<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mycat:schema SYSTEM "schema.dtd">
<mycat:schema xmlns:mycat="http://io.mycat/">
    <!-- name：为mycat逻辑库的名字，对应server<property name="schemas">mydatabase</property>，
    建议设置跟数据库一样的名称
    checkSQLschema：自动检查逻辑库名称并拼接，true会在sql语句中的表名前拼接逻辑库名，
    例如select * from mydatabase.t_user;
    sqlMaxLimit：查询保护、如果没有写limit条件，会自动拼接。只查询100条。
    -->
    <schema name="mydatabase" checkSQLschema="true" sqlMaxLimit="100">
        <!-- name:为物理数据库的表名，命名与物理数据库的一致
        dataNode:为dataNode标签(<dataNode name="dn1" dataHost="dtHost1" database="db1" />)里面的name值
        dataNode里面填写的节点数量必须和rule里面的规则数量一致
        例如rule里面只定义了两个0-1M=0  1M-2M=1那么此处只可以指定两个节点,1M=10000，M为单位万
        primaryKey:为表的ID字段，建议和rule.xml里面指定的ID和物理库的ID一致
        rule：分片规则，对应rule.xml中<tableRule name="student_id">的name
        type：表格类型，默认非global，用于全局表定义
        -->
        <table name="t_user" dataNode="dn1,dn2,dn3" primaryKey="id" rule="auto-sharding-long">
            <!--ER分片注意childTable 标签需要放到table标签内，是主外键关联关系，
                name:为物理数据库的表名，命名与物理数据库的一致
                primaryKey:为表t_loginlog的ID字段，建议和rule.xml里面指定的ID和物理库的ID一致.
                joinKey：从表t_loginlog的外键字段，需要和物理库的字段名称一致
                parentKey：为主表t_user的字段名，依据此字段做关联，进行ER分片-->
            <childTable name="t_loginlog" primaryKey="id" joinKey="user_id" parentKey="id"></childTable>
        </table>
        <table name="t_student" dataNode="dn1,dn3" primaryKey="id" rule="student_id" />
        <table name="t_dictionaries" dataNode="dn1,dn2,dn3" type="global" />
        <table name="t_teacher" dataNode="dn1" />
    </schema>

    <!-- name：节点名称，用于在table标签里面调用
    dataHost:dataHost标签name值(<dataHost name="dtHost1">)
    database:物理数据库名，需要提前创建好实际存在的-->
    <dataNode name="dn1" dataHost="dtHost1" database="db1" />
    <dataNode name="dn2" dataHost="dtHost1" database="db2" />
    <dataNode name="dn3" dataHost="dtHost2" database="db3" />

    <!--name：节点名称，在上方dataNode标签中调用
    maxCon:底层数据库的链接最大数
    minCon:底层数据库的链接最小数
    balance:值可以为0,1,2,3,分别表示对当前datahost中维护的数据库们的读操作逻辑
    0:不开启读写分离，所有的读写操作都在最小的索引号的writeHost(第一个writeHost标签)
    1：全部的readHost和备用writeHost都参与读数据的平衡，如果读的请求过多，负责写的第一个writeHost也分担一部分
    2 ：所有的读操作，都随机的在所有的writeHost和readHost中进行
    3 ：所有的读操作，都到writeHost对应的readHost上进行（备用writeHost不参加了）,在集群中没有配置ReadHost的情况下,读都到第
    一个writeHost完成
    writeType:控制当前datahost维护的数据库集群的写操作
    0：所有的写操作都在第一个writeHost标签的数据库进行
    1：所有的写操作，都随机分配到所有的writeHost（mycat1.5完全不建议配置了）
    dbtype：数据库类型（不同数据库配置不同名称，mysql）
    dbDriver:数据库驱动，native,动态获取
    switchType：切换的逻辑
    -1：故障不切换
    1：故障切换，当前写操作的writeHost故障，进行切换，切换到下一个writeHost；
    slaveThreshold：标签中的<heartbeat>用来检测后端数据库的心跳sql语句;本属性检查从节点与主节点的同步情况(延迟时间数),配合心
    跳语句show slave status; 读写分离时,所有的readHost的数据都可靠-->
  
    <dataHost name="dtHost1" maxCon="1000" minCon="10" balance="1"
              writeType="0" dbType="mysql" dbDriver="native" switchType="1"  slaveThreshold="100">
        <!--用于验证心跳，这个是mysql主库的配置-->
        <heartbeat>select user()</heartbeat>

        <writeHost host="127.0.0.1" url="192.168.244.105:3306" user="root" password="123456">
            <readHost host="127.0.0.1" url="192.168.244.105:3306" user="root" password="123456" />
        </writeHost>

    </dataHost>
  
    <dataHost name="dtHost2" maxCon="1000" minCon="10" balance="1"
              writeType="0" dbType="mysql" dbDriver="native" switchType="1"  slaveThreshold="100">
        <!--用于验证心跳，这个是mysql主库的配置-->
        <heartbeat>select user()</heartbeat>

        <writeHost host="127.0.0.1" url="192.168.244.106:3306" user="root" password="123456">
            <readHost host="127.0.0.1" url="192.168.244.106:3306" user="root" password="123456" />
        </writeHost>

    </dataHost>
</mycat:schema>

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mycat:server SYSTEM "server.dtd">
<mycat:server xmlns:mycat="http://io.mycat/">
    <system>
        <!--配置的端口号-->
        <property name="serverPort">8066</property>
        <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="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="sequnceHandlerType">2</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="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>
        <!-- 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">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>
    </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-->
    <!-- 此处是开放了本机和外网的请求链接，因为我的mycat安装在虚拟机上，所以本机是通过ip链接
    192.*是为了让navicat可以连接使用(配置完整的虚拟机IP也可以)
    127.*是为了让虚拟机本身可以通过命令连接-->
    <firewall>
        <whitehost>
            <host host="192.*" user="root"/>
            <host host="127.*" user="root"/>
        </whitehost>
        <blacklist check="false">
        </blacklist>
    </firewall>
    <!-- 此处定义了一个root用户，可以管理的逻辑库为mydatabase，对应schema.xml中的<schema name="mydatabase" > -->
    <user name="root" defaultAccount="true">
        <property name="password">123456</property>
        <property name="schemas">mydatabase</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">123456</property>
        <property name="schemas">mycat1,test3</property>
        <property name="readOnly">true</property>
    </user>-->
</mycat:server>

<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mycat:rule SYSTEM "rule.dtd">
<mycat:rule xmlns:mycat="http://io.mycat/">
    <!--schema.xml中配置的rule="student_id" 所对应的规则，规则对应主键，
    列名为id需要与数据库的列名对应algorithm对应下方function-->
    <tableRule name="student_id">
        <rule>
            <columns>id</columns>
            <algorithm>student_text</algorithm>
        </rule>
    </tableRule>
    <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>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>
    <!--在conf中需要添加student_text.txt规则文件-->
    <function name="student_text"
              class="io.mycat.route.function.AutoPartitionByLong">
        <property name="mapFile">student_text.txt</property>
    </function>
    <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">
    </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="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>

<dataNode name="dn1" dataHost="dtHost1" database="db1" />
<dataNode name="dn2" dataHost="dtHost1" database="db2" />
<dataNode name="dn3" dataHost="dtHost2" database="db3" />

DROP TABLE IF EXISTS `t_user`;
CREATE TABLE `t_user` (
  `id` int(11) NOT NULL,
  `name` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

DROP TABLE IF EXISTS `t_student`;
CREATE TABLE `t_student` (
  `id` int(11) NOT NULL,
  `s_name` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

DROP TABLE IF EXISTS `t_teacher`;
CREATE TABLE `t_teacher` (
  `id` int(11) NOT NULL,
  `t_name` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

DROP TABLE IF EXISTS `t_loginlog`;
CREATE TABLE `t_loginlog` (
  `id` int(11) NOT NULL,
  `user_id` int(11) NOT NULL,
  `create_time` date DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

DROP TABLE IF EXISTS `t_dictionaries`;
CREATE TABLE `t_dictionaries` (
  `id` int(11) NOT NULL,
  `name` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

INSERT INTO `mydatabase`.`t_dictionaries`(`id`, `name`) VALUES (1, '1');

INSERT INTO `mydatabase`.`t_teacher`(`id`, `t_name`) VALUES (1, '小明');

<function name="rang-long" class="io.mycat.route.function.AutoPartitionByLong">
    <property name="mapFile">autopartition-long.txt</property>
</function>

INSERT INTO `mydatabase`.`t_user`(`id`, `name`) VALUES (1, '1');
INSERT INTO `mydatabase`.`t_user`(`id`, `name`) VALUES (4000000, '4000000');
INSERT INTO `mydatabase`.`t_user`(`id`, `name`) VALUES (5000001, '5000001');
INSERT INTO `mydatabase`.`t_user`(`id`, `name`) VALUES (9000000, '9000000');
INSERT INTO `mydatabase`.`t_user`(`id`, `name`) VALUES (10000001, '10000001');
INSERT INTO `mydatabase`.`t_user`(`id`, `name`) VALUES (14000000, '14000000');

<table name="t_user" dataNode="dn1,dn2,dn3" primaryKey="id" rule="auto-sharding-long">
    <childTable name="t_loginlog" primaryKey="id" joinKey="user_id" parentKey="id"></childTable>
</table>

INSERT INTO `mydatabase`.`t_loginlog`(`id`, `user_id`, `create_time`) VALUES (1, 1, now());
INSERT INTO `mydatabase`.`t_loginlog`(`id`, `user_id`, `create_time`) VALUES (2, 5000001, now());
INSERT INTO `mydatabase`.`t_loginlog`(`id`, `user_id`, `create_time`) VALUES (3, 14000000, now());

<tableRule name="student_id">
    <rule>
         <columns>id</columns>
         <algorithm>student_text</algorithm>
    </rule>
</tableRule>
<!--在conf中需要添加student_text.txt规则文件-->
<function name="student_text"class="io.mycat.route.function.AutoPartitionByLong">
     <property name="mapFile">student_text.txt</property>
</function>

INSERT INTO `mydatabase`.`t_student`(`id`, `s_name`) VALUES (0, '00');
INSERT INTO `mydatabase`.`t_student`(`id`, `s_name`) VALUES (1, '111');
INSERT INTO `mydatabase`.`t_student`(`id`, `s_name`) VALUES (10000, '10000');
INSERT INTO `mydatabase`.`t_student`(`id`, `s_name`) VALUES (10001, '10001');
INSERT INTO `mydatabase`.`t_student`(`id`, `s_name`) VALUES (20000, '20000');

package io.mycat.route.function;

import java.io.BufferedReader;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.HashSet;
import java.util.LinkedList;
import java.util.Set;

import io.mycat.config.model.rule.RuleAlgorithm;

/**
 * auto partition by Long ,can be used in auto increment primary key partition
 * 
 * @author wuzhi
 */
public class AutoPartitionByLong extends AbstractPartitionAlgorithm implements RuleAlgorithm{

	private String mapFile;
	private LongRange[] longRongs;
	
	private int defaultNode = -1;
	@Override
	public void init() {

		initialize();
	}

	public void setMapFile(String mapFile) {
		this.mapFile = mapFile;
	}

	@Override
	public Integer calculate(String columnValue)  {
//		columnValue = NumberParseUtil.eliminateQoute(columnValue);
		try {
			long value = Long.parseLong(columnValue);
			Integer rst = null;
			for (LongRange longRang : this.longRongs) {
				if (value <= longRang.valueEnd && value >= longRang.valueStart) {
					return longRang.nodeIndx;
				}
			}
			//数据超过范围，暂时使用配置的默认节点
			if (rst == null && defaultNode >= 0) {
				return defaultNode;
			}
			return rst;
		} catch (NumberFormatException e){
			throw new IllegalArgumentException(new StringBuilder().append("columnValue:").append(columnValue).append(" Please eliminate any quote and non number within it.").toString(),e);
		}
	}
	
	@Override
	public Integer[] calculateRange(String beginValue, String endValue)  {
		return AbstractPartitionAlgorithm.calculateSequenceRange(this, beginValue, endValue);
	}

	@Override
	public int getPartitionNum() {
//		int nPartition = longRongs.length;
		
		/*
		 * fix #1284 这里的统计应该统计Range的nodeIndex的distinct总数
		 */
		Set<Integer> distNodeIdxSet = new HashSet<Integer>();
		for(LongRange range : longRongs) {
			distNodeIdxSet.add(range.nodeIndx);
		}
		int nPartition = distNodeIdxSet.size();
		return nPartition;
	}

	private void initialize() {
		BufferedReader in = null;
		try {
			// FileInputStream fin = new FileInputStream(new File(fileMapPath));
			InputStream fin = this.getClass().getClassLoader()
					.getResourceAsStream(mapFile);
			if (fin == null) {
				throw new RuntimeException("can't find class resource file "
						+ mapFile);
			}
			in = new BufferedReader(new InputStreamReader(fin));
			LinkedList<LongRange> longRangeList = new LinkedList<LongRange>();

			for (String line = null; (line = in.readLine()) != null;) {
				line = line.trim();
				if (line.startsWith("#") || line.startsWith("//")) {
					continue;
				}
				int ind = line.indexOf('=');
				if (ind < 0) {
					System.out.println(" warn: bad line int " + mapFile + " :"
							+ line);
					continue;
				}
					String pairs[] = line.substring(0, ind).trim().split("-");
					long longStart = NumberParseUtil.parseLong(pairs[0].trim());
					long longEnd = NumberParseUtil.parseLong(pairs[1].trim());
					int nodeId = Integer.parseInt(line.substring(ind + 1)
							.trim());
					longRangeList
							.add(new LongRange(nodeId, longStart, longEnd));

			}
			longRongs = longRangeList.toArray(new LongRange[longRangeList
					.size()]);
		} catch (Exception e) {
			if (e instanceof RuntimeException) {
				throw (RuntimeException) e;
			} else {
				throw new RuntimeException(e);
			}

		} finally {
			try {
				in.close();
			} catch (Exception e2) {
			}
		}
	}
	
	public int getDefaultNode() {
		return defaultNode;
	}

	public void setDefaultNode(int defaultNode) {
		this.defaultNode = defaultNode;
	}

	static class LongRange {
		public final int nodeIndx;
		public final long valueStart;
		public final long valueEnd;

		public LongRange(int nodeIndx, long valueStart, long valueEnd) {
			super();
			this.nodeIndx = nodeIndx;
			this.valueStart = valueStart;
			this.valueEnd = valueEnd;
		}

	}
}

#mycat管理端口
mysql -h mycat_ip  -u databaseName -P9066 -ppassword
show @@help;

#会加载schema.xml配置的调整。
reload @@config;

#刷新全部配置
reload @@config_all;