0025-CENTOS6.5安装CDH5.12.1(二)
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_~]# 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=27513Total 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=2424078336Virtual memory (bytes) snapshot=9435451392
Total committedheap usage (bytes)=_2822766592_
_Shuffle_ Errors BAD\_ID=0CONNECTION=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-cdh5.12.1
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_>_
醉酒鞭名马，少年多浮夸！ 岭南浣溪沙，呕吐酒肆下！挚友不肯放，数据玩的花！
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。
欢迎关注Hadoop实操，第一时间，分享更多Hadoop干货，喜欢请关注分享。
原创文章，欢迎转载，转载请注明：转载自微信公众号Hadoop实操
