加入收藏 | 设为首页 | 会员中心 | 我要投稿 淮北站长网 (https://www.0561zz.com/)- 科技、建站、经验、云计算、5G、大数据,站长网!
当前位置: 首页 > 综合聚焦 > 移动互联 > 通讯 > 正文

Mycat分片法则是怎么样的

发布时间:2021-12-20 10:29:26 所属栏目:通讯 来源:互联网
导读:Mycat分片规则是怎么样的,针对这个问题,这篇文章详细介绍了相对应的分析和解答,希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。 1.sharding-by-intfile hash分片 表对应的分片规则 Mycat分片规则是怎么样的 查看rule.xml查看对应的关系 t
Mycat分片规则是怎么样的,针对这个问题,这篇文章详细介绍了相对应的分析和解答,希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。
 
1.sharding-by-intfile
hash分片
表对应的分片规则
Mycat分片规则是怎么样的
查看rule.xml查看对应的关系
 
<tableRule name="sharding-by-intfile">
                <rule>
                        <columns>sharding_id</columns>   根据该字段分片
                        <algorithm>hash-int</algorithm>    分片的方法
                </rule>
        </tableRule>
 
查看rule.xml对应的方法
 
<function name="hash-int"
                class="io.mycat.route.function.PartitionByFileMap">
                <property name="mapFile">partition-hash-int.txt</property>   ---对应的文件
                <property name="defaultNode">1</property>
        </function>
 
查看文件
 
[root@localhost conf]# more partition-hash-int.txt
10000=0   ####sharding_id为10000发到1节点
10010=1   ####sharding_id为10010发到2节点
DEFAULT_NODE=1  ###其它插到2节点
 
 
 
 
实验
mysql> create table employee (id int not null primary key,name varchar(100),sharding_id int not null);
Query OK, 0 rows affected (0.02 sec)
 
mysql> insert into employee(id,name,sharding_id) values(2,'leader us',10000);
Query OK, 1 row affected (0.01 sec)
 
 
mysql> insert into employee(id,name,sharding_id) values(4,'leader us',10000);
Query OK, 1 row affected (0.00 sec)
 
 
mysql> insert into employee(id,name,sharding_id) values(3,'leader us',100003);               -----其它插到2节点
 
 
 
mysql> insert into employee(id,name,sharding_id) values(4,'leader us',10010);
Query OK, 1 row affected (0.01 sec)
 
 
mysql> insert into employee(id,name,sharding_id) values(5,'leader us',10010);
Query OK, 1 row affected (0.03 sec)
 
 
2.auto-sharding-long
范围分片
分片表如下:
 
<table name="travelrecord" dataNode="dn1,dn2,dn3" rule="auto-sharding-long" />
查看rule.xml对应的关系
 
<tableRule name="auto-sharding-long">
                <rule>
                        <columns>id</columns>
                        <algorithm>rang-long</algorithm>
                </rule>
        </tableRule>
对应的方法
 
<function name="rang-long"
                class="io.mycat.route.function.AutoPartitionByLong">
                <property name="mapFile">autopartition-long.txt</property>
        </function>
对应的文件:
 
# range start-end ,data node index
# K=1000,M=10000.
0-500M=0           #####范围0-500M插到第一个节点
500M-1000M=1       #####范围500m-1000M插到第2个节点
1000M-1500M=2      。。。类推
3.mod-log
取模分片
<table name="tt2" primaryKey="id" autoIncrement="true" dataNode="dn1,dn2,dn3" rule="mod-long" />
 
 fun:
 
 
 
<function name="mod-long" class="io.mycat.route.function.PartitionByMod">
                <!-- how many data nodes -->
                <property name="count">3</property>
        </function>
<tableRule name="mod-long">
                <rule>
                        <columns>id</columns>
                        <algorithm>mod-long</algorithm>
                </rule>
        </tableRule>
 
4. sharding-by-month
按月分片
tab:
 <table name="month_tab" primaryKey="id" autoIncrement="true" dataNode="dn1,dn2,dn3" rule="sharding-by-month" />
 
 
rule:
 
<tableRule name="sharding-by-month">
                <rule>
                        <columns>create_time</columns>
                        <algorithm>partbymonth</algorithm>
                </rule>
        </tableRule>
<function name="partbymonth"
                class="io.mycat.route.function.PartitionByMonth">
                <property name="dateFormat">yyyy-MM-dd</property>
                <property name="sBeginDate">2015-01-01</property>   ##开始时间
        </function>
 
测试:
mysql> insert into month_tab(id,name,sharding_id,create_time) values (1,'1',1,'2015-01-01');
Query OK, 1 row affected (0.43 sec)
 
mysql> insert into month_tab(id,name,sharding_id,create_time) values (2,'2',2,'2015-02-02');
Query OK, 1 row affected (0.01 sec)
 
mysql> insert into month_tab(id,name,sharding_id,create_time) values (3,'3',3,'2015-03-03');
Query OK, 1 row affected (0.49 sec)
 
mysql> insert into month_tab(id,name,sharding_id,create_time) values (4,'4',4,'2015-04-04');   ###按月分片,只有三个节点,只能插到1,2,3月份的,4月份就开始报错了
ERROR 1064 (HY000): Can't find a valid data node for specified node index :MONTH_TAB -> CREATE_TIME -> 2015-04-04 -> Index : 3
5 sharding-by-day
按日分片(1.6默认文件都没写,自己配置的)
tab:
<table name="day_tab" primaryKey="ID" dataNode="dn1,dn2,dn3" rule="sharding-by-day"/>
rule:
 
<tableRule name="sharding-by-day">
                <rule>
                        <columns>create_time</columns>
                        <algorithm>partbyday</algorithm>
                </rule>
        </tableRule>
<function name="partbyday"
                class="io.mycat.route.function.PartitionByDate">
                <property name="dateFormat">yyyy-MM-dd</property>
                <property name="sBeginDate">2015-01-01</property>    ###起始日期
                <property name="sPartionDay">3</property>            ###多少天后开始分片
        </function>
测试:
插了前9天,分到三个分片
mysql> select * from day_tab;
+----+------+-------------+---------------------+
| id | name | sharding_id | create_time         |
+----+------+-------------+---------------------+
|  7 | 1    |           1 | 2015-01-08 00:00:00 |
|  8 | 1    |           1 | 2015-01-09 00:00:00 |
| 13 | 1    |           1 | 2015-01-07 00:00:00 |
|  7 | 1    |           1 | 2015-01-01 00:00:00 |
|  8 | 1    |           1 | 2015-01-02 00:00:00 |
|  9 | 1    |           1 | 2015-01-03 00:00:00 |
| 10 | 1    |           1 | 2015-01-04 00:00:00 |
| 11 | 1    |           1 | 2015-01-05 00:00:00 |
| 12 | 1    |           1 | 2015-01-06 00:00:00 |
+----+------+-------------+---------------------+
9 rows in set (0.01 sec)
 
mysql> insert into day_tab(id,name,sharding_id,create_time) values (17,'1',1,'2015-01-10'),(18,'1',1,'2015-01-11');   ###插第10天的,开始报错
ERROR 1064 (HY000): Index: 3, Size: 3
关于Mycat分片规则是怎么样的问题的解答就分享到这里了,希望以上内容可以对大家有一定的帮助,如果你还有很多疑惑没有解开,可以关注亿速云行业资讯频道了解更多相关知识。

(编辑:淮北站长网)

【声明】本站内容均来自网络,其相关言论仅代表作者个人观点,不代表本站立场。若无意侵犯到您的权利,请及时与联系站长删除相关内容!

    热点阅读