Hadoop使用实例

一、词频统计

1.下载电子书

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

下载电子书

2.编写mapper与reducer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	%s" % (word, 1)

mapper.py

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('	', 1)
    try:
        count = int(count)
    except ValueError: 
        continue
    if current_word == word:
        current_count += count
    else:
        if current_word:
            print "%s	%s" % (current_word, current_count)
        current_count = count
        current_word = word
 
if word == current_word: 
    print "%s	%s" % (current_word, current_count)

reduce.py

授权

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

3.本地测试mapper与reducer

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

本地测试

gedit my.txt

编写my.txt

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

测试my.txt

4.将文本数据上传到HDFS上

start-dfs.sh
start.yarn.sh
jps

启动Hadoop

hdfs dfs -put *.txt input
hdfs dfs -ls input
hdfs dfs -du input

上传文本

查看数据大小

5.准备Hadoop streaming

配置~/.bashrc

export STREAM=$HADOOP_HOME /share/hadoop/tools/lib/hadoop-streaming-3.1.3.jar

配置~/.bashrc

验证配置是否成功

验证成功

二、气象数据分析

1.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*

下载气象数据

2.查看下载的气象数据文件

cd data/ftp.ncdc.noaa.gov/pub/data/noaa/2020
ls -l

查看气象数据文件

3.解压气象数据文件

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

解压气象数据文件

4.上传气象数据文件

hdfs dfs -mkdir qx
hdfs dfs -put data qx

创建qx文件夹

上传气象数据文件

查看上传结果