本次实践基于ubuntu系统;
mycat:1.6.5;
采用docker
拉起3个mysql
容器,端口分别位于33061,33062,33063。
java
sudo apt-get install openjdk-8-jdk-headless
mycat
将mycat
安装包解压到/usr/local
下:java
sudo chown -R $USER /usr/local/mycat
mycat
/usr/local/mycat/bin/mycat start
查看logs/wrapper.log
监控启动状态node
mycat
server.xml
中配置可访问用户:<user name="mycat"> <property name="password">mycat</property> <property name="schemas">db1</property> </user>
这里的db1
必须是schema.xml
中配置的,不然报错。mysql
schema.xml
中配置参数:<?xml version="1.0"?> <!DOCTYPE mycat:schema SYSTEM "schema.dtd"> <mycat:schema xmlns:mycat="http://io.mycat/"> // schema标签的name对应server.xml中的schema <schema name="db1" checkSQLschema="true" sqlMaxLimit="1000000"> <table name="user" primaryKey="id" autoIncrement="true" dataNode="dn$1-3" rule="mod-long" /> </schema> <dataNode name="dn1" dataHost="node1" database="node" /> <dataNode name="dn4" dataHost="node1" database="node" /> <dataNode name="dn7" dataHost="node1" database="node" /> <dataNode name="dn11" dataHost="node1" database="node" /> <dataNode name="dn2" dataHost="node2" database="node" /> <dataNode name="dn5" dataHost="node2" database="node" /> <dataNode name="dn8" dataHost="node2" database="node" /> <dataNode name="dn11" dataHost="node2" database="node" /> <dataNode name="dn3" dataHost="node3" database="node" /> <dataNode name="dn6" dataHost="node3" database="node" /> <dataNode name="dn9" dataHost="node3" database="node" /> <dataNode name="dn12" dataHost="node3" database="node" /> // dataHost的name对应dataNode中的dataHost <dataHost name="node1" maxCon="1000" minCon="10" balance="1" writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100"> <heartbeat>select user()</heartbeat> // 在这里配置docker拉起来的3个容器 <writeHost host="hostM1" url="192.168.1.5:33061" user="root" password="root"> </writeHost> </dataHost> <dataHost name="node2" maxCon="1000" minCon="10" balance="1" writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100"> <heartbeat>select user()</heartbeat> <writeHost host="hostM2" url="192.168.1.5:33062" user="root" password="root"> </writeHost> </dataHost> <dataHost name="node3" maxCon="1000" minCon="10" balance="1" writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100"> <heartbeat>select user()</heartbeat> <writeHost host="hostM3" url="192.168.1.5:33063" user="root" password="root"> </writeHost> </dataHost> </mycat:schema>
root@063b64a0619f:/# mysql -u mycat -p -P 8066 -h HOST
此处HOST
为mycat
安装所在的ip。sql
mysql> show databases; +----------+ | DATABASE | +----------+ | db1 | +----------+ 1 row in set (0.01 sec)
这里的db1是schema标签中对应的名称,这是一个虚拟库。docker
mysql> use db1; Reading table information for completion of table and column names You can turn off this feature to get a quicker startup with -A Database changed mysql> show tables; +----------------------------+ | Tables in datacache | +----------------------------+ | user | +----------------------------+ 5 rows in set (0.01 sec)
这里的user表实际上目前也是个虚拟表,只有当在子节点中建立表以后,这个表才有意义。数据库
mysql> CREATE TABLE IF NOT EXISTS `user` ( -> `id` varchar(20) NOT NULL DEFAULT '0' COMMENT 'ID', -> `name` varchar(20) NOT NULL DEFAULT '' COMMENT '', -> `created_at` datetime NOT NULL DEFAULT now() COMMENT '', -> PRIMARY KEY (`id`) -> ) ENGINE=MyISAM DEFAULT CHARSET=utf8; Query OK, 0 rows affected, 1 warning (0.01 sec)
1.这里的id
不采用int类型,是由于我采用的全局序列是默认的本地时间戳方式,int长度不够;
2.这里建立表结构,必须在对用的全部dataNode上建立相同的表,若是只是在mycat库中建立,只会在第一个dataNode中建立成功,并不能在全部dataNode中一块儿建立,我想这是mycat仍然会进行优化的地方吧。ubuntu
mysql> INSERT INTO `user` (`name`,`date`) VALUES ('mycat','2017-10-10'); Query OK, 1 row affected (0.01 sec)
mysql> select * from user; +----+-------+---------------------+ | id | name | created_at | +----+-------+---------------------+ | 1 | mycat | 2018-02-01 07:12:26 | +----+-------+---------------------+ 1 row in set (0.01 sec)
1.当插入多条数据时,数据会根据mod-long
的分片方式分散到不一样节点上;
2.若是以时间维度做为筛选条件,会遍历全部节点,因此,根据个人业务需求,我将分片方式改成sharding-by-month
。bash
本来是分布在3个节点上的相同database上,可是发现当我插入一条数据,就会产生3条数据;
解决方式是分布到不一样的database上。
<schema name="db1" checkSQLschema="true" sqlMaxLimit="1000000"> <table name="user" primaryKey="id" autoIncrement="true" dataNode="dn$1-12" rule="sharding-by-month" /> </schema> <dataNode name="dn1" dataHost="node1" database="node1" /> <dataNode name="dn4" dataHost="node1" database="node2" /> <dataNode name="dn7" dataHost="node1" database="node3" /> <dataNode name="dn11" dataHost="node1" database="node4" /> <dataNode name="dn2" dataHost="node2" database="node1" /> <dataNode name="dn5" dataHost="node2" database="node2" /> <dataNode name="dn8" dataHost="node2" database="node3" /> <dataNode name="dn11" dataHost="node2" database="node4" /> <dataNode name="dn3" dataHost="node3" database="node1" /> <dataNode name="dn6" dataHost="node3" database="node2" /> <dataNode name="dn9" dataHost="node3" database="node3" /> <dataNode name="dn12" dataHost="node3" database="node4" />
这样虽然须要建立12个database,数据准确性问题获得解决。app