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0025-CENTOS6.5安装CDH5.12.1(二)

发表于:2026-11-03 作者:千家信息网编辑
千家信息网最后更新 2026年11月03日,温馨提示:要看高清无码套图,请使用手机打开并单击图片放大查看。5.快速组件服务验证5.1HDFS验证(mkdir+put+cat+get)mkdir操作:[root@ip-172-31-6-148~]
千家信息网最后更新 2026年11月03日0025-CENTOS6.5安装CDH5.12.1(二)

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5.快速组件服务验证

5.1HDFS验证(mkdir+put+cat+get)

mkdir操作:

[root@ip-172-31-6-148~]# hadoop fs -mkdir -p /fayson/test

[root@ip-172-31-6-148 ~]# hadoop fs -ls /

Found 3 items

drwxr-xr-x - root supergroup 0 2017-09-0506:16 /fayson

drwxrwxrwt - hdfs supergroup 0 2017-09-0504:24 /tmp

drwxr-xr-x - hdfs supergroup 0 2017-09-0504:24 /user

[root@ip-172-31-6-148 ~]#

put操作:

[root@ip-172-31-6-148~]# vim a.txt

1,test

2,fayson

3.zhangsan

[root@ip-172-31-6-148 ~]#hadoop fs -put a.txt /fayson/test

[root@ip-172-31-6-148 ~]# hadoop fs -ls /fayson/test

Found 1 items

-rw-r--r-- 3 root supergroup 27 2017-09-05 06:20 /fayson/test/a.txt

[root@ip-172-31-6-148 ~]#

cat操作:

[root@ip-172-31-6-148 ~]# hadoop fs -cat /fayson/test/a.txt

1,test

2,fayson

3.zhangsan

[root@ip-172-31-6-148 ~]#

get操作:

[root@ip-172-31-6-148~]# rm -rf a.txt

[root@ip-172-31-6-148 ~]# hadoop fs -get /fayson/test/a.txt

[root@ip-172-31-6-148 ~]# cat a.txt

1,test

2,fayson

3.zhangsan

[root@ip-172-31-6-148 ~]#

5.2Hive验证

使用hive命令行操作

[root@ip-172-31-6-148~]# hive

...

hive> create external table test_table(

> s1 string,

> s2 string

> ) row formatdelimited fields terminated by ','

> stored as textfile location '/fayson/test';

OK

Time taken: 1.933 seconds

hive> select * from test_table;

OK

1 test

2 fayson

3 zhangsan

Time taken: 0.44 seconds, Fetched: 3row(s)

hive> insert into test_table values("4","lisi");

...

OK

Time taken: 18.815 seconds

hive> select * from test_table;

OK

4 lisi

1 test

2 fayson

3 zhangsan

Time taken: 0.079 seconds, Fetched: 4row(s)

hive>

Hive MapReduce操作

hive> select count(*) from test_table;

Query ID = root_20170905064545_100f033c-49b9-488b-9920-648a2e1c7285

...

OK

4

Time taken: 26.428 seconds, Fetched: 1 row(s)

hive>

5.3MapReduce验证

[root@ip-172-31-6-148 hadoop-mapreduce]# pwd

/opt/cloudera/parcels/CDH/lib/hadoop-mapreduce

[root@ip-172-31-6-148 hadoop-mapreduce]#hadoop jar hadoop-mapreduce-examples.jar pi 5 5

Number of Maps = 5

Samples per Map = 5

Wrote input for Map #0

Wrote input for Map #1

Wrote input for Map #2

Wrote input for Map #3

Wrote input for Map #4

Starting Job

17/09/05 06:48:53 INFO client.RMProxy: Connecting to ResourceManager atip-172-31-6-148.fayson.com/172.31.6.148:8032

17/09/05 06:48:53 INFO input.FileInputFormat: Total input paths to process : 5

17/09/05 06:48:53 INFO mapreduce.JobSubmitter: number of splits:5

17/09/05 06:48:54 INFO mapreduce.JobSubmitter: Submitting tokens for job:job_1504585342848_0003

17/09/05 06:48:54 INFO impl.YarnClientImpl: Submitted applicationapplication_1504585342848_0003

17/09/05 06:48:54 INFO mapreduce.Job: The url to track the job:http://ip-172-31-6-148.fayson.com:8088/proxy/application\_1504585342848\_0003/

17/09/05 06:48:54 INFO mapreduce.Job: Running job: job_1504585342848_0003

17/09/05 06:49:01 INFO mapreduce.Job: Job job_1504585342848_0003 running in ubermode : false

17/09/05 06:49:01 INFO mapreduce.Job: map0% reduce 0%

17/09/05 06:49:07 INFO mapreduce.Job: map20% reduce 0%

17/09/05 06:49:08 INFO mapreduce.Job: map60% reduce 0%

17/09/05 06:49:09 INFO mapreduce.Job: map100% reduce 0%

17/09/05 06:49:15 INFO mapreduce.Job: map100% reduce 100%

17/09/05 06:49:16 INFO mapreduce.Job: Job job_1504585342848_0003 completedsuccessfully

17/09/05 06:49:16 INFO mapreduce.Job: Counters: 49

File System Counters

FILE: Numberof bytes read=64

FILE: Numberof bytes written=875624

FILE: Numberof read operations=0

FILE: Numberof large read operations=0

FILE: Number of writeoperations=0

HDFS: Numberof bytes read=1400

HDFS: Numberof bytes written=215

HDFS: Numberof read operations=23

HDFS: Numberof large read operations=0

HDFS: Number of writeoperations=3

Job Counters

Launched map tasks=5

Launched reduce tasks=1

Data-local map tasks=5

Total time spent by all maps in occupiedslots (ms)=27513

            _Total_ **time** spentby all reduces **in** occupied slots (ms)=_3803_
            _Total_ **time** spentby all map tasks (ms)=_27513_
            _Total_ **time** spentby all reduce tasks (ms)=_3803_
            _Total_ vcore-milliseconds taken by all map tasks=27513

Total vcore-millisecondstaken by all reduce tasks=3803

Total megabyte-millisecondstaken by all map tasks=28173312

Total megabyte-millisecondstaken by all reduce tasks=3894272

Map-Reduce Framework

Map inputrecords=5

Map outputrecords=10

Map outputbytes=90

Map outputmaterialized bytes=167

Input splitbytes=810

Combine input records=0

Combine output records=0

Reduce input groups=2

Reduce shuffle bytes=167

Reduce input records=10

Reduce output records=0

Spilled Records=20

Shuffled Maps =5

Failed Shuffles=0

Merged Map outputs=5

GC timeelapsed (ms)=273

            _CPU_ **time** spent(ms)=_4870_
            _Physical_ memory (bytes) snapshot=2424078336

Virtual memory (bytes) snapshot=9435451392

Total committedheap usage (bytes)=2822766592

    _Shuffle_ Errors
            BAD\_ID=0

CONNECTION=0

IO_ERROR=0

WRONG_LENGTH=0

WRONG_MAP=0

WRONG_REDUCE=0

File Input FormatCounters

Bytes Read=590

File Output FormatCounters

Bytes Written=97

Job Finished in 23.453 seconds

Estimated value of Pi is 3.68000000000000000000

[root@ip-172-31-6-148 hadoop-mapreduce]#

5.4Spark验证

[root@ip-172-31-6-148~]# spark-shell

Setting default log level to "WARN".

To adjust logging level use sc.setLogLevel(newLevel).

Welcome to

  _\_\_\_\__              \_\_

/ __/__ ___ _____/ /__

\_\ \/ \_ \/ \_ _`_/\_\_/  '\_/

/___/ .__/_,_/_//_/_\ version 1.6.0

/_/

...

Spark context available as sc (master = yarn-client, app id = application_1504585342848_0004).

17/09/05 06:51:59 WARN metastore.ObjectStore: Version information not found in metastore.hive.metastore.schema.verification is not enabled so recording the schemaversion 1.1.0-cdh6.12.1

17/09/05 06:51:59 WARN metastore.ObjectStore: Failed to get database default,returning NoSuchObjectException

SQL context available as sqlContext.

scala> val textFile=sc.textFile("hdfs://ip-172-31-6-148.fayson.com:8020/fayson/test/a.txt")

textFile: org.apache.spark.rdd.RDDString =hdfs://ip-172-31-6-148.fayson.com:8020/fayson/test/a.txt MapPartitionsRDD1 at textFileat :27

scala> textFile.count()

res0: Long = 3

scala>

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