Java 小豆虫';结果同步集?
我最近发现,JDBC有两种方式来命名列,即“按名称”和“按标签”,而显然“按标签”方式是默认的 实际上,列名的概念似乎让我感到困惑。而且可能不仅对我来说,对Beanutils autors来说也是如此,因为默认情况下,它们按名称访问字段(导致无法使用列别名访问任何查询)。同时,它没有效果,因为它是在内省之后设置的 下面是示例代码Java 小豆虫';结果同步集?,java,jdbc,introspection,apache-commons-beanutils,bug-reporting,Java,Jdbc,Introspection,Apache Commons Beanutils,Bug Reporting,我最近发现,JDBC有两种方式来命名列,即“按名称”和“按标签”,而显然“按标签”方式是默认的 实际上,列名的概念似乎让我感到困惑。而且可能不仅对我来说,对Beanutils autors来说也是如此,因为默认情况下,它们按名称访问字段(导致无法使用列别名访问任何查询)。同时,它没有效果,因为它是在内省之后设置的 下面是示例代码 import org.apache.commons.beanutils.*; import java.lang.reflect.InvocationTargetExc
import org.apache.commons.beanutils.*;
import java.lang.reflect.InvocationTargetException;
import java.sql.*;
import java.util.ArrayList;
import java.util.Iterator;
public class ResultSetIteratorAttempt {
public static void main(String[] args) throws ClassNotFoundException, SQLException, InstantiationException, IllegalAccessException, InvocationTargetException, NoSuchMethodException {
Connection conn = null;
Statement stmt = null;
Class.forName("com.mysql.jdbc.Driver");
conn = DriverManager.getConnection("jdbc:mysql://localhost/sample","java","");
stmt = conn.createStatement();
ResultSet rs = stmt.executeQuery("SELECT Id as NM1, Name as NM2 FROM DayOfWeek;");
ArrayList results = new ArrayList(); // To hold copied list
ResultSetDynaClass rsdc = new ResultSetDynaClass(rs);
rsdc.setUseColumnLabel(true);
DynaProperty[] properties = rsdc.getDynaProperties();
String propertyName = "";
for(int i=0; i<properties.length; ++i) {
propertyName = properties[i].getName();
System.out.println(String.format("Property #%d is %s", i, propertyName));
}
Iterator rows = rsdc.iterator();
DynaBean row;
while (rows.hasNext()) {
row = (DynaBean) rows.next();
System.out.println(String.format("Row is %s", row.get(propertyName)));
}
}
}
臭虫是已知的
解决方法是使用替代构造函数签名,它接受三个参数
mysql> select * from dayofweek;
+----+-----------+
| Id | Name |
+----+-----------+
| 5 | Friday |
| 1 | Monday |
| 6 | Saturday |
| 7 | Sunday |
| 4 | Thursday |
| 2 | Tuesday |
| 3 | Wednesday |
+----+-----------+
7 rows in set (0.00 sec)