大数据之---Yarn伪分布式部署和MapReduce案例

[hadoop@hadoop000 hadoop]$ cp mapred-site.xml.template mapred-site.xml

配置yarn
[hadoop@hadoop000 hadoop]$ vi mapred-site.xml


mapreduce.framework.name
yarn

配置mapreduce
[hadoop@hadoop000 hadoop]$ vi yarn-site.xml:


yarn.nodemanager.aux-services
mapreduce_shuffle

[hadoop@hadoop01 sbin]$ ./start-yarn.sh

[hadoop@hadoop01 hadoop]$ find ./* -name *examples*
./lib/native/examples
./share/hadoop/mapreduce/sources/hadoop-mapreduce-examples-2.8.1-sources.jar
./share/hadoop/mapreduce/sources/hadoop-mapreduce-examples-2.8.1-test-sources.jar
./share/hadoop/mapreduce/lib-examples
./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.1.jar
./share/doc/hadoop/hadoop-auth-examples
./share/doc/hadoop/hadoop-mapreduce-examples
./share/doc/hadoop/api/org/apache/hadoop/examples
./share/doc/hadoop/api/org/apache/hadoop/security/authentication/examples
[hadoop@hadoop01 hadoop]$ hadoop jar ./share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.1.jar pi 5 10
Number of Maps = 5
Samples per Map = 10
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
18/04/27 12:58:49 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
18/04/27 12:58:50 INFO input.FileInputFormat: Total input files to process : 5
18/04/27 12:58:50 INFO mapreduce.JobSubmitter: number of splits:5
18/04/27 12:58:50 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1524804813835_0001
18/04/27 12:58:51 INFO impl.YarnClientImpl: Submitted application application_1524804813835_0001
18/04/27 12:58:51 INFO mapreduce.Job: The url to track the job: http://hadoop01:8088/proxy/application_1524804813835_0001/
18/04/27 12:58:51 INFO mapreduce.Job: Running job: job_1524804813835_0001
18/04/27 12:59:03 INFO mapreduce.Job: Job job_1524804813835_0001 running in uber mode : false
18/04/27 12:59:03 INFO mapreduce.Job: map 0% reduce 0%
18/04/27 12:59:18 INFO mapreduce.Job: map 100% reduce 0%
18/04/27 12:59:25 INFO mapreduce.Job: map 100% reduce 100%
18/04/27 12:59:26 INFO mapreduce.Job: Job job_1524804813835_0001 completed successfully
18/04/27 12:59:27 INFO mapreduce.Job: Counters: 49
File System Counters
FILE: Number of bytes read=116
FILE: Number of bytes written=819783
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=1350
HDFS: Number of bytes written=215
HDFS: Number of read operations=23
HDFS: Number of large read operations=0
HDFS: Number of write operations=3
Job Counters
Launched map tasks=5
Launched reduce tasks=1
Data-local map tasks=5
Total time spent by all maps in occupied slots (ms)=64938
Total time spent by all reduces in occupied slots (ms)=4704
Total time spent by all map tasks (ms)=64938
Total time spent by all reduce tasks (ms)=4704
Total vcore-milliseconds taken by all map tasks=64938
Total vcore-milliseconds taken by all reduce tasks=4704
Total megabyte-milliseconds taken by all map tasks=66496512
Total megabyte-milliseconds taken by all reduce tasks=4816896
Map-Reduce Framework
Map input records=5
Map output records=10
Map output bytes=90
Map output materialized bytes=140
Input split bytes=760
Combine input records=0
Combine output records=0
Reduce input groups=2
Reduce shuffle bytes=140
Reduce input records=10
Reduce output records=0
Spilled Records=20
Shuffled Maps =5
Failed Shuffles=0
Merged Map outputs=5
GC time elapsed (ms)=1428
CPU time spent (ms)=5740
Physical memory (bytes) snapshot=1536856064
Virtual memory (bytes) snapshot=12578734080
Total committed heap usage (bytes)=1152385024
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=590
File Output Format Counters
Bytes Written=97
Job Finished in 37.717 seconds
Estimated value of Pi is 3.28000000000000000000
[hadoop@hadoop01 hadoop]$