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0628-6.2-如何在CDH6.2中启用Kerberos

Fayson

发布于 2019-05-16 03:20:20

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代码可运行

文章被收录于专栏：Hadoop实操Hadoop实操

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代码可运行

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Fayson的github： https://github.com/fayson/cdhproject
提示：代码块部分可以左右滑动查看噢

文档编写目的

在前面的文章中，Fayson介绍了《0610-6.2.0-如何在Redhat7.4安装CDH6.2》，这里我们基于这个环境开始安装Kerberos。Kerberos是一个用于安全认证第三方协议，并不是Hadoop专用，你也可以将其用于其他系统，它采用了传统的共享密钥的方式，实现了在网络环境不一定保证安全的环境下，client和server之间的通信，适用于client/server模型，由MIT开发和实现。而使用Cloudera Manager可以较为轻松的实现界面化的Kerberos集成，本文Fayson主要介绍如何在Redhat7.4的CDH6.2环境中启用Kerberos。

内容概述：

1.如何安装及配置KDC服务

2.如何通过CDH启用Kerberos

3.如何登录Kerberos并访问Hadoop相关服务

4.总结

测试环境：

1.操作系统：Redhat7.4

2.CDH6.2

3.采用root用户进行操作

KDC服务安装及配置

本文档中将KDC服务安装在Cloudera Manager Server所在服务器上（KDC服务可根据自己需要安装在其他服务器）

1.在Cloudera Manager服务器上安装KDC服务

[root@ip-172-31-6-83 ~]# yum -y install krb5-server krb5-libs krb5-auth-dialog krb5-workstation

2.修改/etc/krb5.conf配置

[root@ip-172-31-6-83 ~]# vim /etc/krb5.conf
# Configuration snippets may be placed in this directory as well
includedir /etc/krb5.conf.d/

[logging]
 default = FILE:/var/log/krb5libs.log
 kdc = FILE:/var/log/krb5kdc.log
 admin_server = FILE:/var/log/kadmind.log

[libdefaults]
 dns_lookup_realm = false
 ticket_lifetime = 24h
 renew_lifetime = 7d
 forwardable = true
 rdns = false
 default_realm = FAYSON.COM
 #default_ccache_name = KEYRING:persistent:%{uid}

[realms]
 FAYSON.COM = {
  kdc = ip-172-31-6-83.ap-southeast-1.compute.internal
  admin_server = ip-172-31-6-83.ap-southeast-1.compute.internal
 }

[domain_realm]
 .ap-southeast-1.compute.internal = FAYSON.COM
 ap-southeast-1.compute.internal = FAYSON.COM

标红部分为需要修改的信息。

3.修改/var/kerberos/krb5kdc/kadm5.acl配置

[root@ip-172-31-6-83 ~]# vim /var/kerberos/krb5kdc/kadm5.acl
*/admin@FAYSON.COM      *

4.修改/var/kerberos/krb5kdc/kdc.conf配置

[root@ip-172-31-6-83 ~]# vim /var/kerberos/krb5kdc/kdc.conf
[root@ip-172-31-6-83 ~]# cat /var/kerberos/krb5kdc/kdc.conf
[kdcdefaults]
 kdc_ports = 88
 kdc_tcp_ports = 88

[realms]
 FAYSON.COM = {
  #master_key_type = aes256-cts
  max_renewable_life= 7d 0h 0m 0s
  acl_file = /var/kerberos/krb5kdc/kadm5.acl
  dict_file = /usr/share/dict/words
  admin_keytab = /var/kerberos/krb5kdc/kadm5.keytab
  supported_enctypes = aes256-cts:normal aes128-cts:normal des3-hmac-sha1:normal arcfour-hmac:normal camellia256-cts:normal camellia128-cts:normal des-hmac-sha1:normal des-cbc-md5:normal des-cbc-crc:normal
 }

标红部分为需要修改的配置。

5.创建Kerberos数据库

[root@ip-172-31-6-83 ~]# kdb5_util create –r FAYSON.COM -s
Loading random data
Initializing database '/var/kerberos/krb5kdc/principal' for realm 'FAYSON.COM',
master key name 'K/M@FAYSON.COM'
You will be prompted for the database Master Password.
It is important that you NOT FORGET this password.
Enter KDC database master key: 
Re-enter KDC database master key to verify:

此处需要输入Kerberos数据库的密码。

6.创建Kerberos的管理账号

[root@ip-172-31-6-83 ~]# kadmin.local
Authenticating as principal root/admin@FAYSON.COM with password.
kadmin.local:  addprinc admin/admin@FAYSON.COM
WARNING: no policy specified for admin/admin@FAYSON.COM; defaulting to no policy
Enter password for principal "admin/admin@FAYSON.COM": 
Re-enter password for principal "admin/admin@FAYSON.COM": 
Principal "admin/admin@FAYSON.COM" created.
kadmin.local:  exit

标红部分为Kerberos管理员账号，需要输入管理员密码。

7.将Kerberos服务添加到自启动服务，并启动krb5kdc和kadmin服务

[root@ip-172-31-6-83 ~]# systemctl enable krb5kdc
Created symlink from /etc/systemd/system/multi-user.target.wants/krb5kdc.service to /usr/lib/systemd/system/krb5kdc.service.
[root@ip-172-31-6-83 ~]# systemctl enable kadmin
Created symlink from /etc/systemd/system/multi-user.target.wants/kadmin.service to /usr/lib/systemd/system/kadmin.service.
[root@ip-172-31-6-83 ~]# systemctl start krb5kdc
[root@ip-172-31-6-83 ~]# systemctl start kadmin

8.测试Kerberos的管理员账号

[root@ip-172-31-6-83 ~]# kinit admin/admin@FAYSON.COM
Password for admin/admin@FAYSON.COM: 
[root@ip-172-31-6-83 ~]# klist
Ticket cache: FILE:/tmp/krb5cc_0
Default principal: admin/admin@FAYSON.COM

Valid starting       Expires              Service principal
05/11/2019 11:26:56  05/12/2019 11:26:56  krbtgt/FAYSON.COM@FAYSON.COM
        renew until 05/18/2019 11:26:56
[root@ip-172-31-6-83 ~]#

9.为集群安装所有Kerberos客户端，包括Cloudera Manager

使用批处理脚本为集群所有节点安装Kerberos客户端

[root@ip-172-31-6-83 shell]# sh ssh_do_all.sh node.list 'yum -y install krb5-libs krb5-workstation'

10.在Cloudera Manager Server服务器上安装额外的包

[root@ip-172-31-6-83 shell]# yum -y install openldap-clients

11.将KDC Server上的krb5.conf文件拷贝到所有Kerberos客户端

使用批处理脚本将Kerberos服务端的krb5.conf配置文件拷贝至集群所有节点的/etc目录下：

[root@ip-172-31-6-83 shell]# sh bk_cp.sh node.list /etc/krb5.conf /etc/

CDH集群启用Kerberos

1.在KDC中给Cloudera Manager添加管理员账号

[root@ip-172-31-6-83 shell]# kadmin.local
Authenticating as principal admin/admin@FAYSON.COM with password.
kadmin.local:   addprinc cloudera-scm/admin@FAYSON.COM
WARNING: no policy specified for cloudera-scm/admin@FAYSON.COM; defaulting to no policy
Enter password for principal "cloudera-scm/admin@FAYSON.COM": 
Re-enter password for principal "cloudera-scm/admin@FAYSON.COM": 
Principal "cloudera-scm/admin@FAYSON.COM" created.
kadmin.local:  exit

2.进入Cloudera Manager的“管理”->“安全”界面

3.选择“启用Kerberos”，进入如下界面

4.确保如下列出的所有检查项都已完成，然后全部点击勾选

5.点击“继续”，配置相关的KDC信息，包括类型、KDC服务器、KDC Realm、加密类型以及待创建的Service Principal（hdfs，yarn,，hbase，hive等）的更新生命期等

6.不建议让Cloudera Manager来管理krb5.conf, 点击“继续”

7.输入Cloudera Manager的Kerbers管理员账号，一定得和之前创建的账号一致，点击“继续”

8.点击“继续”启用Kerberos

9.Kerberos启用完成，点击“继续”

10.集群重启完成，点击“继续”

11.点击“继续”

点击“完成”，至此已成功启用Kerberos。

12.回到主页，一切正常，再次查看“管理”->“安全”，界面显示“已成功启用 Kerberos。”

Kerberos使用

使用fayson用户运行MapReduce任务及操作Hive，需要在集群所有节点创建fayson用户。

1.使用kadmin创建一个fayson的principal

[root@ip-172-31-6-83 shell]# kadmin.local
Authenticating as principal admin/admin@FAYSON.COM with password.
kadmin.local:  addprinc fayson@FAYSON.COM
WARNING: no policy specified for fayson@FAYSON.COM; defaulting to no policy
Enter password for principal "fayson@FAYSON.COM": 
Re-enter password for principal "fayson@FAYSON.COM": 
Principal "fayson@FAYSON.COM" created.
kadmin.local:  exit
You have new mail in /var/spool/mail/root

2.使用fayson用户登录Kerberos

[root@ip-172-31-6-83 ~]# kdestroy
[root@ip-172-31-6-83 ~]# kinit fayson
Password for fayson@FAYSON.COM: 
[root@ip-172-31-6-83 ~]# klist
Ticket cache: FILE:/tmp/krb5cc_0
Default principal: fayson@FAYSON.COM

Valid starting       Expires              Service principal
05/11/2019 11:38:33  05/12/2019 11:38:33  krbtgt/FAYSON.COM@FAYSON.COM
        renew until 05/18/2019 11:38:33
[root@ip-172-31-6-83 ~]#

3.在集群所有节点添加fayson用户

使用批量脚本在所有节点添加fayson用户

[root@ip-172-31-6-83 shell]#  sh ssh_do_all.sh node.list "useradd fayson"

4.运行MapReduce作业

[root@ip-172-31-6-83 hadoop-mapreduce]# hadoop jar /opt/cloudera/parcels/CDH/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar pi 10 1

5.使用beeline连接hive进行测试

[root@ip-172-31-6-83 ~]# beeline
WARNING: Use "yarn jar" to launch YARN applications.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/cloudera/parcels/CDH-6.2.0-1.cdh6.2.0.p0.967373/jars/log4j-slf4j-impl-2.8.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/cloudera/parcels/CDH-6.2.0-1.cdh6.2.0.p0.967373/jars/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Beeline version 2.1.1-cdh6.2.0 by Apache Hive
beeline> !connect jdbc:hive2://localhost:10000/;principal=hive/ip-172-31-6-83.ap-southeast-1.compute.internal@FAYSON.COM
Connecting to jdbc:hive2://localhost:10000/;principal=hive/ip-172-31-6-83.ap-southeast-1.compute.internal@FAYSON.COM
Connected to: Apache Hive (version 2.1.1-cdh6.2.0)
Driver: Hive JDBC (version 2.1.1-cdh6.2.0)
Transaction isolation: TRANSACTION_REPEATABLE_READ
0: jdbc:hive2://localhost:10000/>  show tables;
INFO  : Compiling command(queryId=hive_20190511114259_ac6763ca-f417-428f-80eb-d4fb115b273f): show tables
INFO  : Semantic Analysis Completed
INFO  : Returning Hive schema: Schema(fieldSchemas:[FieldSchema(name:tab_name, type:string, comment:from deserializer)], properties:null)
INFO  : Completed compiling command(queryId=hive_20190511114259_ac6763ca-f417-428f-80eb-d4fb115b273f); Time taken: 2.735 seconds
INFO  : Executing command(queryId=hive_20190511114259_ac6763ca-f417-428f-80eb-d4fb115b273f): show tables
INFO  : Starting task [Stage-0:DDL] in serial mode
INFO  : Completed executing command(queryId=hive_20190511114259_ac6763ca-f417-428f-80eb-d4fb115b273f); Time taken: 0.434 seconds
INFO  : OK
+-----------+
| tab_name  |
+-----------+
| test      |
+-----------+
1 row selected (3.786 seconds)
0: jdbc:hive2://localhost:10000/> create table t1 (s1 string,s2 string);
INFO  : Compiling command(queryId=hive_20190511114317_a05a8585-daf3-4692-9289-9eab0af336c4): create table t1 (s1 string,s2 string)
INFO  : Semantic Analysis Completed
INFO  : Returning Hive schema: Schema(fieldSchemas:null, properties:null)
INFO  : Completed compiling command(queryId=hive_20190511114317_a05a8585-daf3-4692-9289-9eab0af336c4); Time taken: 0.078 seconds
INFO  : Executing command(queryId=hive_20190511114317_a05a8585-daf3-4692-9289-9eab0af336c4): create table t1 (s1 string,s2 string)
INFO  : Starting task [Stage-0:DDL] in serial mode
INFO  : Completed executing command(queryId=hive_20190511114317_a05a8585-daf3-4692-9289-9eab0af336c4); Time taken: 0.157 seconds
INFO  : OK
No rows affected (0.269 seconds)
0: jdbc:hive2://localhost:10000/>

向test表中插入数据

0: jdbc:hive2://localhost:10000/> insert into t1 values('1','2');
0: jdbc:hive2://localhost:10000/> select * from t1;

执行一个Count语句

0: jdbc:hive2://localhost:10000/> select count(*) from t1;

常见问题

1.使用Kerberos用户身份运行MapReduce作业报错

main : run as user is fayson
main : requested yarn user is fayson
Requested user fayson is not whitelisted and has id 501,which is below the minimum allowed 1000

Failing this attempt. Failing the application.
17/09/02 20:05:04 INFO mapreduce.Job: Counters: 0
Job Finished in 6.184 seconds
java.io.FileNotFoundException: File does not exist: hdfs://ip-172-31-6-148:8020/user/fayson/QuasiMonteCarlo_1504382696029_1308422444/out/reduce-out
        at org.apache.hadoop.hdfs.DistributedFileSystem$20.doCall(DistributedFileSystem.java:1266)
        at org.apache.hadoop.hdfs.DistributedFileSystem$20.doCall(DistributedFileSystem.java:1258)
        at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
        at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1258)
        at org.apache.hadoop.io.SequenceFile$Reader.<init>(SequenceFile.java:1820)
        at org.apache.hadoop.io.SequenceFile$Reader.<init>(SequenceFile.java:1844)
        at org.apache.hadoop.examples.QuasiMonteCarlo.estimatePi(QuasiMonteCarlo.java:314)
        at org.apache.hadoop.examples.QuasiMonteCarlo.run(QuasiMonteCarlo.java:354)
        at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
        at org.apache.hadoop.examples.QuasiMonteCarlo.main(QuasiMonteCarlo.java:363)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:606)
        at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:71)
        at org.apache.hadoop.util.ProgramDriver.run(ProgramDriver.java:144)
        at org.apache.hadoop.examples.ExampleDriver.main(ExampleDriver.java:74)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:606)
        at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
        at org.apache.hadoop.util.RunJar.main(RunJar.java:136)