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。