Package org.apache.avro.mapred

Run Hadoop MapReduce jobs over Avro data, with map and reduce functions written in Java.

See:
Description

Class Summary

AvroCollector<T>	A collector for map and reduce output.
AvroInputFormat<T>	An InputFormat for Avro data files
AvroJob	Setters to configure jobs for Avro data.
AvroKey<T>	The wrapper of keys for jobs configured with AvroJob .
AvroKeyComparator<T>	The RawComparator used by jobs configured with AvroJob.
AvroMapper<IN,OUT>	A mapper for Avro data.
AvroOutputFormat<T>	An OutputFormat for Avro data files.
AvroRecordReader<T>	An RecordReader for Avro data files.
AvroReducer<K,V,OUT>	A reducer for Avro data.
AvroSerialization<T>	The Serialization used by jobs configured with AvroJob.
AvroUtf8InputFormat	An InputFormat for text files.
AvroValue<T>	The wrapper of values for jobs configured with AvroJob .
AvroWrapper<T>	The wrapper of data for jobs configured with AvroJob .
FsInput	Adapt an FSDataInputStream to SeekableInput.
Pair<K,V>	A key/value pair.
SequenceFileInputFormat<K,V>	An InputFormat for sequence files.
SequenceFileReader<K,V>	A FileReader for sequence files.
SequenceFileRecordReader<K,V>	A RecordReader for sequence files.

Package org.apache.avro.mapred Description

Run Hadoop MapReduce jobs over Avro data, with map and reduce functions written in Java.

Avro data files do not contain key/value pairs as expected by Hadoop's MapReduce API, but rather just a sequence of values. Thus we provide here a layer on top of Hadoop's MapReduce API which eliminates the key/value distinction.

To use this for jobs whose input and output are Avro data files:

• Call AvroJob.setInputSchema(org.apache.hadoop.mapred.JobConf, org.apache.avro.Schema) and AvroJob.setOutputSchema(org.apache.hadoop.mapred.JobConf, org.apache.avro.Schema) with your job's input and output schemas.
• Subclass AvroMapper and specify this as your job's mapper with AvroJob.setMapperClass(org.apache.hadoop.mapred.JobConf, java.lang.Class)
• Subclass AvroReducer and specify this as your job's reducer and perhaps combiner, with AvroJob.setReducerClass(org.apache.hadoop.mapred.JobConf, java.lang.Class) and AvroJob.setCombinerClass(org.apache.hadoop.mapred.JobConf, java.lang.Class)
• Specify input files with FileInputFormat.setInputPaths(org.apache.hadoop.mapred.JobConf, java.lang.String)
• Specify an output directory with FileOutputFormat.setOutputPath(org.apache.hadoop.mapred.JobConf, org.apache.hadoop.fs.Path)
• Run your job with JobClient.runJob(org.apache.hadoop.mapred.JobConf)