Java tutorial
package csc555.ebratt.depaul.edu; /* Copyright (c) 2015 Eric Bratt Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. The Software shall be used for Good, not Evil. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ import java.io.IOException; import java.util.Iterator; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; 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.Reducer; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; /** * VoteSorterDriver is the hadoop class that drives the program. It counts and * sorts (descending) the number of votes by author, subreddit, all, etc. * * @author Eric Bratt * @version 11/11/2015 * @since 11/11/2015 * */ public class VoteSorterDriver extends Configured implements Tool { /** * VoteSorterMapper is the hadoop class that maps the input. * * @author Eric Bratt * @version 11/11/2015 * @since 11/11/2015 * */ public static class VoteSorterMapper extends Mapper<LongWritable, Text, LongWritable, Text> { // instance variables for heap size reduction private LongWritable outKey = new LongWritable(); private Text outValue = new Text(); // Default constructor for inner-class public VoteSorterMapper() { }; /** * Parses the input values and emits the percentage followed by the key * * <p> * <b>Preconditions:</b> * <ul> * <li>the input values must be separated by new line character * <li>the input value k,v must be delimited by tab character * </ul> * * <p> * <b>Postconditions:</b> * <ul> * <li>emits (by example) "3500 reddit.com" * </ul> * * @param key * the byte offset as * {@link org.apache.hadoop.io.LongWritable} * @param value * the input as {@link org.apache.hadoop.io.Text} * @param context * the {@link org.apache.hadoop.mapreduce.Mapper.Context} * @throws IOException * if there is an issue with input/output (like network * connection was lost during processing, ran out of space * trying to write, etc.) * @throws InterruptedException * if something calls interrupt() on the thread. * */ public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException, ArrayIndexOutOfBoundsException { // a line in the input String[] line = value.toString().split("\\n"); // loop over the lines for (String t : line) { // attempt to parse the percent gilded long votes = Long.valueOf(t.split("\\t")[1]); String groupBy = t.split("\\t")[0]; outKey.set(votes); outValue.set(groupBy); context.write(outKey, outValue); } } } /** * VoteSorterReducer is the hadoop class that reduces the output of the * VoteSorterMapper. It will emit the gild count along with the group. * * @author Eric Bratt * @version 11/11/2015 * @since 11/11/2015 * */ public static class VoteSorterReducer extends Reducer<LongWritable, Text, LongWritable, Text> { // Default constructor for inner-class public VoteSorterReducer() { }; /** * * Just emits the top 10 since they're already sorted * * @param key * the key from the mapper * {@link org.apache.hadoop.io.LongWritable} * @param values * a list of {@link org.apache.hadoop.io.Text} * @param context * the {@link org.apache.hadoop.mapreduce.Mapper.Context} * @throws IOException * if there is an issue with input/output (like network * connection was lost during processing, ran out of space * trying to write, etc.) * @throws InterruptedException * if something calls interrupt() on the thread. * */ public void reduce(LongWritable key, Iterable<Text> values, Context context) throws IOException, InterruptedException { Iterator<Text> itr = values.iterator(); while (itr.hasNext()) { context.write(key, itr.next()); } } } /** * * Runs the driver by creating a new hadoop Job based on the configuration. * Defines the path in/out based on the first two arguments. Allows for an * optional combiner based on the 4th argument. * * @param args * [0] the input directory on HDFS * @param args * [1] the output directory on HDFS * @param args * [2] tells the system whether or not to use a combiner ("yes") * and, if so, it will use the VoteSorterReducer.class as the * combiner. * @throws Exception * if there is an issue with any of the arguments * */ @Override public int run(String[] args) throws Exception { Job job = new Job(getConf()); StringBuffer sb = new StringBuffer(); sb.append("sorted vote counts"); job.setJobName(sb.toString()); Path in = new Path(args[0]); Path out = new Path(args[1]); FileInputFormat.setInputPaths(job, in); FileOutputFormat.setOutputPath(job, out); // to ensure output is sorted job.setNumReduceTasks(1); // Mapper and Reducer Classes to use job.setMapperClass(VoteSorterMapper.class); job.setReducerClass(VoteSorterReducer.class); // Mapper output classes job.setMapOutputKeyClass(LongWritable.class); job.setMapOutputValueClass(Text.class); // Input format class job.setInputFormatClass(TextInputFormat.class); // Reducer output classes job.setOutputKeyClass(LongWritable.class); job.setOutputValueClass(Text.class); // Output format class job.setOutputFormatClass(TextOutputFormat.class); // Combiner if (args[2].equals("yes")) { job.setCombinerClass(VoteSorterReducer.class); } // sort in descending order job.setSortComparatorClass(LongWritable.DecreasingComparator.class); // The Jar file to run job.setJarByClass(VoteSorterDriver.class); boolean success = job.waitForCompletion(true); System.exit(success ? 0 : 1); return 0; }; /** * * This is the entry point to the program. It creates a new Configuration, * checks the arguments, deletes the output directory on HDFS (if it already * exists), sets the configuration properties 'aggregate' and 'groupBy', * tells hadoop that it wants to compress the mapper output but not the * reducer output, and runs the job. * * @param args * [0] the input directory on HDFS * @param args * [1] the output directory on HDFS * @param args * [2] the combiner flag * @throws Exception * if there is an issue with any of the arguments * */ public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); if (args.length != 3) { System.err.println("Usage: VoteSorter.jar <in> <out> <combiner? yes/no>"); System.exit(2); } Path out = new Path(args[1]); FileSystem hdfs = FileSystem.get(conf); if (hdfs.exists(out)) { hdfs.delete(out, true); } // Enable mapper output compression, but not reducer conf.set("mapreduce.map.output.compress", "true"); conf.set("mapreduce.output.fileoutputformat.compress", "false"); int res = ToolRunner.run(conf, new VoteSorterDriver(), args); System.exit(res); } }