Java tutorial
/* * avenir: Predictive analytic based on Hadoop Map Reduce * Author: Pranab Ghosh * * 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. */ package org.avenir.association; import java.io.IOException; import java.util.ArrayList; import java.util.List; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.NullWritable; 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.output.FileOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; import org.apache.log4j.Level; import org.apache.log4j.Logger; import org.chombo.util.SecondarySort; import org.chombo.util.Tuple; import org.chombo.util.Utility; /** * Association rule mining from frequent item sets * @author pranab * */ public class AssociationRuleMiner extends Configured implements Tool { private static final Logger LOG = Logger.getLogger(AssociationRuleMiner.class); @Override public int run(String[] args) throws Exception { Job job = new Job(getConf()); String jobName = "Association rule mining from frequent item sets"; job.setJobName(jobName); job.setJarByClass(AssociationRuleMiner.class); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); Utility.setConfiguration(job.getConfiguration(), "avenir"); job.setMapperClass(AssociationRuleMiner.RuleMinerMapper.class); job.setReducerClass(AssociationRuleMiner.RuleMinerReducer.class); job.setGroupingComparatorClass(SecondarySort.TuplePairGroupComprator.class); job.setPartitionerClass(SecondarySort.TuplePairPartitioner.class); job.setMapOutputKeyClass(Tuple.class); job.setMapOutputValueClass(Tuple.class); job.setOutputKeyClass(NullWritable.class); job.setOutputValueClass(Text.class); int numReducer = job.getConfiguration().getInt("arm.num.reducer", -1); numReducer = -1 == numReducer ? job.getConfiguration().getInt("num.reducer", 1) : numReducer; job.setNumReduceTasks(numReducer); int status = job.waitForCompletion(true) ? 0 : 1; return status; } /** * @author pranab * */ public static class RuleMinerMapper extends Mapper<LongWritable, Text, Tuple, Tuple> { private String fieldDelimRegex; private String[] items; private Tuple outKey = new Tuple(); private Tuple outVal = new Tuple(); private int maxAntecedentSize; private List<String> transItems = new ArrayList<String>();; private double support; /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Mapper#setup(org.apache.hadoop.mapreduce.Mapper.Context) */ protected void setup(Context context) throws IOException, InterruptedException { Configuration conf = context.getConfiguration(); if (conf.getBoolean("debug.on", false)) { LOG.setLevel(Level.DEBUG); } fieldDelimRegex = conf.get("field.delim.regex", ","); maxAntecedentSize = conf.getInt("arm.max.ante.size", 3); } /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Mapper#map(KEYIN, VALUEIN, org.apache.hadoop.mapreduce.Mapper.Context) */ protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { items = value.toString().split(fieldDelimRegex); transItems.clear(); ; for (int i = 0; i < items.length - 1; ++i) { transItems.add(items[i]); } //emit support outKey.initialize(); outVal.initialize(); outKey.add(transItems); outKey.add(Utility.ZERO); support = Double.parseDouble(items[items.length - 1]); outVal.add(support); context.write(outKey, outVal); //generate antecedent and consequent if (transItems.size() > 1) { //generate sub lists List<List<String>> subLists = Utility.generateSublists(transItems, maxAntecedentSize); for (List<String> subList : subLists) { outKey.initialize(); outVal.initialize(); //key ; antecedent outKey.add(subList); outKey.add(Utility.ONE); //value: consequent and support for whole item set List<String> diff = Utility.listDifference(transItems, subList); outVal.add(diff); outVal.add(support); context.write(outKey, outVal); } } } } /** * @author pranab * */ public static class RuleMinerReducer extends Reducer<Tuple, Tuple, NullWritable, Text> { private String fieldDelim; private Text outVal = new Text(); private double confidenceThreshold; private double confidence; private double totalSupport; private double anteSupport; /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Reducer#setup(org.apache.hadoop.mapreduce.Reducer.Context) */ protected void setup(Context context) throws IOException, InterruptedException { Configuration conf = context.getConfiguration(); if (conf.getBoolean("debug.on", false)) { LOG.setLevel(Level.DEBUG); } fieldDelim = conf.get("field.delim.out", ","); confidenceThreshold = Utility.assertDoubleConfigParam(conf, "arm.conf.threshold", "missing confidence threshold"); } /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Reducer#reduce(KEYIN, java.lang.Iterable, org.apache.hadoop.mapreduce.Reducer.Context) */ protected void reduce(Tuple key, Iterable<Tuple> values, Context context) throws IOException, InterruptedException { for (Tuple value : values) { if (key.getLastAsInt() == 0) { //antecedent support anteSupport = value.getDouble(0); } else { //consequents totalSupport = value.getLastAsDouble(); confidence = totalSupport / anteSupport; if (confidence > confidenceThreshold) { outVal.set(key.toString(0, key.getSize() - 1) + " -> " + value.toString(0, value.getSize() - 1)); context.write(NullWritable.get(), outVal); } } } } } public static void main(String[] args) throws Exception { int exitCode = ToolRunner.run(new AssociationRuleMiner(), args); System.exit(exitCode); } }