部署开启了Kerberos身份验证的大数据平台集群外客户端

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本文档主要用于说明,如何在集群外节点上,部署大数据平台的客户端,此大数据平台已经开启了Kerberos身份验证。通过客户端用户在集群外就可以使用集群内的服务了,如查询集群内的hdfs数据,提交spark任务到集群内执行等操作。
具体部署步骤如下所示:

1、拷贝集群内hadoop相关组件包到客户端

本地创建目录/opt/cloudera/parcels

mkdir –R /opt/cloudera/parcels

拷贝组件包CDH-5.7.2-1.cdh5.7.2.p0.18到目录/opt/cloudera/parcels
进入目录建立软连接

cd /opt/cloudrea/parcels
ln –s CDH-5.7.2-1.cdh5.7.2.p0.18 CDH

2、拷贝集群内hadoop相关配置文件到客户端

创建目录/etc/hadoop,将/etc/hadoop/conf文件夹放入该目录,node1为集群内节点

mkdir /etc/hadoop
scp -r node1:/etc/hadoop/conf /etc/hadoop

创建目录/etc/hive,将/etc/hive/conf文件夹放入该目录

mkdir /etc/hive
scp -r node1:/etc/hive/conf /etc/hive

创建目录/etc/spark,将/etc/spark/conf文件夹放入该目录

mkdir /etc/spark
scp -r node1:/etc/spark/conf /etc/spark

3、拷贝集群内身份验证相关配置文件krb5.conf到客户端

scp node1:/etc/krb5.conf  /etc

4、运行客户端脚本client.sh,文件内容如下:

export HADOOP_HOME=/opt/cloudera/parcels/CDH/lib/hadoop
export HADOOP_CONF=/etc/hadoop/conf
export HADOOP_CONF_DIR=/etc/hadoop/conf
export YARN_CONF_DIR=/etc/hadoop/conf
export SPARK_CONF_DIR=/etc/spark/conf
#export SPARK_HOME=/opt/cloudera/parcels/CDH/lib/spark
CDH_HOME="/opt/cloudera/parcels/CDH"
export PATH=$CDH_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin/:$PATH
##beeline 连接hive进行sql查询
cd /opt/cloudera/parcels/CDH/bin
./beeline -u "jdbc:hive2://node7:10000/;principal=hive/[email protected]" --config /etc/hive/conf
##执行hdfs命令
#./hdfs --config /etc/hadoop/conf dfs -ls /
##提交spark命令
#cd /opt/cloudera/parcels/CDH/lib/spark/bin
#./spark-shell

注意:
1、客户端要与集群时间同步,否则身份认证会失败;
2、客户端host要添加集群hosts,集群hosts可连接集群某一点获取;
3、集群已开启kerberos身份验证,执行shell命令前,需要kinit进行身份验证,示例如下:

#kinit认证命令
[root@node5 client]# kinit -kt /home/user01.keytab user01
#查看当前用户
[root@node5 client]# klist
Ticket cache: FILE:/tmp/krb5cc_0
Default principal: [email protected]

Valid starting       Expires              Service principal
12/01/2016 20:48:50  12/02/2016 20:48:50  krbtgt/[email protected]
    renew until 12/08/2016 20:48:50

4、spark jdbc编程,同样需要调用kerberos身份验证,示例如下,完整工程看【spark jdbc 示例】目录下Security

package kerberos.spark;


import org.apache.hadoop.security.UserGroupInformation;

import java.io.IOException;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;
import java.util.Timer;
import java.util.TimerTask;

/*
 * 开启权限验证时,可以传入用户principal 和 keytab 进行身份验证
 */
public class sparkjdbc {
   public static void main(String args[]) {
      final String principal = args[0];//用户对应principal,如user01
      final String keytab = args[1];//用户对应keytab,如/home/user01/user01.keytab
      String sql = args[2];//业务sql操作语句
      try {
         //1、身份验证:间隔12小时验证一次
         long interval=1;
         long now = System.currentTimeMillis();
         long start = interval - now % interval;
         Timer timer = new Timer();
         timer.schedule(new TimerTask(){
            public void run() {
               org.apache.hadoop.conf.Configuration conf = new org.apache.hadoop.conf.Configuration();
               conf.set("hadoop.security.authentication", "Kerberos");
               UserGroupInformation.setConfiguration(conf);
               try {
                  UserGroupInformation.loginUserFromKeytab(principal,keytab);
                  System.out.println("getting connection");
                  System.out.println("current user: "+UserGroupInformation.getCurrentUser());
                  System.out.println("login user: "+UserGroupInformation.getLoginUser());
               } catch (IOException e) {
                  e.printStackTrace();
               }
               System.out.println("execute task!"+ this.scheduledExecutionTime());
            }
         },start,12*60*60*1000);//定时任务

         //正常业务,spark jdbc连接hive进行sql操作
         Class.forName("org.apache.hive.jdbc.HiveDriver");
         Connection con = DriverManager
               .getConnection("jdbc:hive2://node7:10000/;principal=hive/[email protected]");
         System.out.println("got connection");
         Statement stmt = con.createStatement();
         ResultSet rs = stmt.executeQuery(sql);// executeQuery会返回结果的集合,否则返回空值
            System.out.println("打印输出结果:");
            while (rs.next()) {
                System.out.println(rs.getString(1));// 入如果返回的是int类型可以用getInt()
            }
         
         con.close();
      } catch (Exception e) {
         e.printStackTrace();
      }
   }
}

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