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.io.WritableComparable; 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 edu.umd.cloud9.io.JsonWritable; public class BigramRelativeFrequencyJson extends Configured implements Tool { private static final Logger LOG = Logger.getLogger(BigramRelativeFrequencyJson.class); // Define custom intermediate key; must specify sort order. public static class MyTuple extends JsonWritable implements WritableComparable<MyTuple> { public int compareTo(MyTuple that) { String thisLeft = this.getJsonObject().get("Left").getAsString(); String thatLeft = that.getJsonObject().get("Left").getAsString(); if (thisLeft.equals(thatLeft)) { String thisRight = this.getJsonObject().get("Right").getAsString(); String thatRight = that.getJsonObject().get("Right").getAsString(); return thisRight.compareTo(thatRight); } return thisLeft.compareTo(thatLeft); } } protected static class MyMapper extends Mapper<LongWritable, Text, MyTuple, FloatWritable> { private static final FloatWritable ONE = new FloatWritable(1); private static final MyTuple BIGRAM = new MyTuple(); @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); } BIGRAM.getJsonObject().addProperty("Left", prev); BIGRAM.getJsonObject().addProperty("Right", cur); context.write(BIGRAM, ONE); BIGRAM.getJsonObject().addProperty("Left", prev); BIGRAM.getJsonObject().addProperty("Right", "*"); context.write(BIGRAM, ONE); } prev = cur; } } } protected static class MyCombiner extends Reducer<MyTuple, FloatWritable, MyTuple, FloatWritable> { private final static FloatWritable SUM = new FloatWritable(); @Override public void reduce(MyTuple 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<MyTuple, FloatWritable, MyTuple, FloatWritable> { private static final FloatWritable VALUE = new FloatWritable(); private float marginal = 0.0f; @Override public void reduce(MyTuple 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.getJsonObject().get("Right").getAsString().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<MyTuple, FloatWritable> { @Override public int getPartition(MyTuple key, FloatWritable value, int numReduceTasks) { return (key.getJsonObject().get("Left").getAsString().hashCode() & Integer.MAX_VALUE) % numReduceTasks; } } private BigramRelativeFrequencyJson() { } 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: " + BigramRelativeFrequencyJson.class.getSimpleName()); LOG.info(" - input path: " + inputPath); LOG.info(" - output path: " + outputPath); LOG.info(" - num reducers: " + reduceTasks); Job job = Job.getInstance(getConf()); job.setJobName(BigramRelativeFrequencyJson.class.getSimpleName()); job.setJarByClass(BigramRelativeFrequencyJson.class); job.setNumReduceTasks(reduceTasks); FileInputFormat.setInputPaths(job, new Path(inputPath)); FileOutputFormat.setOutputPath(job, new Path(outputPath)); job.setMapOutputKeyClass(MyTuple.class); job.setMapOutputValueClass(FloatWritable.class); job.setOutputKeyClass(MyTuple.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 BigramRelativeFrequencyJson(), args); } }