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postgresql----唯一索引,表达式索引,部分索引

时间:2016-07-01 01:08:35      阅读:529      评论:0      收藏:0      [点我收藏+]

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一.唯一索引

唯一索引字面上理解就是在索引上增加唯一约束,不允许出现索引值相同的行,目前只有Btree索引可以声明唯一索引,唯一键会自动创建唯一索引。

测试表:

 

test=# create table tbl_unique_index(a int, b int);
CREATE TABLE

 

 

 

示例1.创建唯一索引,相等数据只允许插入一行,NULL除外,因为NULL不等于NULL。

 

test=# create unique index idx_unq_tbl_unique_index_a_b on tbl_unique_index using btree (a,b);
CREATE INDEX
test=# \d tbl_unique_index 
Table "public.tbl_unique_index"
 Column |  Type   | Modifiers 
--------+---------+-----------
 a      | integer | 
 b      | integer | 
Indexes:
    "idx_unq_tbl_unique_index_a_b" UNIQUE, btree (a, b)

 

 

test=# insert into tbl_unique_index values (1,1);
INSERT 0 1
test=# insert into tbl_unique_index values (1,1);
ERROR:  duplicate key value violates unique constraint "idx_unq_tbl_unique_index_a_b"
DETAIL:  Key (a, b)=(1, 1) already exists.
test=# insert into tbl_unique_index values (1);
INSERT 0 1
test=# insert into tbl_unique_index values (1);
INSERT 0 1
test=# insert into tbl_unique_index values (1);
INSERT 0 1

 

示例2.唯一键会自动创建唯一索引

 

test=# truncate table tbl_unique_index ;
TRUNCATE TABLE
test=# alter table tbl_unique_index add constraint pk_tbl_unique_index_a primary key(a);
ALTER TABLE
test=# alter table tbl_unique_index add constraint uk_tbl_unique_index_b unique(b);
ALTER TABLE
test=# \d tbl_unique_index 
Table "public.tbl_unique_index"
 Column |  Type   | Modifiers 
--------+---------+-----------
 a      | integer | not null
 b      | integer | 
Indexes:
    "pk_tbl_unique_index_a" PRIMARY KEY, btree (a)
    "idx_unq_tbl_unique_index_a_b" UNIQUE, btree (a, b)
    "uk_tbl_unique_index_b" UNIQUE CONSTRAINT, btree (b)

 

二.表达式索引

除针对表的字段直接创建索引外,还可以对字段进行某种运算之后的结果创建索引。

测试表

test=# create table tbl_expression(a varchar(32), b varchar(32));
CREATE TABLE

 

test=# insert into tbl_expression select concat(test,x),concat(you,x) from generate_series(1,10000) x;
INSERT 0 10000

 

如果此时分别在a和b字段上各创建一个Btree索引,分别使用a和b字段查询时会进行索引扫描。

test=# create index idx_tbl_expression_a on tbl_expression using btree (a);
CREATE INDEX
test=# create index idx_tbl_expression_b on tbl_expression using btree (b);
CREATE INDEX
test=# 
test=# explain analyze select * from tbl_expression where a = TEST;
                                                              QUERY PLAN                                                             
 
-------------------------------------------------------------------------------------------------------------------------------------
-
 Index Scan using idx_tbl_expression_a on tbl_expression  (cost=0.29..8.30 rows=1 width=15) (actual time=0.130..0.130 rows=0 loops=1)
   Index Cond: ((a)::text = TEST::text)
 Planning time: 0.667 ms
 Execution time: 0.168 ms
(4 rows)

test=# explain analyze select * from tbl_expression where b = you;
                                                              QUERY PLAN                                                             
 
-------------------------------------------------------------------------------------------------------------------------------------
-
 Index Scan using idx_tbl_expression_b on tbl_expression  (cost=0.29..8.30 rows=1 width=15) (actual time=0.171..0.171 rows=0 loops=1)
   Index Cond: ((b)::text = you::text)
 Planning time: 0.126 ms
 Execution time: 0.206 ms
(4 rows)

 

但是下面的两种查询方式是不会进行索引扫描的

select * from tbl_expression where upper(a) = TEST;
select * from tbl_expression where (a ||   ||b) = test you;

 

test=# explain analyze select * from tbl_expression where upper(a) = TEST;
                                                 QUERY PLAN                                                 
------------------------------------------------------------------------------------------------------------
 Seq Scan on tbl_expression  (cost=0.00..166.00 rows=50 width=15) (actual time=5.957..5.957 rows=0 loops=1)
   Filter: (upper((a)::text) = TEST::text)
   Rows Removed by Filter: 10000
 Planning time: 0.140 ms
 Execution time: 6.014 ms
(5 rows)

test=# 
test=# explain analyze select * from tbl_expression where (a ||   ||b) = test you;
                                                 QUERY PLAN                                                 
------------------------------------------------------------------------------------------------------------
 Seq Scan on tbl_expression  (cost=0.00..191.00 rows=50 width=15) (actual time=7.851..7.851 rows=0 loops=1)
   Filter: ((((a)::text ||  ::text) || (b)::text) = test you::text)
   Rows Removed by Filter: 10000
 Planning time: 0.114 ms
 Execution time: 7.883 ms
(5 rows)

 

此时就可以使用表达式创建索引来解决此类全表扫描问题。

test=# explain analyze select * from tbl_expression where upper(a) = TEST;
                                                             QUERY PLAN                                                             
------------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on tbl_expression  (cost=4.67..21.42 rows=50 width=15) (actual time=0.133..0.133 rows=0 loops=1)
   Recheck Cond: (upper((a)::text) = TEST::text)
   ->  Bitmap Index Scan on idx_tbl_expression_upper_a  (cost=0.00..4.66 rows=50 width=0) (actual time=0.129..0.129 rows=0 loops=1)
         Index Cond: (upper((a)::text) = TEST::text)
 Planning time: 0.565 ms
 Execution time: 0.175 ms
(6 rows)

 

test=# create index idx_tbl_expression_a_b on tbl_expression ((a|| ||b));
CREATE INDEX
test=# explain analyze select * from tbl_expression where (a ||   ||b) = test you;
                                                           QUERY PLAN                                                           
--------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on tbl_expression  (cost=4.67..21.55 rows=50 width=15) (actual time=0.130..0.130 rows=0 loops=1)
   Recheck Cond: ((((a)::text ||  ::text) || (b)::text) = test you::text)
   ->  Bitmap Index Scan on idx_tbl_expression_a_b  (cost=0.00..4.66 rows=50 width=0) (actual time=0.128..0.128 rows=0 loops=1)
         Index Cond: ((((a)::text ||  ::text) || (b)::text) = test you::text)
 Planning time: 0.582 ms
 Execution time: 0.187 ms
(6 rows)

 

但是还是需要根据实际业务情况仔细评估后决定采用何种索引,因为并不是索引越多越好。

三.部分索引

只在自己感兴趣的那部分数据上创建索引,而不是对每一行数据都创建索引,此种方式创建索引就需要使用WHERE条件了。

创建两个完全相同的表比较部分索引和全索引的区别。

测试表

test=# create table tbl_partial_index(id bigint,alarm_time timestamp without time zone,level varchar(12),alarm_desc varchar(100));
CREATE TABLE
test=# create table tbl_partial_index1(id bigint,alarm_time timestamp without time zone,level varchar(12),alarm_desc varchar(100));
CREATE TABLE

 

写入完全相同的数据

test=# insert into tbl_partial_index(id,alarm_time,level,alarm_desc) 
select generate_series(1,9000000),clock_timestamp()::timestamp without time zone,green,正常; INSERT 0 9000000 test=# insert into tbl_partial_index(id,alarm_time,level,alarm_desc)
select generate_series(9000000,9000100),clock_timestamp()::timestamp without time zone,red,攻击; INSERT 0 101 test=# test=# test=# insert into tbl_partial_index1(id,alarm_time,level,alarm_desc)
select generate_series(1,9000000),clock_timestamp()::timestamp without time zone,green,正常; INSERT 0 9000000 test=# insert into tbl_partial_index1(id,alarm_time,level,alarm_desc)
select generate_series(9000000,9000100),clock_timestamp()::timestamp without time zone,red,攻击; INSERT 0 101

 

 

示例1.在tbl_partial_index表字段level上创建索引

 

test=# create index idx_tbl_partial_index_level on tbl_partial_index using btree (level);
CREATE INDEX
Time: 31407.356 ms
test=# 
test=# explain analyze select * from tbl_partial_index where level = red;
                                                                    QUERY PLAN                                                       
             
-------------------------------------------------------------------------------------------------------------------------------------
-------------
 Index Scan using idx_tbl_partial_index_level on tbl_partial_index  (cost=0.43..4.45 rows=1 width=29) (actual time=0.069..0.087 rows=
101 loops=1)
   Index Cond: ((level)::text = red::text)
 Planning time: 0.268 ms
 Execution time: 0.124 ms
(4 rows)

Time: 23.460 ms

 

 

test=# select relname,pg_size_pretty(pg_relation_size(oid)) from pg_class where relname=idx_tbl_partial_index_level;
           relname           | pg_size_pretty 
-----------------------------+----------------
 idx_tbl_partial_index_level | 191 MB
(1 row)

Time: 71.799 ms

 

 

示例2.在tbl_partial_index1表字段level等于red的行上创建索引

test=# create index idx_tbl_partial_index1_level on tbl_partial_index1(level) where level = red;
CREATE INDEX
Time: 5558.905 ms
test=# explain analyze select * from tbl_partial_index1 where level = red;
                                                                     QUERY PLAN                                                      
               
-------------------------------------------------------------------------------------------------------------------------------------
---------------
 Index Scan using idx_tbl_partial_index1_level on tbl_partial_index1  (cost=0.14..4.16 rows=1 width=29) (actual time=0.051..0.082 row
s=101 loops=1)
 Planning time: 18.922 ms
 Execution time: 0.136 ms
(3 rows)

Time: 19.929 ms

 

test=# select relname,pg_size_pretty(pg_relation_size(oid)) from pg_class where relname=idx_tbl_partial_index1_level;
           relname            | pg_size_pretty 
------------------------------+----------------
 idx_tbl_partial_index1_level | 64 kB
(1 row)

Time: 0.950 ms

 

比较上面两个示例的结果可知,全表索引在耗时和大小方面要比部分索引消耗更多的资源,查询‘red‘的数据排除环境影响基本相同,数据量更大,‘red‘占比更小时性能可能会有明显差异,但是查询非‘red‘数据时全表索引会有明显的性能优势,因为部分索引并没有‘green‘数据的索引,走的是全表扫描。

 

综上,根据数据的使用方式创建不同的索引在性能上是有明显差异的。

 

postgresql----唯一索引,表达式索引,部分索引

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原文地址:http://www.cnblogs.com/alianbog/p/5631505.html

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