发现公司业务在时序类、流水类业务场景越来越多，对数据治理的需求越来越大，这里整理介绍写PostgreSQL分区表的应用方法。
一、分区表的作用
1.将数据按指定的方法打算到子分区，提高SQL性能。
2.解决时序类、流水类业务大表在进行老旧数据清理时delete引起的性能及磁盘空间碎片问题。
3.利用子分区卸载、重新挂载功能，对数据进行暂时性的隐藏、维护。
4.数据归档治理业务场景：定期增加子分区、定期删除不需要的子分区来对数据进行滑窗处理，保持业务系统瘦身。
5.添加子分区对业务透明，业务逻辑上只需要访问父表即可。
二、业务场景举例
以大型电商平台为例，通常订单类的信息都比较庞大，假设订单表tab_orders的数据量是100G，单表10亿数据量，业务需要统计某个区域内订单的平均额度，往往会消耗比较漫长的时间：
select avg(total_amount) from tab_orders where state_code=1;
如果我们能够把大表分拆成小表，查询数据的时候，只扫描数据所属的小表，就能大大降低扫描时间，提高查询速度。
如果采用分布式架构，比如分10个分片，那么单个分片依旧有1亿条数据，对于常规数据库来说，依然容易出现严重性能问题。
此时，我们可以在分布式架构的基础上，对业务大表再进行分区，那么单个分片的数据就会进一步被打散。
PostgreSQL的分区表可以用来解决此类问题，适用于集中式和分布式架构。解决方式是：
创建一个表tab_orders，作为分区表的父表，再创建50个子分区:
tab_orders_1, tab_orders_2, …, tab_orders_50，
这样每一个分区对应一个城市的数据，分区的数据量平均是2G，如果是分布式架构，那么单个分片内，单个子分区就是0.1G，200w的数据量，如果单表是百亿数据量，如果还嫌子分区数据量太大，我们可以继续进行二级、三级、四级…..多级分区
注：pg分区表分区方法和分区层级不限。
在本例中，这50分区联合在一起，组成分区父表tab_orders。
这里的分区父表和子分区表都是实实在在的表，和传统的分库分表不一样，分区表可以保持原普通表的查询语句保持不变，对业务透明，如下：
select avg(total_amount) from tab_orders where state_code=1;
PostgreSQL通过对执行语句的分析处理，最终把扫描的任务定位在分区tab_order_1上，自动把查询语句转换成下面的语句，其他分区根本不需要扫描，这就是分区裁剪技术。
select avg(total_amount) from tab_orders_1;
三、分区表分区方法
1.pg分区表支持range、list、hash（pg11版本及以上）三种主要分区方法
2.pg分区表的分区级数不限、方法不限：即一级分区下面可以进行二级分区，二级分区下面还可以进行3及分区……..
四、分区表使用注意事项及技巧
1.分区表中分区键和分布式的分布键一样，不允许对分区键字段进行update操作。
2.分区表中建议规范所有唯一性约束必须包含分区键。
1）分区父表的主键必须包含分区字段；
2）唯一索引必须包含分区字段
3.分区键的选择技巧：让分区键尽可能地出现在select、delete、update语句的where条件，以发挥分区裁剪的作用来加速SQL性能。
4.在insert语句中，需在字段列表中指定分区键，如：insert into tab_aken(id,part_col) values(1,’2021-10-16′);
5.子分区数量不宜过多，现网使用中发现子分区1000个和子分区300个两者的性能有较大差别。
五、分区表创建方法
1.range范围分区表例子：PARTITION BY RANGE (分区键字段);
1）.创建父表：（pg-12版本）
–如下使用时间字段info_time作为分区键，使用范围分区方法进行分区
CREATE TABLE tab_aken (
uid integer NOT NULL,
info_time timestamp NOT NULL,
money decimal(5,2) NOT NULL,
primary key (uid,info_time)
) PARTITION BY RANGE (info_time);
2）.按月分区 （pg-12版本）
–方法1：直接添加。如下添加3个子分区
CREATE TABLE aken_2020_1 PARTITION of tab_aken FOR VALUES FROM ('2020-1-01') TO ('2020-1-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_2 PARTITION of tab_aken FOR VALUES FROM ('2020-2-01') TO ('2020-2-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_3 PARTITION of tab_aken FOR VALUES FROM ('2020-3-01') TO ('2020-3-01'::timestamp + interval '1 month');
–方法2：使用generate_series函数，按月创建12个子表，拼接SQL如下：
psql -At -h 9.22.xx.xxx -p xxx -U dbmgr -d akendb -c 'SELECT 'CREATE TABLE aken_2020_' || p_month || ' PARTITION of tab_aken FOR VALUES FROM (''2020-'||p_month||'-01'') TO (''2020-'||p_month||'-01''::timestamp + interval ''1 month'');' FROM generate_series(1,12) as p_month ;' | psql -h 9.22.xx.xxx -p xxx -U dbmgr -d akendb
?column?
-------------------------------------------------------------------------------------------------------------------------------
CREATE TABLE aken_2020_1 PARTITION of tab_aken FOR VALUES FROM ('2020-1-01') TO ('2020-1-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_2 PARTITION of tab_aken FOR VALUES FROM ('2020-2-01') TO ('2020-2-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_3 PARTITION of tab_aken FOR VALUES FROM ('2020-3-01') TO ('2020-3-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_4 PARTITION of tab_aken FOR VALUES FROM ('2020-4-01') TO ('2020-4-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_5 PARTITION of tab_aken FOR VALUES FROM ('2020-5-01') TO ('2020-5-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_6 PARTITION of tab_aken FOR VALUES FROM ('2020-6-01') TO ('2020-6-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_7 PARTITION of tab_aken FOR VALUES FROM ('2020-7-01') TO ('2020-7-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_8 PARTITION of tab_aken FOR VALUES FROM ('2020-8-01') TO ('2020-8-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_9 PARTITION of tab_aken FOR VALUES FROM ('2020-9-01') TO ('2020-9-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_10 PARTITION of tab_aken FOR VALUES FROM ('2020-10-01') TO ('2020-10-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_11 PARTITION of tab_aken FOR VALUES FROM ('2020-11-01') TO ('2020-11-01'::timestamp + interval '1 month');
CREATE TABLE aken_2020_12 PARTITION of tab_aken FOR VALUES FROM ('2020-12-01') TO ('2020-12-01'::timestamp + interval '1 month');
(12 rows)
akendb=#
3）.查看分区表结构：可以看到父表下有12张分区表
akendb=# \d+ tab_aken
Partitioned table 'public.aken'
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-------------+-----------------------------+-----------+----------+---------+---------+--------------+-------------
sensor_id | integer | | not null | | plain | |
ptime | timestamp without time zone | | not null | | plain | |
temperature | numeric(5,2) | | not null | | main | |
Partition key: RANGE (ptime)
Indexes:
'aken_pkey' PRIMARY KEY, btree (sensor_id, ptime)
Partitions: aken_2020_1 FOR VALUES FROM ('2020-01-01 00:00:00') TO ('2020-02-01 00:00:00'),
aken_2020_10 FOR VALUES FROM ('2020-10-01 00:00:00') TO ('2020-11-01 00:00:00'),
aken_2020_11 FOR VALUES FROM ('2020-11-01 00:00:00') TO ('2020-12-01 00:00:00'),
aken_2020_12 FOR VALUES FROM ('2020-12-01 00:00:00') TO ('2021-01-01 00:00:00'),
aken_2020_2 FOR VALUES FROM ('2020-02-01 00:00:00') TO ('2020-03-01 00:00:00'),
aken_2020_3 FOR VALUES FROM ('2020-03-01 00:00:00') TO ('2020-04-01 00:00:00'),
aken_2020_4 FOR VALUES FROM ('2020-04-01 00:00:00') TO ('2020-05-01 00:00:00'),
aken_2020_5 FOR VALUES FROM ('2020-05-01 00:00:00') TO ('2020-06-01 00:00:00'),
aken_2020_6 FOR VALUES FROM ('2020-06-01 00:00:00') TO ('2020-07-01 00:00:00'),
aken_2020_7 FOR VALUES FROM ('2020-07-01 00:00:00') TO ('2020-08-01 00:00:00'),
aken_2020_8 FOR VALUES FROM ('2020-08-01 00:00:00') TO ('2020-09-01 00:00:00'),
aken_2020_9 FOR VALUES FROM ('2020-09-01 00:00:00') TO ('2020-10-01 00:00:00')
4）查询分区表数据
akendb=# select * from tab_aken where time_col >= '2020-05-08 11:20:16'::timestamp and time_col <= '2020-05-10 16:00:00'::timestamp;
上述语句直接查询父表，DB优化器会自动优化只查询tab_aken_2020_5即5月份这个子分区的数据，直接过滤掉其他分区，从而提高查询性能。
2.hash分区表创建例子：PARTITION BY HASH(分区键字段)
1）.创建父表
CREATE TABLE tab_aken (
userid int4,
username character varying(64),
ctime timestamp(6) without time zone,
primary key(userid)) --注意：如果是pg10版本，不允许在分区表中指定主键
PARTITION BY HASH(userid); --这里表示使用userid作为分区键，使用hash进行分区
2）.创建子分区表：方法1
–如下添加16个子分区，即创建16个子分区表:
psql -At postgres postgres -c 'SELECT 'CREATE TABLE tab_aken_' || n || ' PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER ' || n || ');' FROM generate_series(0,15) as n ;' | psql
?column?
--------------------------------------------------------------------------------------------
CREATE TABLE tab_aken_0 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 0);
CREATE TABLE tab_aken_1 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 1);
CREATE TABLE tab_aken_2 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 2);
CREATE TABLE tab_aken_3 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 3);
CREATE TABLE tab_aken_4 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 4);
CREATE TABLE tab_aken_5 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 5);
CREATE TABLE tab_aken_6 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 6);
CREATE TABLE tab_aken_7 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 7);
CREATE TABLE tab_aken_8 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 8);
CREATE TABLE tab_aken_9 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 9);
CREATE TABLE tab_aken_10 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 10);
CREATE TABLE tab_aken_11 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 11);
CREATE TABLE tab_aken_12 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 12);
CREATE TABLE tab_aken_13 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 13);
CREATE TABLE tab_aken_14 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 14);
CREATE TABLE tab_aken_15 PARTITION of tab_aken FOR VALUES WITH (MODULUS 16, REMAINDER 15);
(16 rows)
db_aken=#
3）.创建子分区表：方法2
–如下创建1024个子分区
do language plpgsql $$
declare
begin
for i in 0..1023 loop
execute format('create table tab_aken_%s partition of tab_aken_ for values with (MODULUS %s, REMAINDER %s)', i, 1024, i);
end loop;
end;
$$;
六、为分区表创建索引
–在父表创建索引即可，PostgreSQL会自动在所有子分区创建对应的索引
akendb=# create index idx_sensor_id on aken using btree(sensor_id);
CREATE INDEX
akendb=# \d+ aken
Partitioned table 'public.aken'
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-------------+-----------------------------+-----------+----------+---------+---------+--------------+-------------
sensor_id | integer | | not null | | plain | |
ptime | timestamp without time zone | | not null | | plain | |
temperature | numeric(5,2) | | not null | | main | |
Partition key: RANGE (ptime)
Indexes:
'aken_pkey' PRIMARY KEY, btree (sensor_id, ptime)
'idx_sensor_id' btree (sensor_id)
Partitions: aken_2020_1 FOR VALUES FROM ('2020-01-01 00:00:00') TO ('2020-02-01 00:00:00'),
aken_2020_11 FOR VALUES FROM ('2020-11-01 00:00:00') TO ('2020-12-01 00:00:00'),
aken_2020_12 FOR VALUES FROM ('2020-12-01 00:00:00') TO ('2021-01-01 00:00:00'),
aken_2020_2 FOR VALUES FROM ('2020-02-01 00:00:00') TO ('2020-03-01 00:00:00'),
aken_2020_3 FOR VALUES FROM ('2020-03-01 00:00:00') TO ('2020-04-01 00:00:00'),
aken_2020_4 FOR VALUES FROM ('2020-04-01 00:00:00') TO ('2020-05-01 00:00:00'),
aken_2020_5 FOR VALUES FROM ('2020-05-01 00:00:00') TO ('2020-06-01 00:00:00'),
aken_2020_6 FOR VALUES FROM ('2020-06-01 00:00:00') TO ('2020-07-01 00:00:00'),
aken_2020_7 FOR VALUES FROM ('2020-07-01 00:00:00') TO ('2020-08-01 00:00:00'),
aken_2020_8 FOR VALUES FROM ('2020-08-01 00:00:00') TO ('2020-09-01 00:00:00'),
aken_2020_9 FOR VALUES FROM ('2020-09-01 00:00:00') TO ('2020-10-01 00:00:00')
akendb=# \d+ aken_2020_6
Table 'public.aken_2020_6'
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-------------+-----------------------------+-----------+----------+---------+---------+--------------+-------------
sensor_id | integer | | not null | | plain | |
ptime | timestamp without time zone | | not null | | plain | |
temperature | numeric(5,2) | | not null | | main | |
Partition of: aken FOR VALUES FROM ('2020-06-01 00:00:00') TO ('2020-07-01 00:00:00')
Partition constraint: ((ptime IS NOT NULL) AND (ptime >= '2020-06-01 00:00:00'::timestamp without time zone) AND (ptime < '2020-07-01 00:00:00'::timestamp without time zone))
Indexes:
'aken_2020_6_pkey' PRIMARY KEY, btree (sensor_id, ptime)
'aken_2020_6_sensor_id_idx' btree (sensor_id)
Access method: heap
akendb=#
七、利用分区表进行数据维护：删除分区、添加分区、卸载分区（隐藏分区）、重新挂载分区
1.删除子分区
–大表数据维护，mysql、PostgreSQL、Oracle等关系型DB不建议使用delete操作，对性能影响较大。
–后期如果不需要某个时间段的数据，直接drop对应的子分区即可，不影响全表，对业务透明。
–当需要清理冷旧数据时，直接drop子分区即可，无需使用delete这种比较损耗性能的操作。
1)首先，查看父表tab_aken当前有哪些子分区：
akendb=# select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric)from pg_class where relname like 'tab_aken_part_%' order by 2;
relname | split_part
-----------------+------------
tab_aken_part_1 | 1
tab_aken_part_2 | 2
tab_aken_part_3 | 3
tab_aken_part_4 | 4
tab_aken_part_5 | 5
tab_aken_part_6 | 6
tab_aken_part_7 | 7
tab_aken_part_8 | 8
tab_aken_part_9 | 9
(9 rows)
2).删除目标子分区：
–拼接方法，可以放到定期任务里面，如每次删除前面N个子分区（limit N）
–如下拼接删除2个最早的子分区
akendb=# select 'drop table '||string_agg(relname, ',')||';' as drop_target_child_partitions from ( select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric) from pg_class where relname like 'tab_aken_part%' order by 2 limit 2 ) as aaa;
drop_target_partitions
---------------------------------------------
drop table tab_aken_part_1,tab_aken_part_2;
(2 row)
akendb=# drop table tab_aken_part_1,tab_aken_part_2;
DROP TABLE
akendb=# select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric)from pg_class where relname like 'tab_aken_part_%' order by 2;
relname | split_part
-----------------+------------
tab_aken_part_3 | 3
tab_aken_part_4 | 4
tab_aken_part_5 | 5
tab_aken_part_6 | 6
tab_aken_part_7 | 7
tab_aken_part_8 | 8
tab_aken_part_9 | 9
(7 rows)
akendb=# select 'drop table '||string_agg(relname, ',')||';' as drop_target_child_partitions from ( select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric) from pg_class where relname like 'tab_aken_part%' order by 2 limit 2 ) as aaa;
drop_target_partitions
---------------------------------------------
drop table tab_aken_part_3,tab_aken_part_4;
(1 row)
akendb=# drop table tab_aken_part_3,tab_aken_part_4;
DROP TABLE
akendb=# select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric) from pg_class where relname like 'tab_aken_part_%' order by 2;
relname | split_part
-----------------+------------
tab_aken_part_5 | 5
tab_aken_part_6 | 6
tab_aken_part_7 | 7
tab_aken_part_8 | 8
tab_aken_part_9 | 9
(5 rows)
akendb=#
2.添加子分区
–增加子分区主要是为了承接超出已有子分区范围的业务新数据入库
如下当前父表已有子分区：
akendb=# select * from pg_tables where tablename like 'tab_aken%' order by tablename;
schemaname | tablename | tableowner | tablespace | hasindexes | hasrules | hastriggers | rowsecurity
------------+-----------------+------------+------------+------------+----------+-------------+-------------
public | tab_aken | dbmgr | | t | f | f | f
public | tab_aken_part_1 | dbmgr | | t | f | f | f
public | tab_aken_part_2 | dbmgr | | t | f | f | f
public | tab_aken_part_3 | dbmgr | | t | f | f | f
(3rows)
akendb=#
添加子分区方法1：从最大子分区后面直接添加
–如下给按range分区的父表添加3个月的子分区
akendb=# alter table tab_aken add partitions 3; --默认会自动从最大的子分区后面添加3个子分区
ALTER TABLE
akendb=# select * from pg_tables where tablename like 'tab_aken%' order by tablename;
schemaname | tablename | tableowner | tablespace | hasindexes | hasrules | hastriggers | rowsecurity
------------+-----------------+------------+------------+------------+----------+-------------+-------------
public | tab_aken | dbmgr | | t | f | f | f
public | tab_aken_part_1 | dbmgr | | t | f | f | f
public | tab_aken_part_2 | dbmgr | | t | f | f | f
public | tab_aken_part_3 | dbmgr | | t | f | f | f
public | tab_aken_part_4 | dbmgr | | t | f | f | f
public | tab_aken_part_5 | dbmgr | | t | f | f | f
public | tab_aken_part_6 | dbmgr | | t | f | f | f
(6rows)
akendb=#
添加子分区方法2：指定分区范围添加
CREATE TABLE aken_2020_7 PARTITION of aken FOR VALUES FROM ('2022-6-01') TO ('2020-6-01'::timestamp + interval '1 month');
3.卸载子分区（隐藏子分区）、解绑子分区、重新绑定子分区
相对于drop子分区，推荐先暂时将子分区从父表中移除的方式，当后续发现还需要子分区的数据，重新将子分区挂载回来即可。
1）卸载子分区（或叫解绑子分区）
akendb=# alter table tab_aken detach partition aken_2020_6;
ALTER TABLE
akendb=# \d+ tab_aken
Partitioned table 'public.tab_aken'
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-----------+-------------+-----------+----------+---------+---------+--------------+-------------
sensor_id | integer | | not null | | plain | |
ptime | timestamp without time zone | | not null | | plain | |
temperature | numeric(5,2) | | not null | | main | |
Partition key: RANGE (ptime)
Indexes:
'aken_pkey' PRIMARY KEY, btree (sensor_id, ptime)
'idx_sensor_id' btree (sensor_id)
Partitions: aken_2020_1 FOR VALUES FROM ('2020-01-01 00:00:00') TO ('2020-02-01 00:00:00'),
aken_2020_11 FOR VALUES FROM ('2020-11-01 00:00:00') TO ('2020-12-01 00:00:00'),
aken_2020_12 FOR VALUES FROM ('2020-12-01 00:00:00') TO ('2021-01-01 00:00:00'),
aken_2020_2 FOR VALUES FROM ('2020-02-01 00:00:00') TO ('2020-03-01 00:00:00'),
aken_2020_3 FOR VALUES FROM ('2020-03-01 00:00:00') TO ('2020-04-01 00:00:00'),
aken_2020_4 FOR VALUES FROM ('2020-04-01 00:00:00') TO ('2020-05-01 00:00:00'),
aken_2020_5 FOR VALUES FROM ('2020-05-01 00:00:00') TO ('2020-06-01 00:00:00'),
aken_2020_7 FOR VALUES FROM ('2020-07-01 00:00:00') TO ('2020-08-01 00:00:00'),
aken_2020_8 FOR VALUES FROM ('2020-08-01 00:00:00') TO ('2020-09-01 00:00:00'),
aken_2020_9 FOR VALUES FROM ('2020-09-01 00:00:00') TO ('2020-10-01 00:00:00')
akendb=#
和直接DROP相比，该方式仅仅是使子表脱离了原有的主表，而存储在子表中的数据仍然可以得到访问，因为此时该子表变成了一个普通的数据表:select * from tab_xxx(子分区表名)。
这样无论对DBA还是业务来说，就可以在此时对该表进行必要的维护操作，如数据清理、归档等。
在完成诸多例行性的操作之后，可以考虑是否直接删除该表(DROP TABLE)，还是先清空该表的数据(TRUNCATE TABLE)，或者让该表重新绑定主表。
2）重新挂载子分区
akendb=# ALTER TABLE tab_aken ATTACH PARTITION aken_2020_6 FOR VALUES FROM ('2020-06-01 00:00:00') TO ('2020-07-01 00:00:00');
ALTER TABLE
akendb=# \d+ tab_aken
Partitioned table 'public.tab_aken'
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
-------------+-----------------------------+-----------+----------+---------+---------+--------------+-------------
sensor_id | integer | | not null | | plain | |
ptime | timestamp without time zone | | not null | | plain | |
temperature | numeric(5,2) | | not null | | main | |
Partition key: RANGE (ptime)
Indexes:
'aken_pkey' PRIMARY KEY, btree (sensor_id, ptime)
'idx_sensor_id' btree (sensor_id)
Partitions: aken_2020_1 FOR VALUES FROM ('2020-01-01 00:00:00') TO ('2020-02-01 00:00:00'),
aken_2020_11 FOR VALUES FROM ('2020-11-01 00:00:00') TO ('2020-12-01 00:00:00'),
aken_2020_12 FOR VALUES FROM ('2020-12-01 00:00:00') TO ('2021-01-01 00:00:00'),
aken_2020_2 FOR VALUES FROM ('2020-02-01 00:00:00') TO ('2020-03-01 00:00:00'),
aken_2020_3 FOR VALUES FROM ('2020-03-01 00:00:00') TO ('2020-04-01 00:00:00'),
aken_2020_4 FOR VALUES FROM ('2020-04-01 00:00:00') TO ('2020-05-01 00:00:00'),
aken_2020_5 FOR VALUES FROM ('2020-05-01 00:00:00') TO ('2020-06-01 00:00:00'),
aken_2020_6 FOR VALUES FROM ('2020-06-01 00:00:00') TO ('2020-07-01 00:00:00'), <<<<<子分区6已重新绑定到父表
aken_2020_7 FOR VALUES FROM ('2020-07-01 00:00:00') TO ('2020-08-01 00:00:00'),
aken_2020_8 FOR VALUES FROM ('2020-08-01 00:00:00') TO ('2020-09-01 00:00:00'),
aken_2020_9 FOR VALUES FROM ('2020-09-01 00:00:00') TO ('2020-10-01 00:00:00')
akendb=#
4.查看子分区
select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric) from pg_class where relname like 'tab_aken_part_%' order by 2;
--split_part函数指定分隔符切割目标字符串，如 target_text=“name.cn.com” split_part(target_text,’.’,3) 切割结果为：com
--cast(target_val as numeric)相当于target_val::numeric，即cast(t_val as t_datatype)
akendb=# select relname, cast(split_part(relname,'tab_aken_part_', 2) as numeric) from pg_class where relname like 'tab_aken_part_%' order by 2;
relname | split_part
-----------------+------------
tab_aken_part_1 | 1
tab_aken_part_2 | 2
tab_aken_part_3 | 3
tab_aken_part_4 | 4
tab_aken_part_5 | 5
tab_aken_part_6 | 6
tab_aken_part_7 | 7
tab_aken_part_8 | 8
tab_aken_part_9 | 9
(9 rows)
akendb=#
原创文章，作者：奋斗，如若转载，请注明出处：https://blog.ytso.com/tech/database/237195.html