为什么对于Java示例与Hadoop流相同的Hadoop示例，拆分的数量不同，并使用来自权威指南的python示例

Question

我正在执行Hadoop权威指南第2章中的最高温度示例，我注意到Java示例的分割数量与使用Python的Hadoop Streaming不同。有人能帮我理解这种差异背后的原因吗？

Java示例输出：

Job Counters 
                Launched map tasks=1
                Launched reduce tasks=1
                Rack-local map tasks=1
                Total time spent by all maps in occupied slots (ms)=7007
                Total time spent by all reduces in occupied slots (ms)=5760
                Total time spent by all map tasks (ms)=7007
                Total time spent by all reduce tasks (ms)=5760
                Total vcore-seconds taken by all map tasks=7007
                Total vcore-seconds taken by all reduce tasks=5760
                Total megabyte-seconds taken by all map tasks=7175168
                Total megabyte-seconds taken by all reduce tasks=5898240

使用Python示例输出Hadoop流：

Job Counters 
        Launched map tasks=2
        Launched reduce tasks=1
        Rack-local map tasks=2
        Total time spent by all maps in occupied slots (ms)=16730
        Total time spent by all reduces in occupied slots (ms)=4673
        Total time spent by all map tasks (ms)=16730
        Total time spent by all reduce tasks (ms)=4673
        Total vcore-seconds taken by all map tasks=16730
        Total vcore-seconds taken by all reduce tasks=4673
        Total megabyte-seconds taken by all map tasks=17131520
        Total megabyte-seconds taken by all reduce tasks=4785152