Java tutorial
/* * Cloud9: A Hadoop toolkit for working with big data * * Licensed under the Apache License, Version 2.0 (the "License"); you * may not use this file except in compliance with the License. You may * obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or * implied. See the License for the specific language governing * permissions and limitations under the License. */ import java.io.IOException; import java.util.Iterator; import java.util.StringTokenizer; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.FloatWritable; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.Partitioner; import org.apache.hadoop.mapreduce.Reducer; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; import org.apache.log4j.Logger; import org.apache.pig.backend.executionengine.ExecException; import org.apache.pig.data.BinSedesTuple; import org.apache.pig.data.Tuple; import org.apache.pig.data.TupleFactory; public class BigramRelativeFrequencyTuple extends Configured implements Tool { private static final Logger LOG = Logger.getLogger(BigramRelativeFrequencyTuple.class); private static final TupleFactory TUPLE_FACTORY = TupleFactory.getInstance(); protected static class MyMapper extends Mapper<LongWritable, Text, Tuple, FloatWritable> { private static final FloatWritable ONE = new FloatWritable(1); @Override public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String line = value.toString(); String prev = null; StringTokenizer itr = new StringTokenizer(line); while (itr.hasMoreTokens()) { String cur = itr.nextToken(); // Emit only if we have an actual bigram. if (prev != null) { // Simple way to truncate tokens that are too long. if (cur.length() > 100) { cur = cur.substring(0, 100); } if (prev.length() > 100) { prev = prev.substring(0, 100); } Tuple tuple1 = TUPLE_FACTORY.newTuple(); tuple1.append(prev); tuple1.append(cur); context.write(tuple1, ONE); Tuple tuple2 = TUPLE_FACTORY.newTuple(); tuple2.append(prev); tuple2.append("*"); context.write(tuple2, ONE); } prev = cur; } } } protected static class MyCombiner extends Reducer<Tuple, FloatWritable, Tuple, FloatWritable> { private final static FloatWritable SUM = new FloatWritable(); @Override public void reduce(Tuple key, Iterable<FloatWritable> values, Context context) throws IOException, InterruptedException { int sum = 0; Iterator<FloatWritable> iter = values.iterator(); while (iter.hasNext()) { sum += iter.next().get(); } SUM.set(sum); context.write(key, SUM); } } protected static class MyReducer extends Reducer<Tuple, FloatWritable, Tuple, FloatWritable> { private static final FloatWritable VALUE = new FloatWritable(); private float marginal = 0.0f; @Override public void reduce(Tuple key, Iterable<FloatWritable> values, Context context) throws IOException, InterruptedException { float sum = 0.0f; Iterator<FloatWritable> iter = values.iterator(); while (iter.hasNext()) { sum += iter.next().get(); } if (key.get(1).equals("*")) { VALUE.set(sum); context.write(key, VALUE); marginal = sum; } else { VALUE.set(sum / marginal); context.write(key, VALUE); } } } protected static class MyPartitioner extends Partitioner<Tuple, FloatWritable> { @Override public int getPartition(Tuple key, FloatWritable value, int numReduceTasks) { try { return (((String) key.get(0)).hashCode() & Integer.MAX_VALUE) % numReduceTasks; } catch (ExecException e) { e.printStackTrace(); return 0; } } } private BigramRelativeFrequencyTuple() { } private static int printUsage() { System.out.println("usage: [input-path] [output-path] [num-reducers]"); ToolRunner.printGenericCommandUsage(System.out); return -1; } /** * Runs this tool. */ public int run(String[] args) throws Exception { if (args.length != 3) { printUsage(); return -1; } String inputPath = args[0]; String outputPath = args[1]; int reduceTasks = Integer.parseInt(args[2]); LOG.info("Tool name: " + BigramRelativeFrequencyTuple.class.getSimpleName()); LOG.info(" - input path: " + inputPath); LOG.info(" - output path: " + outputPath); LOG.info(" - num reducers: " + reduceTasks); Job job = Job.getInstance(getConf()); job.setJobName(BigramRelativeFrequencyTuple.class.getSimpleName()); job.setJarByClass(BigramRelativeFrequencyTuple.class); job.setNumReduceTasks(reduceTasks); FileInputFormat.setInputPaths(job, new Path(inputPath)); FileOutputFormat.setOutputPath(job, new Path(outputPath)); job.setMapOutputKeyClass(BinSedesTuple.class); job.setMapOutputValueClass(FloatWritable.class); job.setOutputKeyClass(BinSedesTuple.class); job.setOutputValueClass(FloatWritable.class); job.setOutputFormatClass(SequenceFileOutputFormat.class); job.setMapperClass(MyMapper.class); job.setCombinerClass(MyCombiner.class); job.setReducerClass(MyReducer.class); job.setPartitionerClass(MyPartitioner.class); // Delete the output directory if it exists already. Path outputDir = new Path(outputPath); FileSystem.get(getConf()).delete(outputDir, true); long startTime = System.currentTimeMillis(); job.waitForCompletion(true); System.out.println("Job Finished in " + (System.currentTimeMillis() - startTime) / 1000.0 + " seconds"); return 0; } /** * Dispatches command-line arguments to the tool via the {@code ToolRunner}. */ public static void main(String[] args) throws Exception { ToolRunner.run(new BigramRelativeFrequencyTuple(), args); } }