Executing Query for Paginated List (select)
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可以写个存储过程,IBATIS再调用来实现,但是Ibatis有它自己的便捷的方法,但是有其最大的缺点!以下说明局限及改进方法。
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在ibatis中有一个很吸引人的方法,queryForPaginatedList(java.lang.String id, int pageSize),可以返回 PaginatedList的对象,
实现翻页,刚才测试了一下PaginatedList,在1-2w行数据的时候还可以工作,但是在一个30w行的表里翻页,一次select用了363.031second
忍不住看了一下源,发现ibatis的分页依赖于数据库的jdbcDriver.
调用次序如下SqlMapClientImpl.queryForPaginatedList->SqlMapSessionImpl.queryForPaginatedList
->SqlMapExecutorDelegate.queryForPaginatedList->GeneralStatement.executeQueryForList
->GeneralStatment.executeQueryWithCallback->GeneralStatment.executeQueryWithCallback
->SqlExecutor.executeQuery->SqlExecutor.handleMultipleResults()
分页处理的函数如下
[code]
private void handleResults(RequestScope request, ResultSet rs, int skipResults, int maxResults, RowHandlerCallback callback) throws SQLException {
try {
request.setResultSet(rs);
ResultMap resultMap = request.getResultMap();
if (resultMap != null) {
// Skip Results
if (rs.getType() != ResultSet.TYPE_FORWARD_ONLY) {
if (skipResults > 0) {
rs.absolute(skipResults);
}
} else {
for (int i = 0; i < skipResults; i++) {
if (!rs.next()) {
return;
}
}
}
// Get Results
int resultsFetched = 0;
while ((maxResults == SqlExecutor.NO_MAXIMUM_RESULTS || resultsFetched < maxResults) && rs.next()) {
Object[] columnValues = resultMap.resolveSubMap(request, rs).getResults(request, rs);
callback.handleResultObject(request, columnValues, rs);
resultsFetched++;
}
}
} finally {
request.setResultSet(null);
}
}
[/code]
返回的PaginatedList实际上是PaginatedDataList类的对象,每次翻页的时候最后都会调用
[code]
private List getList(int idx, int localPageSize) throws SQLException {
return sqlMapExecutor.queryForList(statementName, parameterObject, (idx) * pageSize, localPageSize);
}
[/code]
这个方法,可见ibatis的分页机制要看jdbcDriver如何实现以及是否支持rs.absolute(skipResults)。
这种实现肯定不如数据库自己支持的分页方式来的快,一旦碰到数据量大的表,马上会死翘翘。
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以前用ibatis做分页的时候,是用的queryforList()方法,后面感觉不好,因为我看过一些ibatis的源码,感觉它好像是用resultset的滚动游标的方式实现的,这样如果数据量大会不会有问题呢?以前用jdbc的时候是用一个stringbuffer来构造oracle(我们用的是oracle,其它数据库有各自的方法)的三层钳套的sql语句的,做ibatis时语句都是写在xml配置文件里面的,不好做这种构造工作。后来想了葛简单的办法:
在domain包里面定义一个basedomain类:
public class Basedomain {
private int start;
private int end;
/**
* @return Returns the end.
*/
public int getEnd() {
return end;
}
/**
* @param end The end to set.
*/
public void setEnd(int end) {
this.end = end;
}
/**
* @return Returns the start.
*/
public int getStart() {
return start;
}
/**
* @param start The start to set.
*/
public void setStart(int start) {
this.start = start;
}
}
包含两个成员变量
start: 取数据时的起始位置
end: 取数据时的结束位置
然后各个实体类将继承这个basedomain类
然后在要分页的sql语句里面加上三层钳套的sql语句,两个rownum参数分别就是上面的start和end。
以下是一个示例:
select * from (select my_table.*,rownum as my_rownum from (
select name,password from user order by id desc
=#start# ]]>
这就是我的ibatis分页的办法,不知道大家觉得如何?呵呵!
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一直以来ibatis的分页都是通过滚动ResultSet实现的,应该算是逻辑分页吧。逻辑分页虽然能很干净地独立于特定数据库,但效率在多数情况下不及特定数据库支持的物理分页,而hibernate的分页则是直接组装sql,充分利用了特定数据库的分页机制,效率相对较高。本文讲述的就是如何在不重新编译ibatis源码的前提下,为ibatis引入hibernate式的物理分页机制。
基本思路就是找到ibatis执行sql的地方,截获sql并重新组装sql。通过分析ibatis源码知道,最终负责执行sql的类是com.ibatis.sqlmap.engine.execution.SqlExecutor,此类没有实现任何接口,这多少有点遗憾,因为接口是相对稳定契约,非大的版本更新,接口一般是不会变的,而类就相对易变一些,所以这里的代码只能保证对当前版本(2.1.7)的ibatis有效。下面是SqlExecutor执行查询的方法:
/**
* Long form of the method to execute a query
*
* @param request - the request scope
* @param conn - the database connection
* @param sql - the SQL statement to execute
* @param parameters - the parameters for the statement
* @param skipResults - the number of results to skip
* @param maxResults - the maximum number of results to return
* @param callback - the row handler for the query
*
* @throws SQLException - if the query fails
*/
public void executeQuery(RequestScope request, Connection conn, String sql, Object[] parameters,
int skipResults, int maxResults, RowHandlerCallback callback)
throws SQLException {
ErrorContext errorContext = request.getErrorContext();
errorContext.setActivity("executing query");
errorContext.setObjectId(sql);
PreparedStatement ps = null;
ResultSet rs = null;
try {
errorContext.setMoreInfo("Check the SQL Statement (preparation failed).");
Integer rsType = request.getStatement().getResultSetType();
if (rsType != null) {
ps = conn.prepareStatement(sql, rsType.intValue(), ResultSet.CONCUR_READ_ONLY);
} else {
ps = conn.prepareStatement(sql);
}
Integer fetchSize = request.getStatement().getFetchSize();
if (fetchSize != null) {
ps.setFetchSize(fetchSize.intValue());
}
errorContext.setMoreInfo("Check the parameters (set parameters failed).");
request.getParameterMap().setParameters(request, ps, parameters);
errorContext.setMoreInfo("Check the statement (query failed).");
ps.execute();
rs = getFirstResultSet(ps);
if (rs != null) {
errorContext.setMoreInfo("Check the results (failed to retrieve results).");
handleResults(request, rs, skipResults, maxResults, callback);
}
// clear out remaining results
while (ps.getMoreResults());
} finally {
try {
closeResultSet(rs);
} finally {
closeStatement(ps);
}
}
}
其中handleResults(request, rs, skipResults, maxResults, callback)一句用于处理分页,其实此时查询已经执行完毕,可以不必关心handleResults方法,但为清楚起见,下面来看看handleResults的实现:
private void handleResults(RequestScope request, ResultSet rs, int skipResults, int maxResults, RowHandlerCallback callback) throws SQLException {
try {
request.setResultSet(rs);
ResultMap resultMap = request.getResultMap();
if (resultMap != null) {
// Skip Results
if (rs.getType() != ResultSet.TYPE_FORWARD_ONLY) {
if (skipResults > 0) {
rs.absolute(skipResults);
}
} else {
for (int i = 0; i < skipResults; i++) {
if (!rs.next()) {
break;
}
}
}
// Get Results
int resultsFetched = 0;
while ((maxResults == SqlExecutor.NO_MAXIMUM_RESULTS || resultsFetched < maxResults) && rs.next()) {
Object[] columnValues = resultMap.resolveSubMap(request, rs).getResults(request, rs);
callback.handleResultObject(request, columnValues, rs);
resultsFetched++;
}
}
} finally {
request.setResultSet(null);
}
}
此处优先使用的是ResultSet的absolute方法定位记录,是否支持absolute取决于具体数据库驱动,但一般当前版本的数据库都支持该方法,如果不支持则逐条跳过前面的记录。由此可以看出如果数据库支持absolute,则ibatis内置的分页策略与特定数据库的物理分页效率差距就在于物理分页查询与不分页查询在数据库中的执行效率的差距了。因为查询执行后读取数据前数据库并未把结果全部返回到内存,所以本身在存储占用上应该差距不大,如果都使用索引,估计执行速度也差不太多。
继续我们的话题。其实只要在executeQuery执行前组装sql,然后将其传给executeQuery,并告诉handleResults我们不需要逻辑分页即可。拦截executeQuery可以采用aop动态实现,也可直接继承SqlExecutor覆盖executeQuery来静态地实现,相比之下后者要简单许多,而且由于SqlExecutor没有实现任何接口,比较易变,动态拦截反到增加了维护的工作量,所以我们下面来覆盖executeQuery:
package com.aladdin.dao.ibatis.ext;
import java.sql.Connection;
import java.sql.SQLException;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import com.aladdin.dao.dialect.Dialect;
import com.ibatis.sqlmap.engine.execution.SqlExecutor;
import com.ibatis.sqlmap.engine.mapping.statement.RowHandlerCallback;
import com.ibatis.sqlmap.engine.scope.RequestScope;
public class LimitSqlExecutor extends SqlExecutor {
private static final Log logger = LogFactory.getLog(LimitSqlExecutor.class);
private Dialect dialect;
private boolean enableLimit = true;
public Dialect getDialect() {
return dialect;
}
public void setDialect(Dialect dialect) {
this.dialect = dialect;
}
public boolean isEnableLimit() {
return enableLimit;
}
public void setEnableLimit(boolean enableLimit) {
this.enableLimit = enableLimit;
}
@Override
public void executeQuery(RequestScope request, Connection conn, String sql,
Object[] parameters, int skipResults, int maxResults,
RowHandlerCallback callback) throws SQLException {
if ((skipResults != NO_SKIPPED_RESULTS || maxResults != NO_MAXIMUM_RESULTS)
&& supportsLimit()) {
sql = dialect.getLimitString(sql, skipResults, maxResults);
if(logger.isDebugEnabled()){
logger.debug(sql);
}
skipResults = NO_SKIPPED_RESULTS;
maxResults = NO_MAXIMUM_RESULTS;
}
super.executeQuery(request, conn, sql, parameters, skipResults,
maxResults, callback);
}
public boolean supportsLimit() {
if (enableLimit && dialect != null) {
return dialect.supportsLimit();
}
return false;
}
}
其中:
skipResults = NO_SKIPPED_RESULTS;
maxResults = NO_MAXIMUM_RESULTS;
告诉handleResults不分页(我们组装的sql已经使查询结果是分页后的结果了),此处引入了类似hibenate中的数据库方言接口Dialect,其代码如下:
package com.aladdin.dao.dialect;
public interface Dialect {
public boolean supportsLimit();
public String getLimitString(String sql, boolean hasOffset);
public String getLimitString(String sql, int offset, int limit);
}
下面为Dialect接口的MySQL实现:
package com.aladdin.dao.dialect;
public class MySQLDialect implements Dialect {
protected static final String SQL_END_DELIMITER = ";";
public String getLimitString(String sql, boolean hasOffset) {
return new StringBuffer(sql.length() + 20).append(trim(sql)).append(
hasOffset ? " limit ?,?" : " limit ?")
.append(SQL_END_DELIMITER).toString();
}
public String getLimitString(String sql, int offset, int limit) {
sql = trim(sql);
StringBuffer sb = new StringBuffer(sql.length() + 20);
sb.append(sql);
if (offset > 0) {
sb.append(" limit ").append(offset).append(',').append(limit)
.append(SQL_END_DELIMITER);
} else {
sb.append(" limit ").append(limit).append(SQL_END_DELIMITER);
}
return sb.toString();
}
public boolean supportsLimit() {
return true;
}
private String trim(String sql) {
sql = sql.trim();
if (sql.endsWith(SQL_END_DELIMITER)) {
sql = sql.substring(0, sql.length() - 1
- SQL_END_DELIMITER.length());
}
return sql;
}
}
接下来的工作就是把LimitSqlExecutor注入ibatis中。我们是通过spring来使用ibatis的,所以在我们的dao基类中执行注入,代码如下:
package com.aladdin.dao.ibatis;
import java.io.Serializable;
import java.util.List;
import org.springframework.orm.ObjectRetrievalFailureException;
import org.springframework.orm.ibatis.support.SqlMapClientDaoSupport;
import com.aladdin.dao.ibatis.ext.LimitSqlExecutor;
import com.aladdin.domain.BaseObject;
import com.aladdin.util.ReflectUtil;
import com.ibatis.sqlmap.client.SqlMapClient;
import com.ibatis.sqlmap.engine.execution.SqlExecutor;
import com.ibatis.sqlmap.engine.impl.ExtendedSqlMapClient;
public abstract class BaseDaoiBatis extends SqlMapClientDaoSupport {
private SqlExecutor sqlExecutor;
public SqlExecutor getSqlExecutor() {
return sqlExecutor;
}
public void setSqlExecutor(SqlExecutor sqlExecutor) {
this.sqlExecutor = sqlExecutor;
}
public void setEnableLimit(boolean enableLimit) {
if (sqlExecutor instanceof LimitSqlExecutor) {
((LimitSqlExecutor) sqlExecutor).setEnableLimit(enableLimit);
}
}
public void initialize() throws Exception {
if (sqlExecutor != null) {
SqlMapClient sqlMapClient = getSqlMapClientTemplate()
.getSqlMapClient();
if (sqlMapClient instanceof ExtendedSqlMapClient) {
ReflectUtil.setFieldValue(((ExtendedSqlMapClient) sqlMapClient)
.getDelegate(), "sqlExecutor", SqlExecutor.class,
sqlExecutor);
}
}
}
...
}
其中的initialize方法执行注入,稍后会看到此方法在spring Beans 配置中指定为init-method。由于sqlExecutor是com.ibatis.sqlmap.engine.impl.ExtendedSqlMapClient的私有成员,且没有公开的set方法,所以此处通过反射绕过java的访问控制,下面是ReflectUtil的实现代码:
package com.aladdin.util;
import java.lang.reflect.Field;
import java.lang.reflect.Method;
import java.lang.reflect.Modifier;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
public class ReflectUtil {
private static final Log logger = LogFactory.getLog(ReflectUtil.class);
public static void setFieldValue(Object target, String fname, Class ftype,
Object fvalue) {
if (target == null
|| fname == null
|| "".equals(fname)
|| (fvalue != null && !ftype.isAssignableFrom(fvalue.getClass()))) {
return;
}
Class clazz = target.getClass();
try {
Method method = clazz.getDeclaredMethod("set"
+ Character.toUpperCase(fname.charAt(0))
+ fname.substring(1), ftype);
if (!Modifier.isPublic(method.getModifiers())) {
method.setAccessible(true);
}
method.invoke(target, fvalue);
} catch (Exception me) {
if (logger.isDebugEnabled()) {
logger.debug(me);
}
try {
Field field = clazz.getDeclaredField(fname);
if (!Modifier.isPublic(field.getModifiers())) {
field.setAccessible(true);
}
field.set(target, fvalue);
} catch (Exception fe) {
if (logger.isDebugEnabled()) {
logger.debug(fe);
}
}
}
}
}
到此剩下的就是通过Spring将sqlExecutor注入BaseDaoiBatis中了,下面是Spring Beans配置文件:
"http://www.springframework.org/dtd/spring-beans.dtd">
此后就可以通过调用org.springframework.orm.ibatis.SqlMapClientTemplate的
public List queryForList(final String statementName, final Object parameterObject, final int skipResults, final int maxResults) throws DataAccessException
或
public PaginatedList queryForPaginatedList(final String statementName, final Object parameterObject, final int pageSize) throws DataAccessException
得到分页结果了。建议使用第一个方法,第二个方法返回的是PaginatedList,虽然使用简单,但是其获得指定页的数据是跨过我们的dao直接访问ibatis的,不方便统一管理。