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示例的拆分数量与使用python的hadoop流不同。有人能帮我理解这种差异背后的原因吗？
java输出示例：

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的hadoop流的输出示例：

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