实现WordCount的MapReduce代码

以下是一个实现WordCount的MapReduce代码的例子：

# Mapper函数
def mapper(text):
    words = text.split()  # 将文本拆分成单词列表
    word_count = []
    for word in words:
        word_count.append((word, 1))  # 将每个单词映射为(key, value)对，value为1
    return word_count

# Reducer函数
def reducer(word_count_list):
    word_count_dict = {}
    for word_count in word_count_list:
        word = word_count[0]
        count = word_count[1]
        if word in word_count_dict:
            word_count_dict[word] += count  # 对相同单词的计数进行累加
        else:
            word_count_dict[word] = count
    return word_count_dict

# MapReduce函数
def word_count_map_reduce(text_list):
    word_count_list = []
    for text in text_list:
        word_count_list.extend(mapper(text))  # 将每个文本的映射结果合并到一个列表中
    word_count_dict = reducer(word_count_list)  # 对映射结果进行归约
    return word_count_dict

# 测试数据
text_list = ["Hello world", "Hello Python", "Python is great"]

# 调用MapReduce函数
result = word_count_map_reduce(text_list)
print(result)  # 输出：{'Hello': 2, 'world': 1, 'Python': 2, 'is': 1, 'great': 1}