The MultipleOutputs class simplifies writing output data
to multiple outputs
Case one: writing to additional outputs other than the job default output.
Each additional output, or named output, may be configured with its own
OutputFormat, with its own key class and with its own value
class.
Case two: to write data to different files provided by user
MultipleOutputs supports counters, by default they are disabled. The
counters group is the MultipleOutputs class name. The names of the
counters are the same as the output name. These count the number records
written to each output name.
Usage pattern for job submission:
Job job = new Job();
FileInputFormat.setInputPath(job, inDir);
FileOutputFormat.setOutputPath(job, outDir);
job.setMapperClass(MOMap.class);
job.setReducerClass(MOReduce.class);
...
// Defines additional single text based output 'text' for the job
MultipleOutputs.addNamedOutput(job, "text", TextOutputFormat.class,
LongWritable.class, Text.class);
// Defines additional sequence-file based output 'sequence' for the job
MultipleOutputs.addNamedOutput(job, "seq",
SequenceFileOutputFormat.class,
LongWritable.class, Text.class);
...
job.waitForCompletion(true);
...
Usage in Reducer:
String generateFileName(K k, V v) {
return k.toString() + "_" + v.toString();
}
public class MOReduce extends
Reducer<WritableComparable, Writable,WritableComparable, Writable> {
private MultipleOutputs mos;
public void setup(Context context) {
...
mos = new MultipleOutputs(context);
}
public void reduce(WritableComparable key, Iterator<Writable> values,
Context context)
throws IOException {
...
mos.write("text", , key, new Text("Hello"));
mos.write("seq", LongWritable(1), new Text("Bye"), "seq_a");
mos.write("seq", LongWritable(2), key, new Text("Chau"), "seq_b");
mos.write(key, new Text("value"), generateFileName(key, new Text("value")));
...
}
public void cleanup(Context) throws IOException {
mos.close();
...
}
}
When used in conjuction with org.apache.hadoop.mapreduce.lib.output.LazyOutputFormat,
MultipleOutputs can mimic the behaviour of MultipleTextOutputFormat and MultipleSequenceFileOutputFormat
from the old Hadoop API - ie, output can be written from the Reducer to more than one location.
Use MultipleOutputs.write(KEYOUT key, VALUEOUT value, String baseOutputPath) to write key and
value to a path specified by baseOutputPath, with no need to specify a named output:
private MultipleOutputs out;
public void setup(Context context) {
out = new MultipleOutputs(context);
...
}
public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException {
for (Text t : values) {
out.write(key, t, generateFileName(<parameter list...>));
}
}
protected void cleanup(Context context) throws IOException, InterruptedException {
out.close();
}
Use your own code in generateFileName() to create a custom path to your results.
'/' characters in baseOutputPath will be translated into directory levels in your file system.
Also, append your custom-generated path with "part" or similar, otherwise your output will be -00000, -00001 etc.
No call to context.write() is necessary. See example generateFileName() code below.
private String generateFileName(Text k) {
// expect Text k in format "Surname|Forename"
String[] kStr = k.toString().split("\\|");
String sName = kStr[0];
String fName = kStr[1];
// example for k = Smith|John
// output written to /user/hadoop/path/to/output/Smith/John-r-00000 (etc)
return sName + "/" + fName;
}
Using MultipleOutputs in this way will still create zero-sized default output, eg part-00000.
To prevent this use LazyOutputFormat.setOutputFormatClass(job, TextOutputFormat.class);
instead of job.setOutputFormatClass(TextOutputFormat.class); in your Hadoop job configuration.