MyCat 安装部署，实现数据库分片存储，
一、安装MySQL或MariaDB（本文以MariaDB为例）
MySQL手动安装方法：点击查看
MariaDB安装：
1、下载MariaDB的repo
?| 123456789101112131415 | $ vi /etc/yum.repos.d/MariaDB.repo # MariaDB 的Yum源[mariadb]name = MariaDBbaseurl = http://yum.mariadb.org/10.1/centos7-amd64gpgkey=https://yum.mariadb.org/RPM-GPG-KEY-MariaDBgpgcheck=1 #保存退出 #更新Yum源 $ yum clean all$ yum makecache |
2、安装MariaDB
?| 12345678910 | $ yum install -y mariadb.x86_64 mariadb-server.x86_64 mariadb-libs.x86_64 # 启动MariaDB$ service mysql start #MariaDB # 端口：3360 # 账户密码：root/123456 #Datadir：/var/lib/mysql #配置文件：/etc/my.cnf |
其他修改MariaDB的密码或授权操作与MySql无异，可按http://www.cnblogs.com/raphael5200/p/5265736.html 中进行操作。
二、安装部署MyCat
1、下载 安装MyCat
下载地址：http://www.mycat.org.cn/
安装：
?| 12345678910111213141516171819202122 | $ tar -zxvf Mycat-server-1.5.1-RELEASE-2016081617.tar.gz$ mv mycat/ /usr/local/$ cd /usr/local/mycat/conf $ vim wrapper.conf # Java Application 以下参数可以省略wrapper.java.command=/usr/java/jdk1.7.0_71/bin/javawrapper.java.additional.12=-XX:+UseParNewGCwrapper.java.additional.13=-XX:+UseConcMarkSweepGCwrapper.java.additional.14=-XX:+UseCMSCompactAtFullCollectionwrapper.java.additional.15=-XX:CMSFullGCsBeforeCompaction=0wrapper.java.additional.16=-XX:CMSInitiatingOccupancyFraction=70 #设置Hosts名$ vim /etc/hosts192.168.101.161 server-161 #mycat 就已经启动了 端口8066./bin/mycat start #查看方法$ mysql -utest -ptest -h127.0.0.1 -P8066 -DTESTDB |
三、配置MyCat分片
1、在MariaDB中新建3个数据库db1,db2,db3
?| 1234567 | CREATE database db1;CREATE database db2;CREATE database db3; -- 注意：若是LINUX版本的MYSQL，则需要设置为Mysql大小写不敏感，否则可能会发生表找不到的问题。-- 在MySQL的配置文件/etc/my.cnf 的[mysqld] 中增加一行lower_case_table_names = 1 |
2、配置MyCat的schema.xml
?| 123456789101112131415161718 | $ vim /usr/local/mycat/conf/schema.xml <schema name="TESTDB" checkSQLschema="false" sqlMaxLimit="100"> #TESTDB 是MyCat默认的一个测试逻辑数据库，需要在此节点下定义逻辑表，但在这里只是指定表的名称，并不对表进行详细的定义。 #下面这条语句就是指逻辑表tb_user_info将在dn1,dn2,dn3上创建 使用的分片规则是 auto-sharding-long <table name="tb_user_info" dataNode="dn1,dn2,dn3" rule="auto-sharding-long" /> </schema> #配置dataNode 如果业务需要的话，可以配置多个dataHost 指定多个节点 <dataNode name="dn1" dataHost="localhost1" database="db1" /> <dataNode name="dn2" dataHost="localhost1" database="db2" /> <dataNode name="dn3" dataHost="localhost1" database="db3" /> <dataHost name="localhost1" maxCon="1000" minCon="10" balance="0" writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100"> <heartbeat>select user()</heartbeat> <writeHost host="hostM1" url="192.168.244.11:3306" user="root" password="111111"> </writeHost> </dataHost> |
在schema.xml 中配置好的表名，实际上只是一个逻辑的表，这个表在物理数据库中并不存在，需要在MyCat通过Create Table 来创建这个表，执行Create语句以后，MyCat会在真实MySql配置的数据库中创建表。
配置完以后，保存退出，重启MyCat
3、auto-sharding-long分片规则
在上面的例子中使用到auto-sharding-long分片规则，在这里要说明一下这个分片规则的实现原理。
在mycat/conf.rule.xml中定义了分片规则的实现原理 auto-sharding-long 分片规则是这样的：
<tableRule name="auto-sharding-long"> <rule> <columns>id</columns> <algorithm>rang-long</algorithm> </rule> </tableRule> <function name="rang-long" class="org.opencloudb.route.function.AutoPartitionByLong"> <property name="mapFile">autopartition-long.txt</property> </function>
可见这个TableRule是通过id 来进行分片的，分片的算法是rang-long 下面在算法中使用到了autopartition-long.txt(mycat/conf下)，打开看看：
?| 12345 | # range start-end ,data node index# K=1000,M=10000.0-500M=0500M-1000M=11000M-1500M=2 |
K=1000条记录，M=10000条记录，那么下面三个配置就是0~500万的记录会存在数据库db1的表中，500万~1000万会存在db2的表中，1000万~1500万会存在db3的表中。
4、牛刀小试
$ ../bin/mycat start
$ ../bin/mycat status 查看MyCat状态
$ ps -ef | grep mycat 查看MyCat进程
$ ss -tanl 查看端口监听情况
?| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253 | [root@node1 bin]# mysql -utest -ptest -h127.0.0.1 -P8066 -DTESTDB...mysql> show tables;+------------------+| Tables in TESTDB |+------------------+| company || customer || customer_addr || employee || goods || hotnews || orders || order_items || tb_user_info |+------------------+9 rows in set (0.00 sec) -- 在MyCat中创建物理表mysql> create table tb_user_info (id bigint not null auto_increment primary key,name varchar(100));Query OK, 0 rows affected (0.16 sec) -- 查看物理表mysql> use db1; mysql> show tables;+---------------+| Tables_in_db1 |+---------------+| tb_user_info |+---------------+ mysql> use db2; Database changedmysql> show tables;+---------------+| Tables_in_db2 |+---------------+| tb_user_info |+---------------+1 row in set (0.00 sec) mysql> use db3 Database changedmysql> show tables;+---------------+| Tables_in_db3 |+---------------+| tb_user_info |+---------------+1 row in set (0.00 sec) |
可以在MySql中的三个数据库中看到，表确实已经创建了。
下面我们分别向表中插入三条数据分别ID是 100，6000000，11000000，看是否正常分配到三个表中：
能过在MyCat中执行explain SQL语句，可以查看插入的记录将会被分配到哪个表中：
?| 123456789101112131415161718192021222324252627 | insert into tb_user_info(id,name) values(100,'lucy');insert into tb_user_info(id,name) values(6000000,'lily');insert into tb_user_info(id,name) values(11000000,'tom'); mysql> explain insert into tb_user_info(id,name) values(100,'lucy');+-----------+------------------------------------------------------+| DATA_NODE | SQL |+-----------+------------------------------------------------------+| dn1 | insert into tb_user_info(id,name) values(100,'lucy') |+-----------+------------------------------------------------------+1 row in set (0.09 sec) mysql> explain insert into tb_user_info(id,name) values(6000000,'lily');+-----------+----------------------------------------------------------+| DATA_NODE | SQL |+-----------+----------------------------------------------------------+| dn2 | insert into tb_user_info(id,name) values(6000000,'lily') |+-----------+----------------------------------------------------------+1 row in set (0.00 sec) mysql> explain insert into tb_user_info(id,name) values(11000000,'tom');+-----------+----------------------------------------------------------+| DATA_NODE | SQL |+-----------+----------------------------------------------------------+| dn3 | insert into tb_user_info(id,name) values(11000000,'tom') |+-----------+----------------------------------------------------------+1 row in set (0.00 sec) |
实际物理表中查询结果：
?| 1234567891011121314151617181920212223 | mysql> select * from tb_user_info;+-----+------+| id | name |+-----+------+| 100 | lucy |+-----+------+1 row in set (0.00 sec) mysql> select * from db2.tb_user_info;+---------+------+| id | name |+---------+------+| 6000000 | lily |+---------+------+1 row in set (0.00 sec) mysql> select * from db3.tb_user_info;+----------+------+| id | name |+----------+------+| 11000000 | tom |+----------+------+1 row in set (0.00 sec) |
至此一个简单的MyCat分片技术就实现了，后续会有更多MyCat分片规则的介绍！
此外，有朋友可能在使用mongdb也想使用mycat 来进行分库分表等操作；我在这里用一个案例；来演示mycat对mongdb进行分库（因实际原因分表就不演示了）
第一步:service.xml
<?xml version="1.0" encoding="UTF-8"?>
<!-- - - Licensed under the Apache License, Version 2.0 (the "License");
- you may not use this file except in compliance with the License. - You
may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0
- - Unless required by applicable law or agreed to in writing, software -
distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the
License for the specific language governing permissions and - limitations
under the License. -->
<!DOCTYPE mycat:server SYSTEM "server.dtd">
<mycat:server xmlns:mycat="http://io.mycat/">
<system>
<property name="nonePasswordLogin">0</property> <!-- 0为需要密码登陆、1为不需要密码登陆 ,默认为0-->
<property name="useHandshakeV10">1</property>
<property name="useSqlStat">0</property> <!-- 1为开启实时统计、0为关闭 -->
<property name="useGlobleTableCheck">0</property> <!-- 1为开启全加班一致性检测、0为关闭 -->
<property name="charset">utf8</property>
<property name="sequnceHandlerType">2</property>
<!-- <property name="useCompression">1</property>--> <!--1为开启mysql压缩协议-->
<!-- <property name="fakeMySQLVersion">5.6.20</property>--> <!--设置模拟的MySQL版本号-->
<!-- <property name="processorBufferChunk">40960</property> -->
<!--
<property name="processors">1</property>
<property name="processorExecutor">32</property>
-->
<!--默认为type 0: DirectByteBufferPool | type 1 ByteBufferArena | type 2 NettyBufferPool -->
<property name="processorBufferPoolType">0</property>
<!--默认是65535 64K 用于sql解析时最大文本长度 -->
<!--<property name="maxStringLiteralLength">65535</property>-->
<!--<property name="sequnceHandlerType">0</property>-->
<!--<property name="backSocketNoDelay">1</property>-->
<!--<property name="frontSocketNoDelay">1</property>-->
<!--<property name="processorExecutor">16</property>-->
<!--
<property name="serverPort">8066</property> <property name="managerPort">9066</property>
<property name="idleTimeout">300000</property> <property name="bindIp">0.0.0.0</property>
<property name="frontWriteQueueSize">4096</property> <property name="processors">32</property> -->
<!--分布式事务开关，0为不过滤分布式事务，1为过滤分布式事务（如果分布式事务内只涉及全局表，则不过滤），2为不过滤分布式事务,但是记录分布式事务日志-->
<property name="handleDistributedTransactions">0</property>
<property name="serverPort">8066</property>
<!--
off heap for merge/order/group/limit 1开启 0关闭
-->
<property name="useOffHeapForMerge">1</property>
<!--
单位为m
-->
<property name="memoryPageSize">64k</property>
<!--
单位为k
-->
<property name="spillsFileBufferSize">1k</property>
<property name="useStreamOutput">0</property>
<!--
单位为m
-->
<property name="systemReserveMemorySize">384m</property>
<!--是否采用zookeeper协调切换 -->
<property name="useZKSwitch">true</property>
<!-- XA Recovery Log日志路径 -->
<!--<property name="XARecoveryLogBaseDir">./</property>-->
<!-- XA Recovery Log日志名称 -->
<!--<property name="XARecoveryLogBaseName">tmlog</property>-->
</system>
<!-- 全局SQL防火墙设置 -->
<!--白名单可以使用通配符%或着*-->
<!--例如<host host="127.0.0.*" user="root"/>-->
<!--例如<host host="127.0.*" user="root"/>-->
<!--例如<host host="127.*" user="root"/>-->
<!--例如<host host="1*7.*" user="root"/>-->
<!--这些配置情况下对于127.0.0.1都能以root账户登录-->
<!--
<firewall>
<whitehost>
<host host="1*7.0.0.*" user="root"/>
</whitehost>
<blacklist check="false">
</blacklist>
</firewall>
-->
<user name="root">
<property name="password">123456</property>
<property name="schemas">Ch_Gps</property>
<!-- 表级 DML 权限设置 -->
<!--
<privileges check="false">
<schema name="TESTDB" dml="0110" >
<table name="tb01" dml="0000"></table>
<table name="tb02" dml="1111"></table>
</schema>
</privileges>
-->
</user>
<user name="user">
<property name="password">user</property>
<property name="schemas">Ch_Gps</property>
<property name="readOnly">true</property>
</user>
</mycat:server>
<?xml version="1.0"?>
<!DOCTYPE mycat:schema SYSTEM "schema.dtd">
<mycat:schema xmlns:mycat="http://io.mycat/">
<schema name="Ch_Gps" checkSQLschema="false" sqlMaxLimit="100">
<table name="Ch_track" primaryKey="_ID" dataNode="dn$1-12" rule="sharding-by-month" autoIncrement="true"/>
</schema>
<!-- <dataNode name="dn1$0-743" dataHost="localhost1" database="db$0-743"
/> -->
<dataNode name="dn1" dataHost="jdbchost" database="January" />
<dataNode name="dn2" dataHost="jdbchost" database="February" />
<dataNode name="dn3" dataHost="jdbchost" database="March" />
<dataNode name="dn4" dataHost="jdbchost" database="April" />
<dataNode name="dn5" dataHost="jdbchost" database="May" />
<dataNode name="dn6" dataHost="jdbchost" database="June" />
<dataNode name="dn7" dataHost="jdbchost" database="July" />
<dataNode name="dn8" dataHost="jdbchost" database="August" />
<dataNode name="dn9" dataHost="jdbchost" database="September" />
<dataNode name="dn10" dataHost="jdbchost" database="October" />
<dataNode name="dn11" dataHost="jdbchost" database="November" />
<dataNode name="dn12" dataHost="jdbchost" database="December" />
<!--<dataNode name="dn4" dataHost="sequoiadb1" database="SAMPLE" />
<dataNode name="jdbc_dn1" dataHost="jdbchost" database="db1" />
<dataNode name="jdbc_dn2" dataHost="jdbchost" database="db2" />
<dataNode name="jdbc_dn3" dataHost="jdbchost" database="db3" /> -->
<dataHost name="jdbchost" maxCon="1000" minCon="1" balance="0" writeType="0" dbType="mongodb" dbDriver="jdbc">
<heartbeat>select user()</heartbeat>
<writeHost host="hostM" url="mongodb://localhost:27017" user="root" password="123456">
</writeHost>
</dataHost>
<!--
<dataHost name="sequoiadb1" maxCon="1000" minCon="1" balance="0" dbType="sequoiadb" dbDriver="jdbc">
<heartbeat> </heartbeat>
<writeHost host="hostM1" url="sequoiadb://1426587161.dbaas.sequoialab.net:11920/SAMPLE" user="jifeng" password="jifeng"></writeHost>
</dataHost>
<dataHost name="oracle1" maxCon="1000" minCon="1" balance="0" writeType="0" dbType="oracle" dbDriver="jdbc"> <heartbeat>select 1 from dual</heartbeat>
<connectionInitSql>alter session set nls_date_format='yyyy-mm-dd hh24:mi:ss'</connectionInitSql>
<writeHost host="hostM1" url="jdbc:oracle:thin:@127.0.0.1:1521:nange" user="base" password="123456" > </writeHost> </dataHost>
<dataHost name="jdbchost" maxCon="1000" minCon="1" balance="0" writeType="0" dbType="mongodb" dbDriver="jdbc">
<heartbeat>select user()</heartbeat>
<writeHost host="hostM" url="mongodb://192.168.0.99/test" user="admin" password="123456" ></writeHost> </dataHost>
<dataHost name="sparksql" maxCon="1000" minCon="1" balance="0" dbType="spark" dbDriver="jdbc">
<heartbeat> </heartbeat>
<writeHost host="hostM1" url="jdbc:hive2://feng01:10000" user="jifeng" password="jifeng"></writeHost> </dataHost> -->
<!-- <dataHost name="jdbchost" maxCon="1000" minCon="10" balance="0" dbType="mysql"
dbDriver="jdbc"> <heartbeat>select user()</heartbeat> <writeHost host="hostM1"
url="jdbc:mysql://localhost:3306" user="root" password="123456"> </writeHost>
</dataHost> -->
</mycat:schema><?xml version="1.0" encoding="UTF-8"?>
<!-- - - Licensed under the Apache License, Version 2.0 (the "License");
- you may not use this file except in compliance with the License. - You
may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0
- - Unless required by applicable law or agreed to in writing, software -
distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the
License for the specific language governing permissions and - limitations
under the License. -->
<!DOCTYPE mycat:rule SYSTEM "rule.dtd">
<mycat:rule xmlns:mycat="http://io.mycat/">
<tableRule name="rule1">
<rule>
<columns>id</columns>
<algorithm>func1</algorithm>
</rule>
</tableRule>
<tableRule name="rule2">
<rule>
<columns>user_id</columns>
<algorithm>func1</algorithm>
</rule>
</tableRule>
<tableRule name="sharding-by-intfile">
<rule>
<columns>sharding_id</columns>
<algorithm>hash-int</algorithm>
</rule>
</tableRule>
<tableRule name="auto-sharding-long">
<rule>
<columns>id</columns>
<algorithm>rang-long</algorithm>
</rule>
</tableRule>
<tableRule name="mod-long">
<rule>
<columns>id</columns>
<algorithm>mod-long</algorithm>
</rule>
</tableRule>
<tableRule name="sharding-by-murmur">
<rule>
<columns>id</columns>
<algorithm>murmur</algorithm>
</rule>
</tableRule>
<tableRule name="crc32slot">
<rule>
<columns>id</columns>
<algorithm>crc32slot</algorithm>
</rule>
</tableRule>
<tableRule name="sharding-by-month">
<rule>
<columns>utcTime</columns>
<algorithm>partbymonth</algorithm>
</rule>
</tableRule>
<tableRule name="latest-month-calldate">
<rule>
<columns>calldate</columns>
<algorithm>latestMonth</algorithm>
</rule>
</tableRule>
<tableRule name="auto-sharding-rang-mod">
<rule>
<columns>id</columns>
<algorithm>rang-mod</algorithm>
</rule>
</tableRule>
<tableRule name="jch">
<rule>
<columns>id</columns>
<algorithm>jump-consistent-hash</algorithm>
</rule>
</tableRule>
<function name="murmur"
class="io.mycat.route.function.PartitionByMurmurHash">
<property name="seed">0</property><!-- 默认是0 -->
<property name="count">2</property><!-- 要分片的数据库节点数量，必须指定，否则没法分片 -->
<property name="virtualBucketTimes">160</property><!-- 一个实际的数据库节点被映射为这么多虚拟节点，默认是160倍，也就是虚拟节点数是物理节点数的160倍 -->
<!-- <property name="weightMapFile">weightMapFile</property> 节点的权重，没有指定权重的节点默认是1。以properties文件的格式填写，以从0开始到count-1的整数值也就是节点索引为key，以节点权重值为值。所有权重值必须是正整数，否则以1代替 -->
<!-- <property name="bucketMapPath">/etc/mycat/bucketMapPath</property>
用于测试时观察各物理节点与虚拟节点的分布情况，如果指定了这个属性，会把虚拟节点的murmur hash值与物理节点的映射按行输出到这个文件，没有默认值，如果不指定，就不会输出任何东西 -->
</function>
<function name="crc32slot"
class="io.mycat.route.function.PartitionByCRC32PreSlot">
<property name="count">2</property><!-- 要分片的数据库节点数量，必须指定，否则没法分片 -->
</function>
<function name="hash-int"
class="io.mycat.route.function.PartitionByFileMap">
<property name="mapFile">partition-hash-int.txt</property>
</function>
<function name="rang-long"
class="io.mycat.route.function.AutoPartitionByLong">
<property name="mapFile">autopartition-long.txt</property>
</function>
<function name="mod-long" class="io.mycat.route.function.PartitionByMod">
<!-- how many data nodes -->
<property name="count">2</property>
</function>
<function name="func1" class="io.mycat.route.function.PartitionByLong">
<property name="partitionCount">8</property>
<property name="partitionLength">128</property>
</function>
<function name="latestMonth"
class="io.mycat.route.function.LatestMonthPartion">
<property name="splitOneDay">24</property>
</function>
<function name="partbymonth"
class="io.mycat.route.function.PartitionByMonth">
<property name="dateFormat">yyyy-MM-dd</property>
<property name="sBeginDate">2018-01-01</property>
<property name="sEndDate">2018-12-31</property>
</function>
<function name="rang-mod" class="io.mycat.route.function.PartitionByRangeMod">
<property name="mapFile">partition-range-mod.txt</property>
</function>
<function name="jump-consistent-hash" class="io.mycat.route.function.PartitionByJumpConsistentHash">
<property name="totalBuckets">3</property>
</function>
</mycat:rule>原因还是因为mongdb的特性吧,这个问题花了比较久的时间才解决,具体解决办法其实很简单,一想到特性,mongdb没有表的概念,有的是文档,就是说他的不像关系型那样事先设置好表的字段和数据类型 所以当我手动写入一条数据 可以理解为相当于在mongodb建一张表的意思 不然没办法insert进去 后面的测试都成功啦
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