MapReduce是一种分布式计算模型，通常用于处理大规模数据集。在这里，我们假设你有一个包含用户访问日志的文本文件，每行记录包含日期和访问次数。以下是使用Python编写的基本Hadoop MapReduce程序（Hadoop Streaming API）来统计每个日期的访问次数：

```python # Mapper (input is log line, output key-value pairs with date as key and 1 as value) mapper.py #!/usr/bin/env python import sys for line in sys.stdin: # Split the line into parts based on a delimiter (e.g., space or comma) data = line.strip().split(',') # Assuming the first element is the date date = data[0] # Emit the key-value pair for each visit print(f"{date} 1", sep=" ") # Reducer (input is key-value pairs grouped by date, output sum of values) reducer.py #!/usr/bin/env python import sys current_date = None total_visits = 0 for line in sys.stdin: # Split the key-value pair key, value = line.strip().split(" ") if current_date and key != current_date: # Output the previous day's total print(f"{current_date} {total_visits}", sep=" ") current_date = key total_visits += int(value) # Last reducer to handle the last day if current_date: print(f"{current_date} {total_visits}", sep=" ") # Hadoop command to execute the job hadoop jar hadoop-streaming.jar -file mapper.py -mapper mapper.py -file reducer.py -reducer reducer.py -input input_log.txt -output output_dir/ ```