一、词频统计:
- 读文本文件生成RDD lines
lines=sc.textFile("file:///usr/local/spark/mycode/rdd/word.txt")
lines.foreach(print)
- 将一行一行的文本分割成单词 words flatmap()
words=lines.flatMap(lambda line:line.split())
words.foreach(print)
- 全部转换为小写 lower()
words1=lines.map(lambda word:word.lower())
words1.foreach(print)
- 去掉长度小于3的单词 filter()
word=words.filter(lambda words:len(words)>2)
words.foreach(print)
- 去掉停用词
with open("/usr/local/spark/mycode/rdd/stopwords.txt") as f:
stops=f.read().split()
lines.flatMap(lambda line:line.split()).filter(lambda word:word not in stops).collect()
- 转换成键值对 map()
words.map(lambda word:(word,1)).collect()
- 统计词频 reduceByKey()
words.map(lambda word:(word,1)).reduceByKey(lambda a,b:a+b).collect()
- 按字母顺序排序
words.map(lambda word : (word,1)).reduceByKey(lambda a,b:a+b).sortBy(lambda word:word[0]).collect()
- 按词频排序
words.map(lambda word:(word.lower(),1)).reduceByKey(lambda a,b:a+b).sortBy(lambda word:word[1],False).collect()
二、学生课程分数案例
- 总共有多少学生?map(), distinct(), count()
lines=sc.textFile("file:///usr/local/spark/mycode/rdd/chapter4-data01.txt")
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()
name = lines.map(lambda line:line.split(',')).map(lambda line:(line[0],(line[1],line[2])))
name.take(5)
name.count()
name.countByKey()
- 每门课程有多少个学生选?map(), countByValue()
name=lines.map(lambda line:line.split(',')).map(lambda line:line[1])
name.countByValue()
- Tom选修了几门课?每门课多少分?filter(), map() RDD
Tom=lines.filter(lambda line:'Tom' in line).map(lambda line:line.split(','))
Tom.collect()
- Tom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[2])).lookup('Tom')
- Tom的成绩按分数大小排序。filter(), map(), sortBy()
Tom.sortBy(lambda word:word[2],False).collect()
- Tom的平均分。map(),lookup(),mean()
from numpy import mean
tomList=lines.map(lambda line:line.split(',')).map(lambda line:(line[0],line[2])).lookup('Tom')
mean([int(x) for x in tomList])