一、多数据源问题
主要思路是把dataSource、sqlSesstionFactory、MapperScannerConfigurer在配置中区分开，各Mapper对应的包名、类名区分开
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" xmlns:aop="http://www.springframework.org/schema/aop"
4 xmlns:tx="http://www.springframework.org/schema/tx" xmlns:jdbc="http://www.springframework.org/schema/jdbc"
5 xmlns:context="http://www.springframework.org/schema/context"
6 xsi:schemaLocation="
7 http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-3.0.xsd
8 http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd
9 http://www.springframework.org/schema/jdbc http://www.springframework.org/schema/jdbc/spring-jdbc-3.0.xsd
10 http://www.springframework.org/schema/tx http://www.springframework.org/schema/tx/spring-tx-3.0.xsd
11 http://www.springframework.org/schema/aop http://www.springframework.org/schema/aop/spring-aop-3.0.xsd"
12 default-autowire="byName">
13
14 <bean id="dataSource1" class="org.h2.jdbcx.JdbcConnectionPool"
15 destroy-method="dispose">
16 <constructor-arg>
17 <bean class="org.h2.jdbcx.JdbcDataSource">
18 <property name="URL" value="jdbc:h2:r:/h2db/awbprint/a"/>
19 <property name="user" value="sa"/>
20 <property name="password" value="sa"/>
21 </bean>
22 </constructor-arg>
23 </bean>
24
25
26 <bean id="dataSource2" class="org.h2.jdbcx.JdbcConnectionPool"
27 destroy-method="dispose">
28 <constructor-arg>
29 <bean class="org.h2.jdbcx.JdbcDataSource">
30 <property name="URL" value="jdbc:h2:r:/h2db/awbprint/b"/>
31 <property name="user" value="sa"/>
32 <property name="password" value="sa"/>
33 </bean>
34 </constructor-arg>
35 </bean>
36
37 <bean id="sqlSessionFactory1" class="org.mybatis.spring.SqlSessionFactoryBean">
38 <property name="dataSource" ref="dataSource1"/>
39 <property name="configLocation" value="classpath:mybatis-config.xml"></property>
40 <property name="typeAliasesPackage" value="awbprint.mybatis.entity"></property>
41 <property name="mapperLocations" value="classpath:mybatis/a/**/*.xml"></property>
42 </bean>
43
44 <bean id="sqlSessionFactory2" class="org.mybatis.spring.SqlSessionFactoryBean">
45 <property name="dataSource" ref="dataSource2"/>
46 <property name="configLocation" value="classpath:mybatis-config.xml"></property>
47 <property name="typeAliasesPackage" value="awbprint.mybatis.entity"></property>
48 <property name="mapperLocations" value="classpath:mybatis/b/**/*.xml"></property>
49 </bean>
50
51 <bean class="org.mybatis.spring.mapper.MapperScannerConfigurer">
52 <property name="sqlSessionFactoryBeanName" value="sqlSessionFactory1"></property>
53 <property name="basePackage" value="awbprint.mybatis.mapper.a"/>
54 </bean>
55
56 <bean class="org.mybatis.spring.mapper.MapperScannerConfigurer">
57 <property name="sqlSessionFactoryBeanName" value="sqlSessionFactory2"></property>
58 <property name="basePackage" value="awbprint.mybatis.mapper.b"/>
59 </bean>
60
61
62 </beans>
上面的配置，一个连h2的a数据库，一个连h2的b数据库，至于事务管理器，大家可参考这个思路，建二个，各管各的。
项目中mapper接口及映射文件均用包名区分开，如下图：
二、如何使用Map做为参数及动态条件生成
1 <resultMap id="BaseResultMap" type="awbprint.mybatis.entity.PrintLayout">
2 <id column="D_RECID" property="recid" jdbcType="DECIMAL"/>
3 <result column="D_USER_NAME" property="userName" jdbcType="VARCHAR"/>
4 <result column="D_NAME" property="name" jdbcType="VARCHAR"/>
5 <result column="D_TYPE" property="type" jdbcType="VARCHAR"/>
6 ...
7
8 </resultMap>
9
10 <sql id="Base_Column_List">
11 D_RECID, D_USER_NAME, D_NAME, D_TYPE, ...
12 </sql>
13
14 <select id="select" resultMap="BaseResultMap"
15 parameterType="java.util.Map">
16 select
17 <include refid="Base_Column_List"/>
18 from T_PRINT_LAYOUT
19 where D_USER_NAME = #{userName,jdbcType=VARCHAR} and D_TYPE = #{awbType,jdbcType=VARCHAR}
20 <if test="recId != null">
21 and D_RECID = #{recId,jdbcType=DECIMAL}
22 </if>
23 <if test="ids != null">
24 or D_RECID in
25 <foreach item="item" index="index" collection="ids"
26 open="(" separator="," close=")">
27 #{item}
28 </foreach>
29 </if>
30
31 </select>
14-31演示了如何使用Map做为参数，动态传入查询条件，及List参数生成in(...)条件
java端代码示例：
1 PrintLayoutMapper mapper = context.getBean(PrintLayoutMapper.class);
2
3 Map<String, Object> map = new HashMap<String, Object>();
4 map.put("userName", "ADMIN");
5 map.put("awbType", "CARGOLABEL_MU");
6 map.put("recId", 1);
7
8 List<Integer> ids = new ArrayList<Integer>();
9 ids.add(0, 1);
10 ids.add(0, 2);
11 ids.add(0, 3);
12
13 map.put("ids", ids);
14
15 List<?> list = mapper.select(map);
其实PrintLayoutMapper接口的定义为：
1 public interface PrintLayoutMapper {
2 ...
3
4 List<PrintLayout> select(Map<String, Object> map);
5 }最终生成的SQL语句为：
1 select D_RECID, D_USER_NAME, D_NAME, D_TYPE, ... from T_PRINT_LAYOUT where D_USER_NAME = ? and D_TYPE = ? and D_RECID = ? or D_RECID in ( ? , ? , ? )
三、兼容不同的数据库
1 <insert id="insert">
2 <selectKey keyProperty="id" resultType="int" order="BEFORE">
3 <if test="_databaseId == 'oracle'">
4 select seq_users.nextval from dual
5 </if>
6 <if test="_databaseId == 'db2'">
7 select nextval for seq_users from sysibm.sysdummy1"
8 </if>
9 </selectKey>
10 insert into users values (#{id}, #{name})
11 </insert>
这是官方文档上的示例，演示了如何兼容oracle与db2这二种不同的数据库，来获取序列的下一个值
四、加强版的分支、选择判断
1 <select id="findActiveBlogLike"
2 resultType="Blog">
3 SELECT * FROM BLOG WHERE state = ‘ACTIVE’
4 <choose>
5 <when test="title != null">
6 AND title like #{title}
7 </when>
8 <when test="author != null and author.name != null">
9 AND author_name like #{author.name}
10 </when>
11 <otherwise>
12 AND featured = 1
13 </otherwise>
14 </choose>
15 </select>
这也是官方文档上的示例，因为<if>...</if>并没对应的<else>标签，所以要达到<if>...<else>...</else> </if>的效果，得借助<choose>、<when>、<otherwise>组合使用。
五、避免Where 空条件的尴尬
1 <select id="findActiveBlogLike" resultType="Blog">
2 SELECT * FROM BLOG
3 WHERE
4 <if test="state != null">
5 state = #{state}
6 </if>
7 </select>
如果state参数为空时，最终生成SQL语句为
1 SELECT * FROM BLOG
2 WHERE
执行会出错，当然，你可以在where 后加一个1=1，改成
1 <select id="findActiveBlogLike" resultType="Blog">
2 SELECT * FROM BLOG
3 WHERE 1=1
4 <if test="state != null">
5 and state = #{state}
6 </if>
7 </select>
但是这个做法不太“环保”（毕竟引入了一个垃圾条件），其实只要改成<where>...</where>即可
1 <select id="findActiveBlogLike" resultType="Blog">
2 SELECT * FROM BLOG
3 <where>
4 <if test="state != null">
5 and state = #{state}
6 </if>
7 </where>
8 </select>
六、$与#的区别
1 select * from T_PRINT_LAYOUT where D_RECID = ${recId}最后生成的SQL为：
1 select * from T_PRINT_LAYOUT where D_RECID = 1
即：直接将参数值替换到了原来${recId}的位置，相当于硬拼SQL
1 select * from T_PRINT_LAYOUT where D_RECID = #{recid,jdbcType=DECIMAL}最后生成的SQL为：
1 select * from T_PRINT_LAYOUT where D_RECID = ?
即：#{...}被识别为一个SQL参数
七、大量数据的批量insert
大量数据(条数>10000)做insert时，如果按常规方式，每条insert into table(...) values(...);来提交，速度巨慢。改善性能的思路是多条insert批量提交。
oracle环境中，有一种批量insert的小技巧，原理是 insert into ... select from ...，套在mybatis上，变形为：
1 INSERT INTO T_TEST
2 (ID, COL_A, COL_B)
3 SELECT SEQ_TEST.NEXTVAL, A.*
4 FROM (
5 SELECT 'A1', 'B1' FROM DUAL
6 UNION ALL SELECT 'A2', 'B2' FROM DUAL
7 UNION ALL SELECT 'A3', 'B3' FROM DUAL
8 UNION ALL SELECT 'A4', 'B4' FROM DUAL
9 UNION ALL SELECT 'A5', 'B5' FROM DUAL
10 UNION ALL SELECT 'A6', 'B6' FROM DUAL
11 ) A
中间的部分非常有规律，可以用foreach标签生成，参考下面的片段：
1 <insert id="insertBatch2" parameterType="ctas.entity.SharkFlt">
2 <selectKey keyProperty="recId" order="BEFORE" resultType="Long">
3 select SEQ_CTAS_SHARK_FLT.nextval as recId from dual
4 </selectKey>
5 insert into CTAS_SHARK_FLT (<include refid="Base_Column_List"/>) SELECT SEQ_TEST.NEXTVAL, A.*
6 FROM (
7 <foreach collection="list" item="item" index="index" open="" close="" separator="union all">
8 select #{item.awbType,jdbcType=VARCHAR}, #{item.awbPre,jdbcType=VARCHAR},... from dual
9 </foreach>
10 ) A
11 </insert>
即使这样，也不能直接run，oracle中一次执行的sql语句长度是有限制的，如果最后拼出来的sql字符串过长，会导致执行失败，所以java端还要做一个分段处理，参考下面的处理:
1 List<SharkFlt> data = new ArrayList<SharkFlt>();
2 for (TSharkFlt f : sharkFlts) {
3 data.add(getSharkFlt(f));
4 }
5
6 System.out.println(data.size());
7
8 long beginTime = System.currentTimeMillis();
9 System.out.println("开始插入...");
10 SqlSessionFactory sqlSessionFactory = ctx.getBean(SqlSessionFactory.class);
11 SqlSession session = null;
12 try {
13 session = sqlSessionFactory.openSession(ExecutorType.BATCH, false);
14 int a = 2000;//每次提交2000条
15 int loop = (int) Math.ceil(data.size() / (double) a);
16
17 List<SharkFlt> tempList = new ArrayList<SharkFlt>(a);
18 int start, stop;
19 for (int i = 0; i < loop; i++) {
20 tempList.clear();
21 start = i * a;
22 stop = Math.min(i * a + a - 1, data.size() - 1);
23 System.out.println("range:" + start + " - " + stop);
24 for (int j = start; j <= stop; j++) {
25 tempList.add(data.get(j));
26 }
27 session.insert("ctas.importer.writer.mybatis.mappper.SharkFltMapper.insertBatch2", tempList);
28 session.commit();
29 session.clearCache();
30 System.out.println("已经插入" + (stop + 1) + " 条");
31 }
32 } catch (Exception e) {
33 e.printStackTrace();
34 session.rollback();
35 } finally {
36 if (session != null) {
37 session.close();
38 }
39 }
40 long endTime = System.currentTimeMillis();
41 System.out.println("插入完成，耗时 " + (endTime - beginTime) + " 毫秒！");
13,27-29这几行是关键，这一段逻辑会经常使用，为了重用，可以封装一下：
1 /**
2 * 批量提交数据
3 * @param sqlSessionFactory
4 * @param mybatisSQLId SQL语句在Mapper XML文件中的ID
5 * @param commitCountEveryTime 每次提交的记录数
6 * @param list 要提交的数据列表
7 * @param logger 日志记录器
8 */
9 private <T> void batchCommit(SqlSessionFactory sqlSessionFactory, String mybatisSQLId, int commitCountEveryTime, List<T> list, Logger logger) {
10 SqlSession session = null;
11 try {
12 session = sqlSessionFactory.openSession(ExecutorType.BATCH, false);
13 int commitCount = (int) Math.ceil(list.size() / (double) commitCountEveryTime);
14 List<T> tempList = new ArrayList<T>(commitCountEveryTime);
15 int start, stop;
16 Long startTime = System.currentTimeMillis();
17 for (int i = 0; i < commitCount; i++) {
18 tempList.clear();
19 start = i * commitCountEveryTime;
20 stop = Math.min(i * commitCountEveryTime + commitCountEveryTime - 1, list.size() - 1);
21 for (int j = start; j <= stop; j++) {
22 tempList.add(list.get(j));
23 }
24 session.insert(mybatisSQLId, tempList);
25 session.commit();
26 session.clearCache();
27 }
28 Long endTime = System.currentTimeMillis();
29 logger.debug("batchCommit耗时：" + (endTime - startTime) + "毫秒");
30 } catch (Exception e) {
31 logger.error("batchCommit error!", e);
32 e.printStackTrace();
33 session.rollback();
34 } finally {
35 if (session != null) {
36 session.close();
37 }
38 }
39 }
对应的，如果是批量update，也是类似的思路，只不过要注意一点：oracle环境中，多条语句提交的sql语句为
begin
update xxx set xxx =xxx ;
update xxx set xxx =xxx;
end;
用mytais拼的时候，参考下面的写法：
1 <update id="updateBatch" parameterType="java.util.List">
2 <foreach collection="list" item="item" index="index" open="begin" close="end;" >
3 update xxx set x=#{item.x,jdbcType=VARCHAR} where x =#{item.x,jdbcType=VARCHAR};
4 </foreach>
5 </update>
关于批量提交的性能，Oracle环境下，我大概测试了一下：
insert into ... select xxx
union all select yyy
union all select zzz;
最快，其次是
begin
insert into ... values ...;
insert into ... values ...;
end;
当然最慢是逐条insert提交，最后谈下Spring与mybatis集成后，AOP事务管理 对 批量提交的影响 ，通常情况下，我们会这样配置AOP事务管理：
1 <tx:advice id="txAdvice" transaction-manager="transactionManager">
2 <tx:attributes>
3 <tx:method name="do*" read-only="false" rollback-for="java.lang.Exception"/>
4 <tx:method name="*" propagation="SUPPORTS" read-only="true"/>
5 </tx:attributes>
6 </tx:advice>
7
8 <aop:config>
9 <aop:pointcut id="pc" expression="execution(* ctas.service.*.*(..))"/>
10 <aop:advisor pointcut-ref="pc" advice-ref="txAdvice"/>
11 </aop:config>
这样，ctas.service（及子包）下的所有方法都被拦截，而且只有do开头的方法，具有可写的事务（即：能insert/update/delete记录），而其它方法是只读事务（即：只能select数据），但是我们前面谈到的批量提交操作，都是写代码手动提交的，不需要spring管理，所以配置中需要将某些方法排除，可以约定self开头的方法，由开发者自己管理事务，不需要spring代为管理，上面的配置要改成：
1 <aop:config>
2 <aop:pointcut id="pc" expression="execution(* ctas.service.*.*(..)) and !execution(* ctas.service.*.self*(..)))"/>
3 <aop:advisor pointcut-ref="pc" advice-ref="txAdvice"/>
4 </aop:config>
通过 and !execution(...) 将self开头的方法排除就可以了，前面的批量操作代码写到selfXXX方法中。
关于批量提交，还有一种情况：父子表的批量插入。思路还是一样的，但是SQL的写法有点区别，原理参考下面的语句(Oracle环境)
1 DECLARE
2 BASE_ID INTEGER;
3 DETAIL_ID INTEGER;
4 BEGIN
5 --第1组记录
6 SELECT SEQ_T_BASE.NEXTVAL INTO BASE_ID FROM DUAL;
7 INSERT INTO T_BASE (ID, FEE) VALUES (BASE_ID, ?);
8
9 SELECT SEQ_T_DETAIL.NEXTVAL INTO DETAIL_ID FROM DUAL;
10 INSERT INTO T_DETAIL (ID, BASE_ID, FEE) VALUES (DETAIL_ID, BASE_ID, ?);
11 SELECT SEQ_T_DETAIL.NEXTVAL INTO DETAIL_ID FROM DUAL;
12 INSERT INTO T_DETAIL (ID, BASE_ID, FEE) VALUES (DETAIL_ID, BASE_ID, ?);
13
14 --第2组记录
15 SELECT SEQ_T_BASE.NEXTVAL INTO BASE_ID FROM DUAL;
16 INSERT INTO T_BASE (ID, FEE) VALUES (BASE_ID, ?);
17
18 SELECT SEQ_T_DETAIL.NEXTVAL INTO DETAIL_ID FROM DUAL;
19 INSERT INTO T_DETAIL (ID, BASE_ID, FEE) VALUES (DETAIL_ID, BASE_ID, ?);
20 SELECT SEQ_T_DETAIL.NEXTVAL INTO DETAIL_ID FROM DUAL;
21 INSERT INTO T_DETAIL (ID, BASE_ID, FEE) VALUES (DETAIL_ID, BASE_ID, ?);
22
23 --...
24 END;
xml映射文件中的写法：
1 <insert id="insertBatch" parameterType="java.util.List">
2 DECLARE
3 base_id INTEGER ;
4 detail_id INTEGER ;
5 <foreach collection="list" item="item" index="index" open="begin" close="end;">
6 select seq_t_base.nextval into base_id from dual;
7 insert into t_base(id, fee) values(base_id, #{item.baseEntity.fee,jdbcType=DECIMAL});
8 <foreach collection="item.details" item="detail" index="index">
9 select seq_t_detail.nextval into detail_id from dual;
10 insert into t_detail(id, base_id, fee) values(detail_id,base_id,#{detail.fee,jdbcType=DECIMAL});
11 </foreach>
12 </foreach>
13 </insert>
List中的Dto定义
1 public class BaseDetailDto {
2
3 private TBase baseEntity;
4
5 private List<TDetail> details;
6
7 public TBase getBaseEntity() {
8 return baseEntity;
9 }
10
11 public void setBaseEntity(TBase baseEntity) {
12 this.baseEntity = baseEntity;
13 }
14
15
16 public List<TDetail> getDetails() {
17 return details;
18 }
19
20 public void setDetails(List<TDetail> details) {
21 this.details = details;
22 }
23 }
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