我有一个mapreduce程序，当在1%的数据集上运行时，这是所需的时间：

Job Counters
    Launched map tasks=3
    Launched reduce tasks=45
    Data-local map tasks=1
    Rack-local map tasks=2
    Total time spent by all maps in occupied slots (ms)=29338
    Total time spent by all reduces in occupied slots (ms)=200225
    Total time spent by all map tasks (ms)=29338
    Total time spent by all reduce tasks (ms)=200225
    Total vcore-seconds taken by all map tasks=29338
    Total vcore-seconds taken by all reduce tasks=200225
    Total megabyte-seconds taken by all map tasks=30042112
    Total megabyte-seconds taken by all reduce tasks=205030400

我怎样才能推断出分析100%数据所需的时间？我的理由是，因为1%是一个街区，所以它需要100倍多的时间，但在100%上运行时，实际需要134倍多的时间。
100%数据的计时

Job Counters
    Launched map tasks=2113
    Launched reduce tasks=45
    Data-local map tasks=1996
    Rack-local map tasks=117
    Total time spent by all maps in occupied slots (ms)=26800451
    Total time spent by all reduces in occupied slots (ms)=3607607
    Total time spent by all map tasks (ms)=26800451
    Total time spent by all reduce tasks (ms)=3607607
    Total vcore-seconds taken by all map tasks=26800451
    Total vcore-seconds taken by all reduce tasks=3607607
    Total megabyte-seconds taken by all map tasks=27443661824
    Total megabyte-seconds taken by all reduce tasks=3694189568