Partitioner没有被调用的情况

map的输出，通过分区函数决定要发往哪个reducer。

有2种情况，我们自定义的Partitioner不会被调用

1. reducer个数为0

   这种情况，没有reducer，不需要分区

2. reducer个数为1

   这种情况，所有的map输出都会发到这个唯一的reducer，不需要调用我们的自定义reducer

hadoop源码

private class NewOutputCollector<K,V>
    extends org.apache.hadoop.mapreduce.RecordWriter<K,V> {
    private final MapOutputCollector<K,V> collector;
    private final org.apache.hadoop.mapreduce.Partitioner<K,V> partitioner;
    private final int partitions;

    @SuppressWarnings("unchecked")
    NewOutputCollector(org.apache.hadoop.mapreduce.JobContext jobContext,
                       JobConf job,
                       TaskUmbilicalProtocol umbilical,
                       TaskReporter reporter
                       ) throws IOException, ClassNotFoundException {
      collector = createSortingCollector(job, reporter);
      partitions = jobContext.getNumReduceTasks();
      if (partitions > 1) {            // 总分区数(也就是reducer数量)大于1的时候，引用自定义Partitioner
        partitioner = (org.apache.hadoop.mapreduce.Partitioner<K,V>)
          ReflectionUtils.newInstance(jobContext.getPartitionerClass(), job);
      } else {
        partitioner = new org.apache.hadoop.mapreduce.Partitioner<K,V>() {
          @Override
          public int getPartition(K key, V value, int numPartitions) {
            return partitions - 1;
          }
        };
      }
   }
}