Mycat是什么
详见(官网)
一个彻底开源的,面向企业应用开发的大数据库集群
支持事务、ACID、可以替代MySQL的加强版数据库
一个可以视为MySQL集群的企业级数据库,用来替代昂贵的Oracle集群
一个融合内存缓存技术、NoSQL技术、HDFS大数据的新型SQL Server
结合传统数据库和新型分布式数据仓库的新一代企业级数据库产品
一个新颖的数据库中间件产品
Mycat作用
(1). 集中管理多个数据库连接(分布式解决方案)
(2). 配置读写分离
(3). 配置数据库分片(分表、分库)等 (本文视角)
安装配置
1. 准备
环境:jdk1.8、mysql5.6、mycat1.6.7(官网)
测试工具:Navicat12
2. 目录结构
图中分别对应执行、配置、日志等文件目录
3. 配置
主要配置server.xml、schema.xml、rule.xml等文件,下面每个配置的内容均来自本地测试分表分库配置结果。内容已经包含详细介绍和说明。
server.xml:启动服务相关配置
<?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,设置为1则需要指定默认账户-->
<property name="ignoreUnknownCommand">0</property><!-- 0遇上没有实现的报文(Unknown command:),就会报错、1为忽略该报文,返回ok报文。
在某些mysql客户端存在客户端已经登录的时候还会继续发送登录报文,mycat会报错,该设置可以绕过这个错误-->
<property name="useHandshakeV10">1</property>
<property name="removeGraveAccent">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="sqlExecuteTimeout">300</property> <!-- SQL 执行超时 单位:秒-->
<property name="sequnceHandlerType">1</property>
<!--<property name="sequnceHandlerPattern">(?:(\s*next\s+value\s+for\s*MYCATSEQ_(\w+))(,|\)|\s)*)+</property>
INSERT INTO `travelrecord` (`id`,user_id) VALUES ('next value for MYCATSEQ_GLOBAL',"xxx");
-->
<!--必须带有MYCATSEQ_或者 mycatseq_进入序列匹配流程 注意MYCATSEQ_有空格的情况-->
<property name="sequnceHandlerPattern">(?:(\s*next\s+value\s+for\s*MYCATSEQ_(\w+))(,|\)|\s)*)+</property>
<property name="subqueryRelationshipCheck">false</property> <!-- 子查询中存在关联查询的情况下,检查关联字段中是否有分片字段 .默认 false -->
<property name="sequenceHanlderClass">io.mycat.route.sequence.handler.HttpIncrSequenceHandler</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="dataNodeIdleCheckPeriod">300000</property> 5 * 60 * 1000L; //连接空闲检查
<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>
<!--
off heap for merge/order/group/limit 1开启 0关闭
-->
<property name="useOffHeapForMerge">0</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">false</property>
<!-- XA Recovery Log日志路径 -->
<!--<property name="XARecoveryLogBaseDir">./</property>-->
<!-- XA Recovery Log日志名称 -->
<!--<property name="XARecoveryLogBaseName">tmlog</property>-->
<!--如果为 true的话 严格遵守隔离级别,不会在仅仅只有select语句的时候在事务中切换连接-->
<property name="strictTxIsolation">false</property>
<property name="useZKSwitch">true</property>
<!--如果为0的话,涉及多个DataNode的catlet任务不会跨线程执行-->
<property name="parallExecute">0</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" defaultAccount="true">
<property name="password">root</property>
<property name="schemas">TESTDB</property>
<property name="defaultSchema">TESTDB</property>
<!--No MyCAT Database selected 错误前会尝试使用该schema作为schema,不设置则为null,报错 -->
<!-- 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="root">
<property name="password">root</property>
<property name="schemas">TESTDB</property>
<property name="readOnly">true</property>
<property name="defaultSchema">TESTDB</property>
</user>-->
</mycat:server>
这里配置的用户user标签名称不能相同,一般只配置一个
schema.xml:库、表相关配置
<?xml version="1.0"?>
<!DOCTYPE mycat:schema SYSTEM "schema.dtd">
<mycat:schema xmlns:mycat="http://io.mycat/">
<schema name="TESTDB" checkSQLschema="true" sqlMaxLimit="100" randomDataNode="dn1">
<!-- auto sharding by id (long) -->
<!--splitTableNames 启用<table name 属性使用逗号分割配置多个表,即多个表使用这个配置-->
<!-- <table name="travelrecord,address" dataNode="dn1,dn2,dn3" rule="auto-sharding-long" splitTableNames ="true"/> -->
<!-- <table name="oc_call" primaryKey="ID" dataNode="dn1$0-743" rule="latest-month-calldate"
/> -->
<!-- 逻辑表 可以多个 -->
<table name="address" rule="auto-sharding-long" primaryKey="ID" dataNode="dn1,dn2,dn3" />
<!--name需要与数据库表对应 primaryKey主键ID rule分片规则 数据分布在dn1、dn2、dn3三个数据节点dataNode -->
<table name="company" primaryKey="ID" type="global" dataNode="dn1" />
<!--没有分片的表 默认是普通表 type=global表 会将所有dataNode的数据拷贝一份到该逻辑表中-->
</schema>
<!-- <dataNode name="dn1$0-743" dataHost="localhost1" database="db$0-743"
/> -->
<dataNode name="dn1" dataHost="localhost1" database="db1" />
<dataNode name="dn2" dataHost="localhost1" database="db2" />
<dataNode name="dn3" dataHost="localhost1" database="db3" />
<!--<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="localhost1" maxCon="1000" minCon="10" balance="0"
writeType="0" dbType="mysql" dbDriver="native" switchType="1" slaveThreshold="100">
<heartbeat>select user()</heartbeat>
<!-- can have multi write hosts -->
<writeHost host="hostM1" url="xxx.xxx.xxx.xxx:3306" user="root"
password="root">
</writeHost>
<!-- <writeHost host="hostM2" url="localhost:3316" user="root" password="123456"/> -->
</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>
rule.xml: 规则相关配置
<?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="sharding-by-date">
<rule>
<columns>createTime</columns>
<algorithm>partbyday</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>create_time</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">3</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">2015-01-01</property>
</function>
<function name="partbyday"
class="io.mycat.route.function.PartitionByDate">
<property name="dateFormat">yyyy-MM-dd</property>
<property name="sNaturalDay">0</property>
<property name="sBeginDate">2014-01-01</property>
<property name="sEndDate">2014-01-31</property>
<property name="sPartionDay">10</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>
这里的规则对应具体规则文件在conf下,如本例查找使用规则文件过程:
先在schema.xml中找到 :
<!--name需要与数据库表对应 primaryKey主键ID rule分片规则 数据分布在dn1、dn2、dn3三个数据节点dataNode -->
<table name="address" rule="auto-sharding-long" primaryKey="ID" dataNode="dn1,dn2,dn3" />
<!--没有分片的表 默认是普通表 type=global表 会将所有dataNode的数据拷贝一份到该逻辑表中-->
<table name="company" primaryKey="ID" type="global" dataNode="dn1" />
可以发现,表address的规则,auto-sharding-long,通过这个规则去rule.xml查询,结果如下:
<tableRule name="auto-sharding-long">
<rule>
<columns>id</columns>
<algorithm>rang-long</algorithm>
</rule>
</tableRule>
再通过rang-long找到关联的函数,如下:
<function name="rang-long" class="io.mycat.route.function.AutoPartitionByLong">
<property name="mapFile">autopartition-long.txt</property>
</function>
再去conf/目录下查询此文件,内容如下:
# range start-end ,data node index
# K=1000,M=10000.
0-500M=0
500M-1000M=1
1000M-1500M=2
注意:k= 1000 M=1000,上面文件内容默认是500万数据一个表
4.使用测试
打开navicat,连接mycat,server.xml的user标签配置的用户名和密码,还有数据库,我的截图如下:
xuyao
需要的两个数据库,我是在阿里云上部署的两个mysq实例,可自己本地部署
创建的库db1、db2、db3
创建表格脚本:(记得每个库都得创建schma.xml中配置的表格)
SET NAMES utf8mb4;
SET FOREIGN_KEY_CHECKS = 0;
-- ----------------------------
-- Table structure for address
-- ----------------------------
DROP TABLE IF EXISTS `address`;
CREATE TABLE `address` (
`id` int(11) NOT NULL,
`addressname` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL,
PRIMARY KEY (`id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Compact;
-- ----------------------------
-- Table structure for company
-- ----------------------------
DROP TABLE IF EXISTS `company`;
CREATE TABLE `company` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`companyname` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL,
`addressid` int(11) NULL DEFAULT NULL,
PRIMARY KEY (`id`) USING BTREE
) ENGINE = InnoDB AUTO_INCREMENT = 235 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Compact;
-- ----------------------------
-- Table structure for test
-- ----------------------------
DROP TABLE IF EXISTS `test`;
CREATE TABLE `test` (
`id` bigint(20) NULL DEFAULT NULL
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Compact;
-- ----------------------------
-- Table structure for travelrecord
-- ----------------------------
DROP TABLE IF EXISTS `travelrecord`;
CREATE TABLE `travelrecord` (
`id` bigint(20) NOT NULL AUTO_INCREMENT,
`user_id` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
`traveldate` date NULL DEFAULT NULL,
`fee` decimal(10, 0) NULL DEFAULT NULL,
`days` int(11) NULL DEFAULT NULL,
`blob` longblob NULL,
PRIMARY KEY (`id`) USING BTREE
) ENGINE = InnoDB AUTO_INCREMENT = 2 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Compact;
-- ----------------------------
-- Table structure for travelrecord2
-- ----------------------------
DROP TABLE IF EXISTS `travelrecord2`;
CREATE TABLE `travelrecord2` (
`id` bigint(20) NOT NULL AUTO_INCREMENT,
`user_id` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
`traveldate` date NULL DEFAULT NULL,
`fee` decimal(10, 0) NULL DEFAULT NULL,
`days` int(11) NULL DEFAULT NULL,
`blob` longblob NULL,
PRIMARY KEY (`id`) USING BTREE
) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Compact;
-- ----------------------------
-- Table structure for travelrecord3
-- ----------------------------
DROP TABLE IF EXISTS `travelrecord3`;
CREATE TABLE `travelrecord3` (
`id` bigint(20) NOT NULL AUTO_INCREMENT,
`user_id` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
`traveldate` date NULL DEFAULT NULL,
`fee` decimal(10, 0) NULL DEFAULT NULL,
`days` int(11) NULL DEFAULT NULL,
`blob` longblob NULL,
PRIMARY KEY (`id`) USING BTREE
) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Compact;
SET FOREIGN_KEY_CHECKS = 1;
测试数据
INSERT INTO address(id, addressname) VALUES(5000000,1100) #对应db1的address
INSERT INTO address(id, addressname) VALUES(5000001,1100) #对应db2的address
INSERT INTO address(id, addressname) VALUES(10000001,1100) #对应db3的address
INSERT INTO address(id, addressname) VALUES(15000001,1100) #无对应
只是测试了分库分表,还可以配置读写分离,多数据源集群管理等
最新的mycat2,配置发生了变化,均在mycat.yml中配置server、schma、rule。并有sample文件,有对应的配置demo可参考。