A Combiner runs after the Mapper and before the Reducer, it will receive as input all data emitted by the Mapper instances on a given node. It then emits output to the Reducers. So the records of the combiner input should less than the maps ouputs.
12/08/29 13:38:49 INFO mapred.JobClient: Map-Reduce Framework
12/08/29 13:38:49 INFO mapred.JobClient: Reduce input groups=8649
12/08/29 13:38:49 INFO mapred.JobClient: Map output materialized bytes=306210
12/08/29 13:38:49 INFO mapred.JobClient: Combine output records=859412
12/08/29 13:38:49 INFO mapred.JobClient: Map input records=457272
12/08/29 13:38:49 INFO mapred.JobClient: Reduce shuffle bytes=0
12/08/29 13:38:49 INFO mapred.JobClient: Reduce output records=8649
12/08/29 13:38:49 INFO mapred.JobClient: Spilled Records=1632334
12/08/29 13:38:49 INFO mapred.JobClient: Map output bytes=331837344
12/08/29 13:38:49 INFO mapred.JobClient: **Combine input records=26154506**
12/08/29 13:38:49 INFO mapred.JobClient: **Map output records=25312392**
12/08/29 13:38:49 INFO mapred.JobClient: SPLIT_RAW_BYTES=218
12/08/29 13:38:49 INFO mapred.JobClient: Reduce input records=17298
I think it's because the Combiner can also run on the output of previous Combine steps, since your Combiner runs and produces new records which are then Combined with other records coming out of your Mappers. It may also be that Map output records is calculated after the Combiner runs, meaning that there are less records because some have been Combined.
来源：https://stackoverflow.com/questions/12171965/why-is-the-number-of-combiner-input-records-more-than-the-number-of-outputs-of-m