第1关：WordCount - 词频统计
# -*- coding: UTF-8 -*-
from pyspark import SparkContextif __name__ == "__main__":"""需求：对本地文件系统URI为：/root/wordcount.txt 的内容进行词频统计"""# ********** Begin **********#sc = SparkContext("local","pySpark")rdd = sc.textFile("/root/wordcount.txt")values = rdd.flatMap(lambda x:str(x).split(" ")).map(lambda x:(x,1)).reduceByKey(lambda x,y:x+y).sortBy(lambda x:tuple(x)[1],False)print(values.collect())# ********** End **********#
第2关：Friend Recommendation - 好友推荐
# -*- coding: UTF-8 -*-
from pyspark import SparkContextdef word_couple(word1, word2):if hash(word1) > hash(word2):return word1 + '_' + word2return word2 + '_' + word1def relations(items):result = []for i in range(1, len(items)):result.append((word_couple(items[0], items[i]), 0))for j in range(i+1, len(items)):result.append((word_couple(items[i], items[j]), 1))return resultdef fun2(x):values = tuple(x[1])return ((x[0], 0) if min(values)==0 else (x[0], sum(values)))if __name__ == "__main__":"""需求：对本地文件系统URI为：/root/friend.txt 的数据统计间接好友的数量"""# ********** Begin **********#sc = SparkContext("local", "friend recommendation")src = sc.textFile("/root/friend.txt").map(lambda x:x.strip().encode('utf-8').split(" "))rdd = src.flatMap(relations).reduceByKey(lambda x,y:0 if x==0 or y==0 else x+y).filter(lambda x:x[1]>0)print(rdd.collect())# ********** End **********#
)
