------------------------------
Seq Scan on website_2 (cost=0.00..132.00 rows=7991 width=4) -- 132 = 112+8000*0.0025
Filter: (hits > 10)
(2 rows)
虽然读取的COST更大,但是因为索引的缘故,访问的数据量变小了,所以总体COST是下降的。
--多表JOIN的执行计划 示例: 若想看实际的一个执行时间,可以加上 analyze 参数
kenyon=# explain analyze select * from dba.website a ,dba.website_2 b where a.hits = b.hits and a.hits >18;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------
Merge Join (cost=1.26..1.90 rows=2 width=8) (actual time=0.070..0.075 rows=2 loops=1)
Merge Cond: (b.hits = a.hits)
-> Index Scan using ind_website_2 on website_2 b (cost=0.00..235.25 rows=8000 width=4) (actual time=0.013..0.020 rows=21 loops=1)
-> Sort (cost=1.26..1.26 rows=2 width=4) (actual time=0.035..0.037 rows=2 loops=1)
Sort Key: a.hits
Sort Method: quicksort Memory: 17kB
-> Seq Scan on website a (cost=0.00..1.25 rows=2 width=4) (actual time=0.009..0.011 rows=2 loops=1)
Filter: (hits > 18)
Total runtime : 0.120 ms
(9 rows)
total runtime 是执行器启动和关闭的时间,但不包括解析,重写和规划的时间
kenyon=# insert into dba.website select generate_series(8000,9000);
INSERT 0 1001
kenyon=# select relpages,reltuples,relname,relkind from pg_class where relname like '%website%';
relpages | reltuples | relname | relkind
----------+-----------+---------------+---------
1 | 20 | website | r
32 | 8000 | website_2 | r
20 | 8000 | ind_website_2 | i
(3 rows)
kenyon=# vacuum analyze dba.website;
VACUUM
kenyon=# vacuum analyze dba.website;
VACUUM
kenyon=# select relpages,reltuples,relname,relkind from pg_class where relname like '%website%';
relpages | reltuples | relname | relkind
----------+-----------+---------------+---------
5 | 1021 | website | r
36 | 8999 | website_2 | r
22 | 8999 | ind_website_2 | i
(3 rows)
示例2:
kenyon=# insert into dba.website select generate_series(8000,9000);
INSERT 0 1001
kenyon=# select relpages,reltuples,relname,relkind from pg_class where relname like '%website%';
relpages | reltuples | relname | relkind
----------+-----------+---------------+---------
1 | 21 | website | r
36 | 8999 | website_2 | r
22 | 8999 | ind_website_2 | i
(3 rows)
kenyon=# create index ind_website on dba.website(hits);
CREATE INDEX
kenyon=# select relpages,reltuples,relname,relkind from pg_class where relname like '%website%';
relpages | reltuples | relname | relkind
----------+-----------+---------------+---------
5 | 1022 | website | r
36 | 8999 | website_2 | r
22 | 8999 | ind_website_2 | i
5 | 1022 | ind_website | i
(4 rows)
所涉及的系统表:
kenyon=# show default_statistics_target ;
default_statistics_target
---------------------------
100
(1 row)
kenyon=# show geqo_threshold ; --这个参数的大小会设置执行计划从穷举搜索到概率选择性搜索的临界值
geqo_threshold
----------------
12
(1 row)
kenyon=# show join_collapse_limit ; --join连接走执行计划上限
join_collapse_limit
---------------------
8
(1 row)
kenyon=# show from_collapse_limit ;
from_collapse_limit
---------------------
8
(1 row)
EXPLAIN kenyon=# explain (analyze,verbose,costs,buffers) select id from dba.test222 order by id desc limit 1;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------
Limit (cost=1807.80..1807.80 rows=1 width=4) (actual time=87.167..87.168 rows=1 loops=1)
Output: id
Buffers: shared hit=393
-> Sort (cost=1807.80..2043.60 rows=94320 width=4) (actual time=87.165..87.165 rows=1 loops=1)
Output: id
Sort Key: test222.id
Sort Method: top-N heapsort Memory: 17kB
Buffers: shared hit=393
-> Seq Scan on dba.test222 (cost=0.00..1336.20 rows=94320 width=4) (actual time=0.036..42.847 rows=100000 loops=1)
Output: id
Buffers: shared hit=393
Total runtime: 87.183 ms
(12 rows)
kenyon=# explain (analyze,verbose,costs,buffers) select max(id) from dba.test222;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=1572.00..1572.01 rows=1 width=4) (actual time=77.679..77.680 rows=1 loops=1)
Output: max(id)
Buffers: shared hit=393
-> Seq Scan on dba.test222 (cost=0.00..1336.20 rows=94320 width=4) (actual time=0.012..36.908 rows=100000 loops=1)
Output: id
Buffers: shared hit=393
Total runtime: 77.701 ms
(7 rows)
explain参数解释:
FORMAT :默认格式是text
一个顺序磁盘页面操作的cost值由系统参数seq_page_cost (floating point)参数指定的,由于这个参数默认为1.0,所以我们可以认为一次顺序磁盘页面操作的cost值为1。
下面
osdba=# explain select * from t;
QUERY PLAN
———————————————————-
Seq Scan on t (cost=0.00 ..4621.00 rows=300000 width=10 )
(1 row)
cost=说明:
可以explain后加analyze来通过真实执行这个SQL来获得真实的执行计划和执行时间:.
osdba=# EXPLAIN ANALYZE SELECT * FROM t;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------
Seq Scan on t (cost=0.00..4621.00 rows=300000 width=10) (actual time=0.022 ..355.380rows=300000 loops=1)
Total runtime: 696.074 ms
actual time=中的第一个数字表示返回第一行需要的时间(叫启动时间),第二个数字表示执行这个整个花的时间。后面的rows=300000是实际的行数。
表顺序扫描由于是立即可以获得第一行,所以启动时间一般都是0,而如果是排序操作,则需要处理完所有行后才能返回第一行,所以排序操作是需要启动时间的,下表列出了哪些操作是需要启动时间的,哪些操作不是需要的:
执行计划运算类型 | 操作说明 | 是否有启动时间 |
---|---|---|
Seq Scan | 扫描表 | 无启动时间 |
Index Scan | 索引扫描 | 无启动时间 |
Bitmap Index Scan | 索引扫描 | 有启动时间 |
Bitmap Heap Scan | 索引扫描 | 有启动时间 |
Subquery Scan | 子查询 | 无启动时间 |
Tid Scan | ctid = …条件 | 无启动时间 |
Function Scan | 函数扫描 | 无启动时间 |
Nested Loop | 循环结合 | 无启动时间 |
Merge Join | 合并结合 | 有启动时间 |
Hash Join | 哈希结合 | 有启动时间 |
Sort | 排序,ORDER BY操作 | 有启动时间 |
Hash | 哈希运算 | 有启动时间 |
Result | 函数扫描,和具体的表无关 | 无启动时间 |
Unique | DISTINCT,UNION操作 | 有启动时间 |
Limit | LIMIT,OFFSET操作 | 有启动时间 |
Aggregate | count, sum,avg, stddev集约函数 | 有启动时间 |
Group | GROUP BY分组操作 | 有启动时间 |
Append | UNION操作 | 无启动时间 |
Materialize | 子查询 | 有启动时间 |
SetOp | INTERCECT,EXCEPT | 有启动时 |
explain select distinct course_id from course where course_term = 'Fal02';
NOTICE: QUERY PLAN:
Unique (cost=12223.09..12339.76 rows=4667 width=4)
-> Sort (cost=12223.09..12223.09 rows=46666 width=4)
-> Seq Scan on course (cost=0.00..8279.99 rows=46666 width=4)
1.从下往上读
2.explain报告查询的操作,开启的消耗,查询总的消耗,访问的行数 访问的平均宽度
3.开启时间消耗是输出开始前的时间例如排序的时间
4.消耗包括磁盘检索页,cpu时间
5.注意,每一步的cost包括上一步的
6.重要的是,explain 不是真正的执行一次查询 只是得到查询执行的计划和估计的花费
索引有用条件 当满足特定条件的元组数小于总的数目