1.One of the simplest example of Iterative Mapreduce is K-Means Clustering.
We have the same input which is mapped into clusters then the output from mapper is used for making new clusters.
2. Identity Mappers and Reducers don't have a body, it only generates key-value pairs and the package is org.apache.hadoop.mapred.identity.
Identity Mapper and Reducer just like the concept of Identity function in mathematics i.e. do not transform the input and return it as it is in output form
An identity mapper is used can be used (among others!) if you would only want to sort your input.
Identity reducer is a bit different. It does not mean that the reduce step will not take place. It will take place and the related sorting/shuffling will also be performed but there will be no aggregation.
Hope this helps