Hive记录-配置远程连接（JAVA/beeline）

1.修改配置hive-site.xml    hadoop core-site.xml限制---参考Hive记录-部署Hive环境

2.启动hadoop 

 #sh /usr/app/hadoop/sbin/start-all.sh

3.jps查看五大进程是否齐全：NameNode  DataNode NodeManager ResourceManager SecondaryNameNode
4.启动hiveserver2服务

#hive --service hiveserver2
#netstat -ant | grep 10000   #监听

5.beeline连接

#beeline
#beeline>!connect jdbc:hive2://192.168.66.66:10000
#输入用户名和密码       ###登录系统的用户名root也行，但是要有操作hadoop hive文件夹的权限
#连接成功就可以操作hive数据了

6.Java远程连接

6.1 所需包（hive-xxx.jar要与服务器上的hive版本一致）

6.2 src下新建log4j.properties

-------------------------------------------------------
inceptor.root.logger=INFO,RFA
inceptor.log.dir=/usr/app/hive/logs
inceptor.log.file=spark.log

# Define the root logger to the system property "hadoop.root.logger".
log4j.rootLogger=${inceptor.root.logger}

# Set everything to be logged to the console
log4j.appender.console=org.apache.log4j.ConsoleAppender
log4j.appender.console.target=System.err
log4j.appender.console.layout=org.apache.log4j.PatternLayout
log4j.appender.console.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c: %m%n

# output to file
log4j.appender.RFA=org.apache.log4j.RollingFileAppender
log4j.appender.RFA.File=${inceptor.log.dir}/${inceptor.log.file}
# The MaxFileSize can be 512KB
log4j.appender.RFA.MaxFileSize=10MB
# Keep three backup files.
log4j.appender.RFA.MaxBackupIndex=1024
# Pattern to output: date priority [category] - message
log4j.appender.RFA.layout=org.apache.log4j.PatternLayout
log4j.appender.RFA.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss} %p %c: %m%n

# Ignore messages below warning level from Jetty, because it's a bit verbose
log4j.logger.org.eclipse.jetty=WARN

6.3  ToHive.java

package hive;

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;

public class ToHive {
	private static String driverName = "org.apache.hive.jdbc.HiveDriver";
	public boolean run() {

		try {
			Class.forName(driverName);
			Connection con = null;
			//端口号默认为10000，根据实际情况修改；
			//用户名：root，密码：1(登录linux系统)
			con = DriverManager.getConnection(
					"jdbc:hive2://192.168.66.66:10000/siat", "root", "1");
			Statement stmt = con.createStatement();
			ResultSet res = null;
			String sql = "select count(*) from test";
			System.out.println("Running: " + sql);
			res = stmt.executeQuery(sql);
			System.out.println("ok");
			while (res.next()) {
				System.out.println(res.getString(1));
			}
			return true;
		} catch (Exception e) {
			e.printStackTrace();
			System.out.println("error");
			return false;
		}
	}
	public static void main(String[] args) throws SQLException {
		ToHive hiveJdbcClient = new ToHive();
		hiveJdbcClient.run();
	}

}

6.4 右键执行-提交任务给hadoop进行计算返回结果

转载于:https://www.cnblogs.com/xinfang520/p/7684613.html