1.读文本文件生成RDD lines

lines = sc.textFile('file:///home/hadoop/word.txt')

lines.collect()

2.将一行一行的文本分割成单词 words

words=lines.flatMap(lambda line:line.split())

words.collect()

3.全部转换为小写

words=lines.flatMap(lambda line:line.lower().split())

words.collect()

4.去掉长度小于3的单词

words=lines.flatMap(lambda line:line.split()).filter(lambda line:len(line)>3)

words.collect()

5.去掉停用词

  1.准备停用词文本：

lines = sc.textFile('file:///home/hadoop/stopwords.txt')
stop = lines.flatMap(lambda line : line.split()).collect()

stop

  2.去除停用词：

 lines=sc.textFile("file:///home/hadoop/word.txt")

words=lines.flatMap(lambda line:line.lower().split()).filter(lambda word:word not in stop)

words
words.collect()

6.转换成键值对 map()

wordskv=words.map(lambda word:(word.lower(),1))

wordskv.collect()

7.统计词频 reduceByKey()

wordskv.reduceByKey(lambda a,b:a+b).collect()

8、按字母顺序排序 sortBy(f)

wordskv=words.map(lambda word:(word.lower(),1)).reduceByKey(lambda a,b:a+b).sortBy(lambda word:word[0])

wordskv.collect()

9、按词频排序 sortByKey()

wordskv=words.map(lambda word:(word.lower(),1)).reduceByKey(lambda a,b:a+b)

wordskv.sortByKey().collect()

二、学生课程分数案例

• 总共有多少学生？map(), distinct(), count()
• lines.map(lambda line : line.split(',')[0]).distinct().count()
• 
• 开设了多少门课程？

• lines.map(lambda line : line.split(',')[1]).distinct().count()

• 每个学生选修了多少门课？map(), countByKey()
• lines.map(lambda line : line.split(',')).map(lambda line:(line[0],(line[1],line[2]))).countByKey()
• 每门课程有多少个学生选？map(), countByValue()
• lines.map(lambda line : line.split(',')).map(lambda line : (line[1])).countByValue()
• Allen选修了几门课？每门课多少分？filter(), map() RDD
• lines.filter(lambda line:"Allen" in line).map(lambda line:line.split(',')).collect()
• Allen选修了几门课？每门课多少分？map(),lookup()  list
• lines.map(lambda line:line.split(',')).map(lambda line:(line[0],(line[1],line[2]))).lookup("Allen")
• Allen的成绩按分数大小排序。filter(), map(), sortBy()

   

• lines.filter(lambda line:"Allen" in line).map(lambda line:line.split(',')).sortBy(lambda line:(line[2])).collect()
• Allen的平均分。map(),lookup(),mean()

• import numpy as np

• meanlist=lines.map(lambda line:line.split(',')).map(lambda line:(line[0],line[2])).lookup("Allen")

• np.mean([int(x) for x in meanlist])