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/** * 分库数量 */public static final int DB_COUNT = 4;
/** * 获取数据库分库索引号 * * @param buyerId 会员ID * @return */public static int indexDbByBuyerId(Long buyerId) { return (Math.abs(buyerId.hashCode()) % 4096) / (4096 / DB_COUNT);}

X * 步长 + (Y-1) * (库数量 * 步长)

X * 步长 + (Y-1) * (库数量 * 步长) + (1000 -1)

import lombok.Setter;import org.apache.commons.lang3.time.DateFormatUtils;
/** * 问题单ID构建器 * <p> * ID格式(18位)：6位日期 + 2位版本号 + 2位库索引号 + 8位序列号 * 示例：180903010300001111 * 说明这个问题单是2018年9月3号生成的，采用的01版本的ID生成规则，数据存放在03库，最后8位00001111是生成的序列号ID。* 采用这种ID格式还有个好处就是每天都有1亿(8位)的序列号可用。* </p> */@Setterpublic class ProblemOrdIdBuilder { public static final int DB_COUNT = 4;  private static final String DATE_FORMATTER = "yyMMdd";
 private String version = "01"; private long buyerId; private long timeInMills; private long seqNum;
 public Long build() { int dbIndex = indexDbByBuyerId(buyerId); StringBuilder pid = new StringBuilder(18) .append(DateFormatUtils.format(timeInMills, DATE_FORMATTER)) .append(version) .append(String.format("%02d", dbIndex)) .append(String.format("%08d", seqNum % 10000000)); return Long.valueOf(pid.toString()); }
 /** * 获取数据库分库索引号 * * @param buyerId 会员ID * @return */ public int indexDbByBuyerId(Long buyerId) { return (Math.abs(buyerId.hashCode()) % 4096) / (4096 / DB_COUNT); }}

<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE beans PUBLIC "-//SPRING//DTD BEAN//EN" "http://www.springframework.org/dtd/spring-beans.dtd">
<beans> <bean id="vtabroot" class="com.taobao.tddl.interact.rule.VirtualTableRoot" init-method="init"> <property name="dbType" value="MYSQL" /> <property name="defaultDbIndex" value="PROBLEM_0000_GROUP" /> <property name="tableRules"> <map> <entry key="problem_ord" value-ref="problem_ord" /> <entry key="problem_operate_log" value-ref="problem_operate_log" /> </map> </property> </bean> <!-- 问题(诉求)单表 --> <bean id="problem_ord" class="com.taobao.tddl.interact.rule.TableRule"> <property name="dbNamePattern" value="PROBLEM_{0000}_GROUP" /> <property name="tbNamePattern" value="problem_ord_{0000}" /> <property name="dbRuleArray" value="((Math.abs(#buyer_id,1,4#.hashCode()) % 4096).intdiv(1024))" /> <property name="tbRuleArray"> <list> <value> <![CDATA[ def hashCode = Math.abs(#buyer_id,1,32#.hashCode()); int dbIndex = ((hashCode % 4096).intdiv(1024)) as int; int tableCountPerDb = 32 / 4; int tableIndexStart = dbIndex * tableCountPerDb; int tableIndexOffset = (hashCode % tableCountPerDb) as int; int tableIndex = tableIndexStart + tableIndexOffset; return tableIndex; ]]> </value> </list> </property> <property name="allowFullTableScan" value="false" /> </bean> <!-- 问题操作日志表 --> <bean id="problem_operate_log" class="com.taobao.tddl.interact.rule.TableRule"> <property name="dbNamePattern" value="PROBLEM_{0000}_GROUP" /> <property name="tbNamePattern" value="problem_operate_log_{0000}" /> <!-- 【#buyer_id,1,4#.hashCode()】 --> <!-- buyer_id 代表分片字段；1代表分库步长；4代表一共4个分库，当执行全表扫描时会用到 --> <property name="dbRuleArray" value="((Math.abs(#buyer_id,1,4#.hashCode()) % 4096).intdiv(1024))" /> <property name="tbRuleArray"> <list> <value> <![CDATA[ def hashCode = Math.abs(#buyer_id,1,512#.hashCode()); int dbIndex = ((hashCode % 4096).intdiv(1024)) as int; int tableCountPerDb = 512 / 4; int tableIndexStart = dbIndex * tableCountPerDb; int tableIndexOffset = (hashCode % tableCountPerDb) as int; int tableIndex = tableIndexStart + tableIndexOffset; return tableIndex; ]]> </value> </list> </property> <property name="allowFullTableScan" value="false" /> </bean></beans>

// 在 Java 中System.out.println(5 / 3); // 结果 = 1
// 在 Groovy 中println (5 / 3); // 结果 = 1.6666666667 println (5.intdiv(3)); // 结果 = 1（Groovy整除正确用法）