如何在Hadoop中控制map的个数
转载自：如何在hadoop中控制map的个数hadoop提供了一个设置map个数的参数mapred.map.tasks，我们可以通过这个参数来控制map的个数。但是通过这种方式设置map的个数，并不是每次都有效的。原因是mapred.map.tasks只是一个hadoop的参考数值，最终map的个数，还
转载自：如何在hadoop中控制map的个数 hadoop提供了一个设置map个数的参数mapred.map.tasks，我们可以通过这个参数来控制map的个数。但是通过这种方式设置map的个数，并不是每次都有效的。原因是mapred.map.tasks只是一个hadoop的参考数值，最终map的个数，还取决于其他的因素。 为了方便介绍，先来看几个名词： block_size : hdfs的文件块大小，默认为64M，可以通过参数dfs.block.size设置 total_size : 输入文件整体的大小 input_file_num : 输入文件的个数 （1）默认map个数 如果不进行任何设置，默认的map个数是和blcok_size相关的。 default_num = total_size / block_size; （2）期望大小 可以通过参数mapred.map.tasks来设置程序员期望的map个数，但是这个个数只有在大于default_num的时候，才会生效。 goal_num = mapred.map.tasks; （3）设置处理的文件大小 可以通过mapred.min.split.size 设置每个task处理的文件大小，但是这个大小只有在大于block_size的时候才会生效。 split_size = max(mapred.min.split.size, block_size); split_num = total_size / split_size; （4）计算的map个数 compute_map_num = min(split_num, max(default_num, goal_num)) 除了这些配置以外，mapreduce还要遵循一些原则。 mapreduce的每一个map处理的数据是不能跨越文件的，也就是说max_map_num 原文地址：如何在Hadoop中控制map的个数, 感谢原作者分享。
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