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://node128a7:10000/;principal=hive/node128a7@HADOOP.COM" --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@node128a225 client]# kinit -kt /home/user01.keytab user01
#查看当前用户
[root@node128a225 client]# klist
Ticket cache: FILE:/tmp/krb5cc_0
Default principal: user01@HADOOP.COM
Valid starting Expires Service principal
12/01/2016 20:48:50 12/02/2016 20:48:50 krbtgt/HADOOP.COM@HADOOP.COM
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://node128a7:10000/;principal=hive/node128a7@HADOOP.COM");
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();
}
}
}
