sharding-jdbc是当当开源的一款分库分表的数据访问层框架,能对mysql很方便的分库、分表,基本不用修改原有代码,只要配置一下即可,完整的配置参考以下内容:
1 <?xml version="1.0" encoding="UTF-8"?>
2 <beans xmlns="http://www.springframework.org/schema/beans"
3 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
4 xmlns:context="http://www.springframework.org/schema/context"
5 xmlns:tx="http://www.springframework.org/schema/tx"
6 xsi:schemaLocation="http://www.springframework.org/schema/beans
7 http://www.springframework.org/schema/beans/spring-beans.xsd
8 http://www.springframework.org/schema/tx
9 http://www.springframework.org/schema/tx/spring-tx.xsd
10 http://www.springframework.org/schema/context
11 http://www.springframework.org/schema/context/spring-context.xsd">
12
13 <context:component-scan base-package="com.cnblogs.yjmyzz.sharding"/>
14
15 <bean id="propertiesFactoryBean"
16 class="org.springframework.beans.factory.config.PropertiesFactoryBean">
17 <property name="locations">
18 <list>
19 <value>classpath:properties/jdbc.properties</value>
20 </list>
21 </property>
22 </bean>
23
24 <context:property-placeholder properties-ref="propertiesFactoryBean" ignore-unresolvable="true"/>
25
26 <!--父数据源-->
27 <bean id="parentDataSource" class="com.alibaba.druid.pool.DruidDataSource" init-method="init"
28 destroy-method="close">
29 <property name="driverClassName" value="${jdbc-driver}"/>
30 <property name="url" value="${jdbc-url-0}"/>
31 <property name="username" value="${jdbc-user-0}"/>
32 <property name="password" value="${jdbc-password-0}"/>
33 <property name="filters" value="stat"/>
34 <property name="maxActive" value="20"/>
35 <property name="initialSize" value="1"/>
36 <property name="maxWait" value="60000"/>
37 <property name="minIdle" value="1"/>
38 <property name="timeBetweenEvictionRunsMillis" value="3000"/>
39 <property name="minEvictableIdleTimeMillis" value="300000"/>
40 <property name="validationQuery" value="SELECT 'x'"/>
41 <property name="testWhileIdle" value="true"/>
42 <property name="testOnBorrow" value="false"/>
43 <property name="testOnReturn" value="false"/>
44 <property name="poolPreparedStatements" value="true"/>
45 <property name="maxPoolPreparedStatementPerConnectionSize" value="20"/>
46 <property name="connectionInitSqls" value="set names utf8mb4;"/>
47 </bean>
48
49 <!--数据源0-->
50 <bean id="ds_0" parent="parentDataSource">
51 <property name="driverClassName" value="${jdbc-driver}"/>
52 <property name="url" value="${jdbc-url-0}"/>
53 <property name="username" value="${jdbc-user-0}"/>
54 <property name="password" value="${jdbc-password-0}"/>
55 </bean>
56
57 <!--数据源1-->
58 <bean id="ds_1" parent="parentDataSource">
59 <property name="driverClassName" value="${jdbc-driver}"/>
60 <property name="url" value="${jdbc-url-1}"/>
61 <property name="username" value="${jdbc-user-1}"/>
62 <property name="password" value="${jdbc-password-1}"/>
63 </bean>
64
65 <!--数据源2-->
66 <bean id="ds_2" parent="parentDataSource">
67 <property name="driverClassName" value="${jdbc-driver}"/>
68 <property name="url" value="${jdbc-url-2}"/>
69 <property name="username" value="${jdbc-user-2}"/>
70 <property name="password" value="${jdbc-password-2}"/>
71 </bean>
72
73 <!--真正使用的数据源-->
74 <bean id="dataSource" class="com.dangdang.ddframe.rdb.sharding.api.rule.DataSourceRule">
75 <constructor-arg>
76 <map>
77 <entry key="ds_0" value-ref="ds_0"/>
78 <entry key="ds_1" value-ref="ds_1"/>
79 <entry key="ds_2" value-ref="ds_2"/>
80 </map>
81 </constructor-arg>
82 </bean>
83
84 <!--t_order的"分表"设置:分N个表 -->
85 <bean id="orderTableRule" class="com.dangdang.ddframe.rdb.sharding.api.rule.TableRule">
86 <constructor-arg value="t_order" index="0"/>
87 <constructor-arg index="1">
88 <list>
89 <value>t_order_0</value>
90 <value>t_order_1</value>
91 </list>
92 </constructor-arg>
93 <constructor-arg index="2" ref="dataSource"/>
94 </bean>
95
96 <!--分库的sharding规则:按user_id分库 -->
97 <bean id="databaseShardingStrategy"
98 class="com.dangdang.ddframe.rdb.sharding.api.strategy.database.DatabaseShardingStrategy">
99 <constructor-arg index="0" value="user_id"/>
100 <constructor-arg index="1">
101 <bean class="com.cnblogs.yjmyzz.sharding.algorithm.SingleKeyModuloDatabaseShardingAlgorithm">
102 <!--dbount的值要跟上面dataSource的个数匹配-->
103 <property name="dbCount" value="3"/>
104 </bean>
105 </constructor-arg>
106 </bean>
107
108 <!--分表的规则:按order_id分表-->
109 <bean id="tableShardingStrategy" class="com.dangdang.ddframe.rdb.sharding.api.strategy.table.TableShardingStrategy">
110 <constructor-arg index="0" value="order_id"/>
111 <constructor-arg index="1">
112 <bean class="com.cnblogs.yjmyzz.sharding.algorithm.SingleKeyModuloTableShardingAlgorithm">
113 <!--tableCount的值要跟上面t_order表设置的分表个数保持一致-->
114 <property name="tableCount" value="2"/>
115 </bean>
116 </constructor-arg>
117 </bean>
118
119 <!--sharding规则Bean-->
120 <bean id="shardingRule" class="com.dangdang.ddframe.rdb.sharding.api.rule.ShardingRule">
121 <constructor-arg index="0" ref="dataSource"/>
122 <constructor-arg index="1">
123 <list>
124 <ref bean="orderTableRule"/>
125 </list>
126 </constructor-arg>
127 <constructor-arg index="2" ref="databaseShardingStrategy"/>
128 <constructor-arg index="3" ref="tableShardingStrategy"/>
129 </bean>
130
131 <!--sharding数据源-->
132 <bean id="shardingDataSource" class="com.dangdang.ddframe.rdb.sharding.api.ShardingDataSource">
133 <constructor-arg ref="shardingRule"/>
134 </bean>
135
136 <!--sharding事务管理器-->
137 <!--<bean id="transactionManager"-->
138 <!--class="org.springframework.jdbc.datasource.DataSourceTransactionManager">-->
139 <!--<property name="dataSource" ref="shardingDataSource"/>-->
140 <!--</bean>-->
141
142 <!--<tx:annotation-driven transaction-manager="transactionManager"/>-->
143
144 <!--mybatis配置-->
145 <bean id="sqlSessionFactory" class="org.mybatis.spring.SqlSessionFactoryBean">
146 <property name="configLocation" value="classpath:mybatis-config.xml"></property>
147 <property name="dataSource" ref="shardingDataSource"/>
148 <property name="mapperLocations" value="classpath:mybatis/OrderMapper.xml"/>
149 </bean>
150
151 <bean class="org.mybatis.spring.mapper.MapperScannerConfigurer">
152 <property name="basePackage" value="com.cnblogs.yjmyzz.sharding.mapper"/>
153 <property name="sqlSessionFactoryBeanName" value="sqlSessionFactory"/>
154 </bean>
155
156 </beans>
上面的配置,表示T_Order表按user_id进行分成ds_0,ds_1,ds_2共三库,每个库中又按order_id分成T_Order_0,T_Order_1二张表。
分库、分表是按常见的取模算法处理的,需要用户自定义二个类(基本上就是模板代码,不需要什么改动)
SingleKeyModuloDatabaseShardingAlgorithm
1 /**
2 * Copyright 1999-2015 dangdang.com.
3 * <p>
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 * <p/>
8 * http://www.apache.org/licenses/LICENSE-2.0
9 * <p/>
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 * </p>
16 */
17
18 package com.cnblogs.yjmyzz.sharding.algorithm;
19
20 import com.dangdang.ddframe.rdb.sharding.api.ShardingValue;
21 import com.dangdang.ddframe.rdb.sharding.api.strategy.database.SingleKeyDatabaseShardingAlgorithm;
22 import com.google.common.collect.Range;
23
24 import java.util.Collection;
25 import java.util.LinkedHashSet;
26
27 public final class SingleKeyModuloDatabaseShardingAlgorithm implements SingleKeyDatabaseShardingAlgorithm<Integer> {
28
29 private int dbCount = 1;
30
31 @Override
32 public String doEqualSharding(final Collection<String> availableTargetNames, final ShardingValue<Integer> shardingValue) {
33 for (String each : availableTargetNames) {
34 if (each.endsWith(shardingValue.getValue() % dbCount + "")) {
35 return each;
36 }
37 }
38 throw new UnsupportedOperationException();
39 }
40
41 @Override
42 public Collection<String> doInSharding(final Collection<String> availableTargetNames, final ShardingValue<Integer> shardingValue) {
43 Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
44 Collection<Integer> values = shardingValue.getValues();
45 for (Integer value : values) {
46 for (String dataSourceName : availableTargetNames) {
47 if (dataSourceName.endsWith(value % dbCount + "")) {
48 result.add(dataSourceName);
49 }
50 }
51 }
52 return result;
53 }
54
55 @Override
56 public Collection<String> doBetweenSharding(final Collection<String> availableTargetNames, final ShardingValue<Integer> shardingValue) {
57 Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
58 Range<Integer> range = shardingValue.getValueRange();
59 for (Integer i = range.lowerEndpoint(); i <= range.upperEndpoint(); i++) {
60 for (String each : availableTargetNames) {
61 if (each.endsWith(i % dbCount + "")) {
62 result.add(each);
63 }
64 }
65 }
66 return result;
67 }
68
69 /**
70 * 设置database分库的个数
71 * @param dbCount
72 */
73 public void setDbCount(int dbCount) {
74 this.dbCount = dbCount;
75 }
76 }
SingleKeyModuloTableShardingAlgorithm
1 /**
2 * Copyright 1999-2015 dangdang.com.
3 * <p>
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 * <p/>
8 * http://www.apache.org/licenses/LICENSE-2.0
9 * <p/>
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 * </p>
16 */
17
18 package com.cnblogs.yjmyzz.sharding.algorithm;
19
20 import com.dangdang.ddframe.rdb.sharding.api.ShardingValue;
21 import com.dangdang.ddframe.rdb.sharding.api.strategy.table.SingleKeyTableShardingAlgorithm;
22 import com.google.common.collect.Range;
23
24 import java.util.Collection;
25 import java.util.LinkedHashSet;
26
27 public final class SingleKeyModuloTableShardingAlgorithm implements SingleKeyTableShardingAlgorithm<Integer> {
28
29 private int tableCount = 1;
30
31 @Override
32 public String doEqualSharding(final Collection<String> availableTargetNames, final ShardingValue<Integer> shardingValue) {
33 for (String each : availableTargetNames) {
34 if (each.endsWith(shardingValue.getValue() % tableCount + "")) {
35 return each;
36 }
37 }
38 throw new UnsupportedOperationException();
39 }
40
41 @Override
42 public Collection<String> doInSharding(final Collection<String> availableTargetNames, final ShardingValue<Integer> shardingValue) {
43 Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
44 Collection<Integer> values = shardingValue.getValues();
45 for (Integer value : values) {
46 for (String tableNames : availableTargetNames) {
47 if (tableNames.endsWith(value % tableCount + "")) {
48 result.add(tableNames);
49 }
50 }
51 }
52 return result;
53 }
54
55 @Override
56 public Collection<String> doBetweenSharding(final Collection<String> availableTargetNames, final ShardingValue<Integer> shardingValue) {
57 Collection<String> result = new LinkedHashSet<>(availableTargetNames.size());
58 Range<Integer> range = shardingValue.getValueRange();
59 for (Integer i = range.lowerEndpoint(); i <= range.upperEndpoint(); i++) {
60 for (String each : availableTargetNames) {
61 if (each.endsWith(i % tableCount + "")) {
62 result.add(each);
63 }
64 }
65 }
66 return result;
67 }
68
69 /**
70 * 设置分表的个数
71 *
72 * @param tableCount
73 */
74 public void setTableCount(int tableCount) {
75 this.tableCount = tableCount;
76 }
77 }
然后mybatis里就可以类似常规操作一样来写sql了,具体可参考源码中的示例代码。
不过,经个人测试发现一些小问题,以避免大家踩坑:
1、聚合函数的使用要特别小心,我试了下max/min/count这几个函数,返回时记得给返回结果加字段别名,即: select count(*) order_count from t_order,否则可能返回的结果不正确(已经向作者反馈,估计很快会修复该bug)
2、另外分库的key,不支持范围搜索,类似 select * from t_order where user_id > 100的操作,直接报错,如果需要这样的操作,建议先取max(user_id),比如最大用户id为120,然后user_id in (101,102...120) 或者 between ... and 这样处理。
3、如果采用druid数据源,目前有点不稳定,偶尔会出异常,建议采用dbcp(跟作者反馈了下,说是很快会修复该问题)
4、批量插入问题,insert xxx values(...),(...),(...) 不支持,主要原因是因为要插入的记录,无法定位分片。但是可以适当预处理下变通解决,思路:按db-key将List<T>中的对象先划分成Map<dbkey,List<T>>,然后每个entry的List<T>再按tableKey做同样的map映射,即:将List<T>变成Map<dbkey,Map<tableKey,List<T>> 这种结构,相当于人工把同一分片的数据整理到一起,再做insert批量插入就可以了。
其它一些使用上的限制,参考:
http://dangdangdotcom.github.io/sharding-jdbc/post/limitations/
最后,我在github上放了一个示例代码sharding-jdbc-sample,需要的同学可以参考