标签：lte text 选修课 文本文件 rgba line 键值 http park
一、词频统计：
1.读文本文件生成RDD lines
2.将一行一行的文本分割成单词 words flatmap()
lines=sc.textFile("file:///usr/local/spark/mycode/wordcount/word.txt") words = lines.flatMap(lambda line:line.split()).collect() print(words)
3.全部转换为小写 lower()
sc.parallelize(words).map(lambda line: line.lower()).collect()
4.去掉长度小于3的单词 filter()
words1=sc.parallelize(words) words1.collect() words1.filter(lambda word:len(word)>3).collect()
5.去掉停用词
with open(‘/usr/local/spark/mycode/stopwords.txt‘)as f: stops=f.read().split() words1.filter(lambda word:word not in stops).collect()
6.转换成键值对 map()
words1.map(lambda word:(word,1)).collect()
7.统计词频 reduceByKey()
words1.map(lambda word:(word,1)).reduceByKey(lambda a,b:b+b).collect()
二、学生课程分数 groupByKey()
-- 按课程汇总全总学生和分数
1. 分解出字段 map()
lines = sc.textFile(‘file:///usr/local/spark/mycode/chapter4-data01.txt‘) lines.take(5)
2. 生成键值对 map()
lines.map(lambda line:line.split(‘,‘)).take(5)
3. 按键分组
lines.map(lambda line:line.split(‘,‘)).map(lambda line:(line[1],(line[0],line[2]))).take(5)
4. 输出汇总结果
groupByCoure=lines.map(lambda line:line.split(‘,‘)).map(lambda line:(line[1],(line[0],line[2]))).groupByKey() for i in groupByCoure.first()[1]: print(i)
三、学生课程分数 reduceByKey()
-- 每门课程的选修人数
lines = sc.textFile(‘file:///usr/local/spark/mycode/chapter4-data01.txt‘)>>> number=lines.map(lambda line:line.split(‘,‘)).map(lambda line:(line[1],1)) number1 = number.reduceByKey(lambda x,y:x+y) number1.collect()
number=lines.map(lambda line:line.split(‘,‘)).map(lambda line:(line[0],1)) number2 = number.reduceByKey(lambda x,y:x+y) number2.collect()
-- 每个学生的选修课程数
标签：lte text 选修课 文本文件 rgba line 键值 http park
原文地址：https://www.cnblogs.com/jieninice/p/14617633.html
