Cloudera Certified Associate Administrator案例之Test篇

　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　作者：尹正杰

版权声明：原创作品，谢绝转载！否则将追究法律责任。

一.准备工作（将CM升级到"60天使用的企业版"）

1>.在CM界面中点击"试用Cloudera Enterprise 60天"

2>.进入许可证界面可以看到当前使用的是"Cloudera Express"，点击"试用Cloudera Enterprise 60天""

3>.点击确认

4>.进入升级向导，点击"继续"

5>.升级完成

6>.查看CM主界面

二.使用企业级的CM的快照功能

1>.点击HDFS中的"文件浏览器"

2>.进入我们的测试目录

3>.点击启用快照

4>.弹出一个确认对话框，点击"启用快照"

5>.快照启用成功

6>.点击拍摄快照

7>.给快照起一个名字

8>.等待快照创建完毕

9>.快照创建成功

19>.彻底删除做了快照的文件

[root@node101.yinzhengjie.org.cn ~]# hdfs dfs -ls  /yinzhengjie/debug/hdfs/log

Found  items

-rw-r--r--    root supergroup       -- : /yinzhengjie/debug/hdfs/log/timestamp_1560583829

[root@node101.yinzhengjie.org.cn ~]#

[root@node101.yinzhengjie.org.cn ~]#

[root@node101.yinzhengjie.org.cn ~]# hdfs dfs -rm -skipTrash /yinzhengjie/debug/hdfs/log/timestamp_1560583829

Deleted /yinzhengjie/debug/hdfs/log/timestamp_1560583829

[root@node101.yinzhengjie.org.cn ~]#

[root@node101.yinzhengjie.org.cn ~]# hdfs dfs -ls  /yinzhengjie/debug/hdfs/log

[root@node101.yinzhengjie.org.cn ~]#

[root@node101.yinzhengjie.org.cn ~]# hdfs dfs -rm -skipTrash /yinzhengjie/debug/hdfs/log/timestamp_1560583829　　　　#会跳过回收站

三.使用最近一个快照恢复数据

问题描述：

　　公司某用户在HDFS上存放了重要的文件，但是不小心将其删除了。幸运的是，该目录被设置为可快照的，并曾经创建过一次快照。请使用最近的一个快照回复数据。
　　要求恢复"/yinzhengjie/debug/hdfs/log"目录下的所有文件，并恢复文件原有的权限，所有者，ACL等。

解决方案：
　　快照在操作中日常运维中也是很有用的，不单是用于测试。我之前在博客中有介绍过Hadoop2.9.2版本是如何使用命令行的管理快照的方法，本次我们使用CM来操作。

1>.点击HDFS服务

2>.点击文件浏览器

3>.进入我们要还原数据的目录，并点击"从快照还原目录"

4>.选择快照及恢复的方法 

5>.恢复完成，点击"关闭"

6>.刷新当前页面，发现数据恢复成功啦

7>.恢复文件权限

四.运行一个mapreduce进程

问题描述：

　　公司一个运维人员尝试优化集群，但反而使得一些以前可以运行的MapReduce作业不能运行了。请你识别问题并予以纠正，并成功运行性能测试，要求为在Linux文件系统上找到hadoop-mapreduce-examples.jar包，并使用它完成三步测试：

　　　　>.使用teragen 　/user/yinzhengjie/data/day001/test_input 生成10000000行测试记录并输出到指定目录 　　　　

　　　　>.使用terasort /user/yinzhengjie/data/day001/test_input  /user/yinzhengjie/data/day001/test_output 进行排序并输出到指定目录 　　　　

　　　　>.使用teravalidate /user/yinzhengjie/data/day001/test_output  /user/yinzhengjie/data/day001/ts_validate检查输出结果 

解决方案： 　　

　　 需要对MapReduce作业的常见错误会排查。按照上述操作执行即可，遇到问题自行处理。

1>.生成输入数据

[root@node101.yinzhengjie.org.cn ~]# find / -name hadoop-mapreduce-examples.jar

/opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar

[root@node101.yinzhengjie.org.cn ~]#

[root@node101.yinzhengjie.org.cn ~]# cd /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]#

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar teragen   /user/yinzhengjie/data/day001/test_input
[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar teragen   /user/yinzhengjie/data/day001/test_input

// :: INFO terasort.TeraGen: Generating  using

// :: INFO mapreduce.JobSubmitter: number of splits:

// :: INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1558520562958_0001

// :: INFO impl.YarnClientImpl: Submitted application application_1558520562958_0001

// :: INFO mapreduce.Job: The url to track the job: http://node101.yinzhengjie.org.cn:8088/proxy/application_1558520562958_0001/

// :: INFO mapreduce.Job: Running job: job_1558520562958_0001

// :: INFO mapreduce.Job: Job job_1558520562958_0001 running in uber mode : false

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job: Job job_1558520562958_0001 completed successfully

// :: INFO mapreduce.Job: Counters:

        File System Counters

                FILE: Number of bytes read=

                FILE: Number of bytes written=

                FILE: Number of read operations=

                FILE: Number of large read operations=

                FILE: Number of write operations=

                HDFS: Number of bytes read=

                HDFS: Number of bytes written=

                HDFS: Number of read operations=

                HDFS: Number of large read operations=

                HDFS: Number of write operations=

        Job Counters

                Launched map tasks=

                Other local map tasks=

                Total time spent by all maps in occupied slots (ms)=

                Total time spent by all reduces in occupied slots (ms)=

                Total time spent by all map tasks (ms)=

                Total vcore-milliseconds taken by all map tasks=

                Total megabyte-milliseconds taken by all map tasks=

        Map-Reduce Framework

                Map input records=

                Map output records=

                Input split bytes=

                Spilled Records=

                Failed Shuffles=

                Merged Map outputs=

                GC time elapsed (ms)=

                CPU time spent (ms)=

                Physical memory (bytes) snapshot=

                Virtual memory (bytes) snapshot=

                Total committed heap usage (bytes)=

        org.apache.hadoop.examples.terasort.TeraGen$Counters

                CHECKSUM=

        File Input Format Counters

                Bytes Read=

        File Output Format Counters

                Bytes Written=

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]#

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.1-1.cdh5.15.1.p0.4/lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar teragen 10000000 /user/yinzhengjie/data/day001/test_input

2>.排序和输出

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]# pwd

/opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]#

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar terasort /user/yinzhengjie/data/day001/test_input /user/yinzhengjie/data/day001/test_output

// :: INFO terasort.TeraSort: starting

// :: INFO input.FileInputFormat: Total input paths to process :

Spent 151ms computing base-splits.

Spent 3ms computing TeraScheduler splits.

Computing input splits took 155ms

Sampling  splits of

Making  from  sampled records

Computing parititions took 1019ms

Spent 1178ms computing partitions.

// :: INFO mapreduce.JobSubmitter: number of splits:

// :: INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1558520562958_0002

// :: INFO impl.YarnClientImpl: Submitted application application_1558520562958_0002

// :: INFO mapreduce.Job: The url to track the job: http://node101.yinzhengjie.org.cn:8088/proxy/application_1558520562958_0002/

// :: INFO mapreduce.Job: Running job: job_1558520562958_0002

// :: INFO mapreduce.Job: Job job_1558520562958_0002 running in uber mode : false

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job: Job job_1558520562958_0002 completed successfully

// :: INFO mapreduce.Job: Counters:

        File System Counters

                FILE: Number of bytes read=

                FILE: Number of bytes written=

                FILE: Number of read operations=

                FILE: Number of large read operations=

                FILE: Number of write operations=

                HDFS: Number of bytes read=

                HDFS: Number of bytes written=

                HDFS: Number of read operations=

                HDFS: Number of large read operations=

                HDFS: Number of write operations=

        Job Counters

                Launched map tasks=

                Launched reduce tasks=

                Data-local map tasks=

                Rack-local map tasks=

                Total time spent by all maps in occupied slots (ms)=

                Total time spent by all reduces in occupied slots (ms)=

                Total time spent by all map tasks (ms)=

                Total time spent by all reduce tasks (ms)=

                Total vcore-milliseconds taken by all map tasks=

                Total vcore-milliseconds taken by all reduce tasks=

                Total megabyte-milliseconds taken by all map tasks=

                Total megabyte-milliseconds taken by all reduce tasks=

        Map-Reduce Framework

                Map input records=

                Map output records=

                Map output bytes=

                Map output materialized bytes=

                Input split bytes=

                Combine input records=

                Combine output records=

                Reduce input groups=

                Reduce shuffle bytes=

                Reduce input records=

                Reduce output records=

                Spilled Records=

                Shuffled Maps =

                Failed Shuffles=

                Merged Map outputs=

                GC time elapsed (ms)=

                CPU time spent (ms)=

                Physical memory (bytes) snapshot=

                Virtual memory (bytes) snapshot=

                Total committed heap usage (bytes)=

        Shuffle Errors

                BAD_ID=

                CONNECTION=

                IO_ERROR=

                WRONG_LENGTH=

                WRONG_MAP=

                WRONG_REDUCE=

        File Input Format Counters

                Bytes Read=

        File Output Format Counters

                Bytes Written=

// :: INFO terasort.TeraSort: done

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]#

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.1-1.cdh5.15.1.p0.4/lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar terasort /user/yinzhengjie/data/day001/test_input /user/yinzhengjie/data/day001/test_output

[root@node102.yinzhengjie.org.cn ~]# hdfs dfs -ls  /user/yinzhengjie/data/day001

Found  items

drwxr-xr-x   - root supergroup           -- : /user/yinzhengjie/data/day001/test_input

drwxr-xr-x   - root supergroup           -- : /user/yinzhengjie/data/day001/test_output

[root@node102.yinzhengjie.org.cn ~]#

[root@node102.yinzhengjie.org.cn ~]# hdfs dfs -ls  /user/yinzhengjie/data/day001/test_input

Found  items

-rw-r--r--    root supergroup           -- : /user/yinzhengjie/data/day001/test_input/_SUCCESS

-rw-r--r--    root supergroup   -- : /user/yinzhengjie/data/day001/test_input/part-m-

-rw-r--r--    root supergroup   -- : /user/yinzhengjie/data/day001/test_input/part-m-

[root@node102.yinzhengjie.org.cn ~]#

[root@node102.yinzhengjie.org.cn ~]# hdfs dfs -ls  /user/yinzhengjie/data/day001/test_output

Found  items

-rw-r--r--    root supergroup           -- : /user/yinzhengjie/data/day001/test_output/_SUCCESS

-rw-r--r--   root supergroup         -- : /user/yinzhengjie/data/day001/test_output/_partition.lst

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

-rw-r--r--    root supergroup    -- : /user/yinzhengjie/data/day001/test_output/part-r-

[root@node102.yinzhengjie.org.cn ~]#

3>.验证输出

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]# pwd

/opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]#

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar teravalidate  /user/yinzhengjie/data/day001/test_output  /user/yinzhengjie/data/day001/ts_validate

// :: INFO input.FileInputFormat: Total input paths to process :

Spent 29ms computing base-splits.

Spent 3ms computing TeraScheduler splits.

// :: INFO mapreduce.JobSubmitter: number of splits:

// :: INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1558520562958_0003

// :: INFO impl.YarnClientImpl: Submitted application application_1558520562958_0003

// :: INFO mapreduce.Job: The url to track the job: http://node101.yinzhengjie.org.cn:8088/proxy/application_1558520562958_0003/

// :: INFO mapreduce.Job: Running job: job_1558520562958_0003

// :: INFO mapreduce.Job: Job job_1558520562958_0003 running in uber mode : false

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job:  map % reduce %

// :: INFO mapreduce.Job: Job job_1558520562958_0003 completed successfully

// :: INFO mapreduce.Job: Counters:

        File System Counters

                FILE: Number of bytes read=

                FILE: Number of bytes written=

                FILE: Number of read operations=

                FILE: Number of large read operations=

                FILE: Number of write operations=

                HDFS: Number of bytes read=

                HDFS: Number of bytes written=

                HDFS: Number of read operations=

                HDFS: Number of large read operations=

                HDFS: Number of write operations=

        Job Counters

                Launched map tasks=

                Launched reduce tasks=

                Data-local map tasks=

                Rack-local map tasks=

                Total time spent by all maps in occupied slots (ms)=

                Total time spent by all reduces in occupied slots (ms)=

                Total time spent by all map tasks (ms)=

                Total time spent by all reduce tasks (ms)=

                Total vcore-milliseconds taken by all map tasks=

                Total vcore-milliseconds taken by all reduce tasks=

                Total megabyte-milliseconds taken by all map tasks=

                Total megabyte-milliseconds taken by all reduce tasks=

        Map-Reduce Framework

                Map input records=

                Map output records=

                Map output bytes=

                Map output materialized bytes=

                Input split bytes=

                Combine input records=

                Combine output records=

                Reduce input groups=

                Reduce shuffle bytes=

                Reduce input records=

                Reduce output records=

                Spilled Records=

                Shuffled Maps =

                Failed Shuffles=

                Merged Map outputs=

                GC time elapsed (ms)=

                CPU time spent (ms)=

                Physical memory (bytes) snapshot=

                Virtual memory (bytes) snapshot=

                Total committed heap usage (bytes)=

        Shuffle Errors

                BAD_ID=

                CONNECTION=

                IO_ERROR=

                WRONG_LENGTH=

                WRONG_MAP=

                WRONG_REDUCE=

        File Input Format Counters

                Bytes Read=

        File Output Format Counters

                Bytes Written=

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.-.cdh5.15.1.p0./lib/hadoop-mapreduce]#

[root@node101.yinzhengjie.org.cn /opt/cloudera/parcels/CDH-5.15.1-1.cdh5.15.1.p0.4/lib/hadoop-mapreduce]# hadoop jar hadoop-mapreduce-examples.jar teravalidate /user/yinzhengjie/data/day001/test_output /user/yinzhengjie/data/day001/ts_validate

[root@node102.yinzhengjie.org.cn ~]# hdfs dfs -ls  /user/yinzhengjie/data/day001

Found  items

drwxr-xr-x   - root supergroup           -- : /user/yinzhengjie/data/day001/test_input

drwxr-xr-x   - root supergroup           -- : /user/yinzhengjie/data/day001/test_output

drwxr-xr-x   - root supergroup           -- : /user/yinzhengjie/data/day001/ts_validate

[root@node102.yinzhengjie.org.cn ~]#

[root@node102.yinzhengjie.org.cn ~]# hdfs dfs -ls  /user/yinzhengjie/data/day001/ts_validate

Found  items

-rw-r--r--    root supergroup           -- : /user/yinzhengjie/data/day001/ts_validate/_SUCCESS

-rw-r--r--    root supergroup          -- : /user/yinzhengjie/data/day001/ts_validate/part-r-

[root@node102.yinzhengjie.org.cn ~]#

[root@node102.yinzhengjie.org.cn ~]# hdfs dfs -cat /user/yinzhengjie/data/day001/ts_validate/part-r-00000　　　　　　#我们可以看到checksum是有内容，说明验证的数据是有序的。

checksum        4c49607ac53602

[root@node102.yinzhengjie.org.cn ~]#

[root@node102.yinzhengjie.org.cn ~]#

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