Hadoop使用实例

一.词频统计

1.下载喜欢的电子书或大量文本数据，并保存在本地文本文件中

wget http://www.gutenberg.org/files/1342/1342-0.txt

 

 

 

 2.编写map与reduce函数

#mapper.py

#!/usr/bin/env python
import sys
for line in sys.stdin:
    line = line.strip()
    words = line.split()
    for word in words:
        print "%s\t%s" % (word, 1)

 

 

#reducer.py

#!/usr/bin/env python
from operator import itemgetter
import sys
 
current_word = None
current_count = 0
word = None
 
for line in sys.stdin:
    line = line.strip()
    word, count = line.split('\t', 1)
    try:
        count = int(count)
    except ValueError: 
        continue
    if current_word == word:
        current_count += count
    else:
        if current_word:
            print "%s\t%s" % (current_word, current_count)
        current_count = count
        current_word = word
 
if word == current_word: 
    print "%s\t%s" % (current_word, current_count)

　　

 

 

3.本地测试map与reduce

#授权
ls -l
chmod a+x mapper.py
chmod a+x reducer.py
ls -l

 

 

 

echo “usr local hadoop user hadoop home hadoop" | ./mapper.py
echo “usr local hadoop user hadoop home hadoop" | ./mapper.py | ./reducer.py
echo “usr local hadoop user hadoop home hadoop" | ./mapper.py | sort -k1,1 | ./reducer.py

 

 

 

 

cat my.txt | ./mapper.py
cat my.txt | ./mapper.py | ./reducer.py
cat my.txt | ./mapper.py | sort -k1,1 | ./reducer.py

 

 

 

 

4.将文本数据上传至HDFS上

start-dfs.sh
start.yarn.sh
jps
hdfs dfs -put *.txt /input
hdfs dfs -ls /input
hdfs dfs -du /input

 

 

 

5.用hadoop streaming提交任务

 

配置~/.bashrc
export STREAM=$HADOOP_HOME /share/hadoop/tools/lib/hadoop-streaming-2.7.3.jar

 

 

 

 

二、气象数据分析

1.批量下载气象数据

 

wget -D --accept-regex=REGEX -P data -r -c ftp://ftp.ncdc.noaa.gov/pub/data/noaa/2020/5*

 

 

 

 

 

2.解压数据集，并保存在本地文本文件中

 

cd data/ftp.ncdc.noaa.gov/pub/data/noaa/2020
ls -l
zcat data/ftp.ncdc.noaa.gov/pub/data/noaa/2020/5*.gz >qxdata.txt

 

 

 

 

 

3.将气象数据上传至HDFS上

hdfs dfs -mkdir /wether
hdfs dfs -put data /wether
hdfs dfs -ls /wether