JDBC连接hive（附完整代码）
作者：互联网
一、创建maven工程
1、选择quickStart
2、导入依赖（如下）——依赖定时检查更新
<dependencies>
<dependency>
<groupId>org.apache.hive</groupId>
<artifactId>hive-jdbc</artifactId>
<version>${hive.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-auth</artifactId>
<version>${hadoop.version}</version>
<exclusions>
<exclusion>
<artifactId>jdk.tools</artifactId>
<groupId>jdk.tools</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>${hadoop.version}</version>
<exclusions>
<exclusion>
<artifactId>jdk.tools</artifactId>
<groupId>jdk.tools</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>${hadoop.version}</version>
<exclusions>
<exclusion>
<artifactId>jdk.tools</artifactId>
<groupId>jdk.tools</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>${hadoop.version}</version>
<exclusions>
<exclusion>
<artifactId>jdk.tools</artifactId>
<groupId>jdk.tools</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>${hadoop.version}</version>
</dependency>
</dependencies>
二、创建resource
1、HiveResource.properties
driver=org.apache.hive.jdbc.HiveDriver
url=jdbc:hive2://你的虚拟机ip地址:10000/hive的库名
username=root
password=密码
2、log4j.properties——可加可不加（日志）
log4j.rootLogger=INFO, stdout
log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=%d %p [%c] - %m%n
log4j.appender.logfile=org.apache.log4j.FileAppender
log4j.appender.logfile.File=target/hadoop.log
log4j.appender.logfile.layout=org.apache.log4j.PatternLayout
log4j.appender.logfile.layout.ConversionPattern=%d %p [%c] - %m%n
注意
这边的资源文件是虚拟机hive里
beeline -u jdbc:hive2://你的虚拟机ip地址:10000 -n root
//进入hive客户端，查看库和对应的表
或者打开网页：你的ip地址:9870
三、代码如下
BaseDao类
package cn.kgc.jdbc;
import java.io.FileReader;
import java.io.IOException;
import java.sql.*;
import java.util.Properties;
public class BaseDao {
private static final Properties properties = new Properties();
private static final String PATH="config/HiveResource.properties";
static {
try {
properties.load(new FileReader(PATH));
Class.forName(properties.getProperty("driver"));
} catch (IOException | ClassNotFoundException e) {
e.printStackTrace();
System.exit(-1);
}
}
private static Connection con() throws SQLException {
return DriverManager.getConnection(
properties.getProperty("url"),
properties.getProperty("username"),
properties.getProperty("password")
);
}
private static PreparedStatement pst(Connection con,String sql,Object...objs) throws SQLException {
PreparedStatement pst = con.prepareStatement(sql);
if (null != objs && objs.length>0){
for (int i = 0; i < objs.length; i++) {
pst.setObject(i+1,objs[i]);
}
}
return pst;
}
private static void close(AutoCloseable...closes){
for (AutoCloseable close : closes) {
if (null != close){
try {
close.close();
} catch (Exception e) {
e.printStackTrace();
}
}
}
}
//执行增删改操作
public static int exeUpdate(String sql ,Object...objs){
Connection con = null;
PreparedStatement pst = null;
try {
con = con();
pst = pst(con,sql,objs);
return pst.executeUpdate();
} catch (SQLException e) {
e.printStackTrace();
}finally {
close(pst,con);
}
return -1;
}
//执行批量插入
public static int addBatch(String sql,int cloSize,int batchSize,Object...objs){
Connection con= null;
PreparedStatement pst = null;
int affactedRows=0;
try {
con = con();
pst = con.prepareStatement(sql);
for (int i = 0,realSize = 0; i < objs.length; i+=cloSize) {
for (int j = i,size=0; size <cloSize ;size++, j++) {
pst.setObject(size+1,objs[j]);
}
pst.addBatch();
if (++realSize%batchSize==0){
affactedRows = pst.executeBatch().length;
pst.clearBatch();
}
affactedRows = pst.executeBatch().length;
pst.clearBatch();
}
} catch (Exception e) {
e.printStackTrace();
}finally {
close(pst,con);
}
return -1;
}
//查询输出
public static void exeQuery(String sql){
Connection con = null;
PreparedStatement pst = null;
ResultSet rst = null;
try {
con = con();
pst = con.prepareStatement(sql);
rst = pst.executeQuery();
int colSize = rst.getMetaData().getColumnCount();
while (rst.next()){
for (int i = 1; i <= colSize ; i++) {
System.out.print(rst.getObject(i).toString());
System.out.print("\t");
}
System.out.println();
}
} catch (Exception e) {
e.printStackTrace();
}finally {
close(rst,pst,con);
}
}
}
2、Test类（和jdbc连接mysql一样）
package cn.kgc;
import cn.kgc.jdbc.BaseDao;
public class Test {
public static void main(String[] args){
BaseDao baseDao= new BaseDao();
//查询
/*String sql = "select * from sqp_testsqoop_par";
BaseDao.exeQuery(sql);*/
//单条数据导入
/*String sql = "insert into studentinfo(stuId,stuName,stuAge,StuGender,fkClassId) values(?,?,?,?,?)";
BaseDao.exeUpdate(sql,30,"戴敏","23","男",1);*/
//批量导入
/*String sql = "insert into studentinfo(stuId,stuName,stuAge,StuGender,fkClassId) values(?,?,?,?,?)";
Object[] arr = {12,"戴敏","24","男",1,13,"张","25","男",1}
BaseDao.addBatch(sql,5,2,arr);*/
//删除
/*String sql = "delete from studentinfo where stuId like ?";
BaseDao.exeUpdate(sql,30);*/
//修改
String sql = "update studentinfo set stuName= ?,StuGender = ? where stuId = 31";
BaseDao.exeUpdate(sql,"戴敏","男");
}
}
标签：JDBC,代码,hadoop,hive,sql,apache,log4j,pst,con 来源： https://blog.csdn.net/daimin1/article/details/119062550