Avro - Hadoop: The Definitive Guide - page 430

Sorting Using Avro MapReduce
In this section, we use Avro's sort capabilities and combine them with MapReduce to write
a program to sort an Avro datafile ( Example 12-3 ) .
Example 12-3. A MapReduce program to sort an Avro datafile
public class AvroSort extends Configured implements Tool {
static class SortMapper < K > extends Mapper < AvroKey < K >, NullWritable ,
AvroKey < K >, AvroValue < K >> {
@Override
protected void map ( AvroKey < K > key , NullWritable value ,
Context context ) throws IOException , InterruptedException {
context . write ( key , new AvroValue < K >( key . datum ()));
}
}
static class SortReducer < K > extends Reducer < AvroKey < K >, AvroValue < K >,
AvroKey < K >, NullWritable > {
@Override
protected void reduce ( AvroKey < K > key , Iterable < AvroValue < K >> values ,
Context context ) throws IOException , InterruptedException {
for ( AvroValue < K > value : values ) {
context . write ( new AvroKey ( value . datum ()), NullWritable . get ());
}
}
}
@Override
public int run ( String [] args ) throws Exception {
if ( args . length != 3 ) {
System . err . printf (
"Usage: %s [generic options] <input> <output> <schema-file>\n" ,
getClass (). getSimpleName ());
ToolRunner . printGenericCommandUsage ( System . err );
return - 1 ;
}
String input = args [ 0 ];
String output = args [ 1 ];
String schemaFile = args [ 2 ];
Job job = new Job ( getConf (), "Avro sort" );
job . setJarByClass ( getClass ());