Hadoop系列之MapReduce(分布式计算测试)
MapReduce分布式计算测试1.统计文本单词数量
1.1.查看当前hdfs分布式系统存储内容
# hdfs dfs -ls -R /
drwxr-xr-x - root supergroup 0 2014-09-15 09:05 /test
-rw-r--r-- 2 root supergroup 4 2014-09-15 09:05 /test/aa.txt
-rw-r--r-- 2 root supergroup 4 2014-09-12 21:58 /test/bb.txt
1.2.在本地建立测试文件为count.txt
# touch count.txt
# ls
count.txt
1.3.在count.txt输入测试内容
# cat count.txt
hello world
hello hadoop
hello python
hadoop hdfs mapreduce
1.4.在hdfs分布式系统上建立测试目录/mapreduce/input
#hdfs dfs -mkdir -p /mapreduce/input
1.5.再次查看当前hdfs分布式系统目录是否成功
# hdfs dfs -ls -R /
drwxr-xr-x - root supergroup 0 2014-09-15 14:24 /mapreduce
drwxr-xr-x - root supergroup 0 2014-09-15 14:24 /mapreduce/input
drwxr-xr-x - root supergroup 0 2014-09-15 09:05 /test
-rw-r--r-- 2 root supergroup 4 2014-09-15 09:05 /test/aa.txt
-rw-r--r-- 2 root supergroup 4 2014-09-12 21:58 /test/bb.txt
1.6.上传本地测试文件count.txt 到hdfs分布式存储/mapreduce/input目录下
# hdfs dfs -put count.txt /mapreduce/input
1.7.检查count.txt文件是否上传成功
# hdfs dfs -ls/mapreduce/input
-rw-r--r-- 2 root supergroup 60 2014-09-15 14:27 /mapreduce/input/count.txt
1.8.通过mapreduce统计/mapreduce/input/count.txt单词数量
#hadoop jar /usr/local/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.4.0.jar wordcount /mapreduce/input/count.txt /mapreduce/output
1.9.查看统计数量的结果目录为/mapreduce/output
# hdfs dfs -ls -R /mapreduce/output
-rw-r--r-- 2 root supergroup 0 2014-09-15 14:30 /mapreduce/output/_SUCCESS
-rw-r--r-- 2 root supergroup 53 2014-09-15 14:30 /mapreduce/output/part-r-00000
1.10查看真正的单词数量文件为/mapreduce/output/part-r-00000
# hdfs dfs -cat /mapreduce/output/part-r-00000
hadoop 2
hdfs 1
hello 3
mapreduce 1
python 1
world 1
2.通过shell脚本分布式搜索给定的内容
2.1建立测试文件file01和file02
# cat file01
hello world bye world
# cat file02
hello hadoop bye hadoop
2.2上传测试文件到hdfs分布式存储
#hdfs dfs -put file0*/mapreduce/input
2.3查看上传文件是否成功
# hdfs dfs -ls /mapreduce/input
-rw-r--r-- 2 root supergroup 22 2014-09-15 14:42 /mapreduce/input/file01
-rw-r--r-- 2 root supergroup 24 2014-09-15 14:42 /mapreduce/input/file02
2.4编写shell脚本搜索带有hadoop关键字
# cat reduce.sh
grep hadoop
2.5执行分布式计算
#hadoop jar /usr/local/hadoop/share/hadoop/tools/lib/hadoop-streaming-2.4.0.jar -input /mapreduce/input/ -output /mapreduce/output -mapper /bin/cat -reducer /root/soft/reduce.sh -file /root/soft/reduce.sh
2.6查看搜索结果文件/mapreduce/output/part-00000
# hdfs dfs-cat /mapreduce/output/part-00000
hello hadoop bye hadoop
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