Java tutorial
/* * Sifarish: Recommendation Engine * 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.sifarish.common; 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.input.FileSplit; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; import org.chombo.util.SecondarySort; import org.chombo.util.Tuple; import org.chombo.util.Utility; /** * Aggregates item predicted rating and attribute aggregator. Used by attribute bases diversifier * @author pranab * */ public class ItemRatingAttributeAggregator extends Configured implements Tool { @Override public int run(String[] args) throws Exception { Job job = new Job(getConf()); String jobName = "Item predicted rating and attribute aggregator MR"; job.setJobName(jobName); job.setJarByClass(ItemRatingAttributeAggregator.class); FileInputFormat.addInputPaths(job, args[0]); FileOutputFormat.setOutputPath(job, new Path(args[1])); job.setMapperClass(ItemRatingAttributeAggregator.ItemAggregatorMapper.class); job.setReducerClass(ItemRatingAttributeAggregator.ItemAggregatorReducer.class); job.setMapOutputKeyClass(Tuple.class); job.setMapOutputValueClass(Tuple.class); job.setOutputKeyClass(NullWritable.class); job.setOutputValueClass(Text.class); job.setGroupingComparatorClass(SecondarySort.TuplePairGroupComprator.class); job.setPartitionerClass(SecondarySort.TuplePairPartitioner.class); Utility.setConfiguration(job.getConfiguration()); int numReducer = job.getConfiguration().getInt("iraa.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 ItemAggregatorMapper extends Mapper<LongWritable, Text, Tuple, Tuple> { private String fieldDelimRegex; private Tuple keyOut = new Tuple(); private Tuple valOut = new Tuple(); private boolean isMetaDataFileSplit; private String itemID; private int[] attrOrdinals; /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Mapper#setup(org.apache.hadoop.mapreduce.Mapper.Context) */ protected void setup(Context context) throws IOException, InterruptedException { Configuration config = context.getConfiguration(); fieldDelimRegex = config.get("field.delim.regex", ","); String metaDataFilePrefix = config.get("item.metadta.file.prefix", "meta"); isMetaDataFileSplit = ((FileSplit) context.getInputSplit()).getPath().getName() .startsWith(metaDataFilePrefix); if (null != config.get("item.attr.ordinals")) { attrOrdinals = Utility.intArrayFromString(config.get("item.attr.ordinals")); } } /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Mapper#map(KEYIN, VALUEIN, org.apache.hadoop.mapreduce.Mapper.Context) */ @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String[] items = value.toString().split(fieldDelimRegex); keyOut.initialize(); valOut.initialize(); if (isMetaDataFileSplit) { //items attributes itemID = items[0]; keyOut.add(itemID, 1); valOut.append(1); if (null != attrOrdinals) { //selected attributes for (int ordinal : attrOrdinals) { valOut.append(items[ordinal]); } } else { //all attributes for (int i = 1; i < items.length; ++i) { valOut.append(items[i]); } } } else { //predicted rating itemID = items[1]; keyOut.add(itemID, 0); valOut.add(0, items[0], items[2]); } context.write(keyOut, valOut); } } /** * @author pranab * */ public static class ItemAggregatorReducer extends Reducer<Tuple, Tuple, NullWritable, Text> { private String fieldDelim; private Text valOut = new Text(); private List<String> users = new ArrayList<String>(); private List<Integer> ratings = new ArrayList<Integer>(); private String itemID; private StringBuilder stBld = new StringBuilder(); private boolean outputRating; /* (non-Javadoc) * @see org.apache.hadoop.mapreduce.Reducer#setup(org.apache.hadoop.mapreduce.Reducer.Context) */ protected void setup(Context context) throws IOException, InterruptedException { Configuration config = context.getConfiguration(); fieldDelim = config.get("field.delim", ","); outputRating = config.getBoolean("output.rating", false); } /* (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 { users.clear(); if (outputRating) { ratings.clear(); } itemID = key.getString(0); for (Tuple value : values) { int type = value.getInt(0); if (0 == type) { //users for which this item has predicted ratings users.add(value.getString(1)); if (outputRating) { ratings.add(value.getInt(2)); } } else { //item attributes String attrs = value.toString(1); int i = 0; for (String user : users) { stBld.delete(0, stBld.length()); stBld.append(user).append(fieldDelim).append(itemID).append(fieldDelim).append(attrs); if (outputRating) { stBld.append(fieldDelim).append(ratings.get(i++)); } valOut.set(stBld.toString()); //userID, itemID, item attribute, ...,..,[rating] context.write(NullWritable.get(), valOut); } } } } } /** * @param args * @throws Exception */ public static void main(String[] args) throws Exception { int exitCode = ToolRunner.run(new ItemRatingAttributeAggregator(), args); System.exit(exitCode); } }