Java教程

05 RDD编程

本文主要是介绍05 RDD编程,对大家解决编程问题具有一定的参考价值,需要的程序猿们随着小编来一起学习吧!

一、词频统计:

  1. 读文本文件生成RDD lines

lines=sc.textFile("file:///usr/local/spark/mycode/rdd/word.txt")
lines.foreach(print)

  1. 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)

  1. 全部转换为小写 lower()

words1=lines.map(lambda word:word.lower())
words1.foreach(print)

  1. 去掉长度小于3的单词 filter()

word=words.filter(lambda words:len(words)>2)
words.foreach(print)

  1. 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()

  1. 转换成键值对 map()

words.map(lambda word:(word,1)).collect()

  1. 统计词频 reduceByKey()

words.map(lambda word:(word,1)).reduceByKey(lambda a,b:a+b).collect()

  1. 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()

  1. 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

  1. 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()

  1. 开设了多少门课程?

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

  1. 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()

  1. 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()

  1. 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()

  1. 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')

  1. Tom的成绩按分数大小排序。filter(), map(), sortBy()

Tom.sortBy(lambda word:word[2],False).collect()

  1. 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])

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