write(str(word) +": " + str(count) + "\n") spark.stop() 使用 python word_count.py input output 3 运行后,可在 output 中查看对应的输出文件 result.txt : Hello: 3 World: 2 Goodbye: 1 David: 1 Tom: 1 可见成功完成了单词计数功能。 参考 [1] Spark官方文档: Quick Start [2] 许利杰...
#!/usr/bin/env python from operator import itemgetter import sys current_word = None current_count = 0 word = None for line in sys.stdin: line = line.strip() word, count = line.split('\t', 1) try: count = int(count) except ValueError: #count如果不是数字的话,直接忽略掉 continue...
.map(lambdaword: (word,1))\ .reduceByKey(add) output = counts.collect()withopen(os.path.join(output_path,"result.txt"),"wt")asf:for(word, count)inoutput: f.write(str(word) +": "+str(count) +"\n") spark.stop() 使用python word_count.py input output 3运行后,可在output中查看...
三、基于多进程实现MapReduce 由于Python中GIL机制的存在,无法实现真正的并行。这里有两种解决方案,一种是使用其他语言,例如C语言,这里我们不考虑;另一种就是利用多核,CPU的多任务处理能力。 from collections import defaultdict import multiprocessing def mapper(chunk): word_count = defaultdict(int) for word in...
line=line.strip()words=line.split()forwordinwords:# 注意这里哦print("%s\t%s"%(word,1)) Reducer 代码语言:javascript 代码运行次数:0 运行 AI代码解释 #!/usr/bin/env python#-*-coding:utf-8-*-"""---FileName:reducerAuthor:yingDate:18-12-6---Change Activity:18-12-6"""importsys __au...
/usr/bin/env pythonfromoperatorimportitemgetterimportsys current_word=None current_count=0 word=Noneforlineinsys.stdin: line=line.strip() word, count= line.split('\t', 1)try: count=int(count)exceptValueError:#count如果不是数字的话,直接忽略掉continueifcurrent_word ==word:...
/usr/bin/env pythonfromoperatorimportitemgetterimportsyscurrent_word=Nonecurrent_count=0word=Noneforlineinsys.stdin:line=line.strip()word,count=line.split('\t',1)try:count=int(count)exceptValueError:continueifcurrent_word==word:current_count+=countelse:ifcurrent_word:print"%s\t%s"%(current_word...
# send all (num_occurrences, word) pairs to the same reducer. # num_occurrences is so we can easily use Python's max() function. yield (word,sum(counts)) def steps(self): return [ (mapper=self.mapper_get_words, combiner=self.combiner_count_words, ...
输入命令cat word.txt | ./mapper.py,运行结果如下: reducer.py #!/usr/bin/python3 import sys current_word = None current_count = 0 word = None for line in sys.stdin: line = line.strip() word, count = line.split("\t", 1) ...
```python from collections import defaultdict import itertools # Map函数 def map_function(data):words = data.split()return [(word, 1) for word in words]# Reduce函数 def reduce_function(mapped_data):word_count = defaultdict(int)for word, count in mapped_data:word_count[word] += count re...