Map Reduce Median

https://www.quora.com/Is-there-a-fast-algorithm-to-run-on-the-MapReduce-framework-to-find-the-median-from-a-huge-integer-set
You could use MapReduce to sort the data and then some postprocessing outside of the MapReduce framework to find the median in the sorted data.  
This isn't asymptotically optimal - it's O(nlogn).

http://www.1point3acres.com/bbs/thread-14930-1-1.html
http://stackoverflow.com/questions/10109514/computing-median-in-map-reduce
Related:
https://github.com/rajdeepd/hadoop-samples
public class MedianTemperatureMapper extends Mapper<LongWritable, Text, Text, IntWritable> {

          private Text yearText = new Text();
          private final static IntWritable tempWritable = new IntWritable(0);

          protected void map(LongWritable key, Text value, Context context)
              throws java.io.IOException, InterruptedException {
        String[] line = value.toString().split(";");
            String year = line[0];
            yearText.set(year);
            int temp = Integer.parseInt(line[1]);
            tempWritable.set(temp);
            context.write(yearText,tempWritable);
          }
}              
public class MedianTemperatureReducer extends
        Reducer<Text, IntWritable, Text, IntWritable> {
        ArrayList<Integer> temperatureList = new ArrayList<Integer>();
       
        protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws java.io.IOException, InterruptedException {
                int median = 0;
                for (IntWritable value : values) {
                        temperatureList.add(value.get());
                }
                Collections.sort(temperatureList);
                int size  = temperatureList.size();

                if(size%2 == 0){
                        int half = size/2;

                        median  = temperatureList.get(half);
                }else {
                        int half = (size + 1)/2;
                        median = temperatureList.get(half -1);
                }
                context.write(key, new IntWritable(median));
        }

}