postgresql數據庫中間件pgoneproxy支持二級分庫分表

  在不少場景中須要按照多個字段來進行分庫分表，好比在電信行業中，通常會根據用戶號碼以及時間（好比月份）來存儲用戶通訊產生的數據。今天就給你們講講，怎麼使用pgoneproxy來實現這個功能。如今假設用戶號碼就是int 型的id號，下面的配置中先根據id進行分表，在根據時間tt進行分表。

[
	{
        "table"  : "bigtest",
        "pkey"   :  "id",
        "type"   :  "int",
        "method" :  "crc32",
        "partitions":
        [
                {"suffix":"_0", "group":"data1"},
                {"suffix":"_1", "group":"data1"}
        ],
        "subpkey":"tt",
        "subtype":"timestamp",
        "submethod":"buffer",
        "subpartitions":
        [
                {"suffix":"_2015", "group":"data1", "minval":"1997-01-01 00:00:00", "maxval":"2015-01-01 00:00:00"},
                {"suffix":"_2037", "group":"data1", "minval":"2015-01-01 00:00:01", "maxval":"2037-01-01 00:00:00"}
        ]
        
        
  }
]

上面經過crc32來針對ID進行分表，存儲到後綴爲_0,_1的表中。在經過buffer的方式來針對時間字段tt來把數據存儲到對應後綴的表中。經過上面的配置，在數據庫表中會產生以下的四張表：

pgbench=> \dt;
              List of relations
 Schema |       Name       | Type  |  Owner   
--------+------------------+-------+----------
 public | bigtest_0_2015   | table | db_user
 public | bigtest_0_2037   | table | db_user
 public | bigtest_1_2015   | table | db_user
 public | bigtest_1_2037   | table | db_user

即小於2015-01-01 00:00:00的數據存放到後綴爲2015的表中，其餘的數據存放到2037的表中。若是想根據更加具體的時間來分表，則能夠經過修改subpartitiions來作到。

下面經過具體的操做來看看實現狀況：

pgbench=> \dt;
              List of relations
 Schema |       Name       | Type  |  Owner   
--------+------------------+-------+----------
 public | pgbench_accounts | table | postgres
 public | pgbench_branches | table | postgres
 public | pgbench_history  | table | postgres
 public | pgbench_tellers  | table | postgres
(4 rows)

pgbench=> create table bigtest(id int, name varchar(1024), age int, tt timestamp);
CREATE 0
pgbench=> \dt;
              List of relations
 Schema |       Name       | Type  |  Owner   
--------+------------------+-------+----------
 public | bigtest_0_2015   | table | db_user
 public | bigtest_0_2037   | table | db_user
 public | bigtest_1_2015   | table | db_user
 public | bigtest_1_2037   | table | db_user
 public | pgbench_accounts | table | postgres
 public | pgbench_branches | table | postgres
 public | pgbench_history  | table | postgres
 public | pgbench_tellers  | table | postgres
(8 rows)

pgbench=> insert into bigtest(id, name, age, tt) values(0, 'name0', 30, '2001-01-01 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(1, 'name1', 31, '2002-01-01 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(2, 'name2', 32, '2012-11-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(3, 'name3', 33, '2012-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(4, 'name4', 34, '2013-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(5, 'name5', 35, '2014-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(6, 'name6', 36, '2016-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(7, 'name7', 37, '2017-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(8, 'name8', 38, '2018-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(9, 'name9', 39, '2012-12-11 00:00:00');
INSERT 0 1
pgbench=> insert into bigtest(id, name, age, tt) values(10, 'name10', 40, '2022-12-11 00:00:00');
INSERT 0 1
pgbench=> \dt;
              List of relations
 Schema |       Name       | Type  |  Owner   
--------+------------------+-------+----------
 public | bigtest_0_2015   | table | db_user
 public | bigtest_0_2037   | table | db_user
 public | bigtest_1_2015   | table | db_user
 public | bigtest_1_2037   | table | db_user
 public | pgbench_accounts | table | postgres
 public | pgbench_branches | table | postgres
 public | pgbench_history  | table | postgres
 public | pgbench_tellers  | table | postgres
(8 rows)

pgbench=> select * from bigtest_0_2015;
 id | name  | age |         tt          
----+-------+-----+---------------------
  0 | name0 |  30 | 2001-01-01 00:00:00
  2 | name2 |  32 | 2012-11-11 00:00:00
  4 | name4 |  34 | 2013-12-11 00:00:00
(3 rows)

pgbench=> select * from bigtest_0_2037;
 id |  name  | age |         tt          
----+--------+-----+---------------------
  6 | name6  |  36 | 2016-12-11 00:00:00
  8 | name8  |  38 | 2018-12-11 00:00:00
 10 | name10 |  40 | 2022-12-11 00:00:00
(3 rows)

pgbench=> select * from bigtest_1_2015;
 id | name  | age |         tt          
----+-------+-----+---------------------
  1 | name1 |  31 | 2002-01-01 00:00:00
  3 | name3 |  33 | 2012-12-11 00:00:00
  5 | name5 |  35 | 2014-12-11 00:00:00
  9 | name9 |  39 | 2012-12-11 00:00:00
(4 rows)

pgbench=> select * from bigtest_1_2037;
 id | name  | age |         tt          
----+-------+-----+---------------------
  7 | name7 |  37 | 2017-12-11 00:00:00
(1 row)

pgbench=> select * from bigtest;
 id |  name  | age |         tt          
----+--------+-----+---------------------
  0 | name0  |  30 | 2001-01-01 00:00:00
  2 | name2  |  32 | 2012-11-11 00:00:00
  4 | name4  |  34 | 2013-12-11 00:00:00
  6 | name6  |  36 | 2016-12-11 00:00:00
  8 | name8  |  38 | 2018-12-11 00:00:00
 10 | name10 |  40 | 2022-12-11 00:00:00
  1 | name1  |  31 | 2002-01-01 00:00:00
  3 | name3  |  33 | 2012-12-11 00:00:00
  5 | name5  |  35 | 2014-12-11 00:00:00
  9 | name9  |  39 | 2012-12-11 00:00:00
  7 | name7  |  37 | 2017-12-11 00:00:00
(11 rows)

pgbench=> select * from bigtest where id = 0;
 id | name  | age |         tt          
----+-------+-----+---------------------
  0 | name0 |  30 | 2001-01-01 00:00:00
(1 row)

pgbench=> select * from bigtest where tt < '2015-01-01 00:00:00';
 id | name  | age |         tt          
----+-------+-----+---------------------
  0 | name0 |  30 | 2001-01-01 00:00:00
  2 | name2 |  32 | 2012-11-11 00:00:00
  4 | name4 |  34 | 2013-12-11 00:00:00
  1 | name1 |  31 | 2002-01-01 00:00:00
  3 | name3 |  33 | 2012-12-11 00:00:00
  5 | name5 |  35 | 2014-12-11 00:00:00
  9 | name9 |  39 | 2012-12-11 00:00:00
(7 rows)

pgbench=> select * from bigtest where tt > '2015-01-01 00:00:00';
 id |  name  | age |         tt          
----+--------+-----+---------------------
  6 | name6  |  36 | 2016-12-11 00:00:00
  8 | name8  |  38 | 2018-12-11 00:00:00
 10 | name10 |  40 | 2022-12-11 00:00:00
  7 | name7  |  37 | 2017-12-11 00:00:00
(4 rows)

pgbench=> select * from bigtest where tt > '2015-01-01 00:00:00' and tt < '2018-01-01 00:00:00';
 id | name  | age |         tt          
----+-------+-----+---------------------
  6 | name6 |  36 | 2016-12-11 00:00:00
  7 | name7 |  37 | 2017-12-11 00:00:00
(2 rows)

pgbench=> select * from bigtest where tt > '2014-01-01 00:00:00' and tt < '2015-01-01 00:00:00';
 id | name  | age |         tt          
----+-------+-----+---------------------
  5 | name5 |  35 | 2014-12-11 00:00:00
(1 row)

pgbench=>

上面展現了重新建表，插入數據，查詢數據的整個過程。從實驗結果看可以很好的支持上面講述的場景。