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/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.apache.mahout.vectorizer.collocations.llr;
import java.io.IOException;
import java.util.List;
import java.util.Map;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
import org.apache.hadoop.util.ToolRunner;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.mahout.common.AbstractJob;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.commandline.DefaultOptionCreator;
import org.apache.mahout.common.lucene.AnalyzerUtils;
import org.apache.mahout.vectorizer.DocumentProcessor;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/** Driver for LLR Collocation discovery mapreduce job */
public final class CollocDriver extends AbstractJob {
//public static final String DEFAULT_OUTPUT_DIRECTORY = "output";
public static final String SUBGRAM_OUTPUT_DIRECTORY = "subgrams";
public static final String NGRAM_OUTPUT_DIRECTORY = "ngrams";
public static final String EMIT_UNIGRAMS = "emit-unigrams";
public static final boolean DEFAULT_EMIT_UNIGRAMS = false;
private static final int DEFAULT_MAX_NGRAM_SIZE = 2;
private static final int DEFAULT_PASS1_NUM_REDUCE_TASKS = 1;
private static final Logger log = LoggerFactory.getLogger(CollocDriver.class);
public static void main(String[] args) throws Exception {
ToolRunner.run(new CollocDriver(), args);
}
@Override
public int run(String[] args) throws Exception {
addInputOption();
addOutputOption();
addOption(DefaultOptionCreator.numReducersOption().create());
addOption("maxNGramSize",
"ng",
"(Optional) The max size of ngrams to create (2 = bigrams, 3 = trigrams, etc) default: 2",
String.valueOf(DEFAULT_MAX_NGRAM_SIZE));
addOption("minSupport", "s", "(Optional) Minimum Support. Default Value: "
+ CollocReducer.DEFAULT_MIN_SUPPORT, String.valueOf(CollocReducer.DEFAULT_MIN_SUPPORT));
addOption("minLLR", "ml", "(Optional)The minimum Log Likelihood Ratio(Float) Default is "
+ LLRReducer.DEFAULT_MIN_LLR, String.valueOf(LLRReducer.DEFAULT_MIN_LLR));
addOption(DefaultOptionCreator.overwriteOption().create());
addOption("analyzerName", "a", "The class name of the analyzer to use for preprocessing", null);
addFlag("preprocess", "p", "If set, input is SequenceFile where the value is the document, "
+ " which will be tokenized using the specified analyzer.");
addFlag("unigram", "u", "If set, unigrams will be emitted in the final output alongside collocations");
Map> argMap = parseArguments(args);
if (argMap == null) {
return -1;
}
Path input = getInputPath();
Path output = getOutputPath();
int maxNGramSize = DEFAULT_MAX_NGRAM_SIZE;
if (hasOption("maxNGramSize")) {
try {
maxNGramSize = Integer.parseInt(getOption("maxNGramSize"));
} catch (NumberFormatException ex) {
log.warn("Could not parse ngram size option");
}
}
log.info("Maximum n-gram size is: {}", maxNGramSize);
if (hasOption(DefaultOptionCreator.OVERWRITE_OPTION)) {
HadoopUtil.delete(getConf(), output);
}
int minSupport = CollocReducer.DEFAULT_MIN_SUPPORT;
if (getOption("minSupport") != null) {
minSupport = Integer.parseInt(getOption("minSupport"));
}
log.info("Minimum Support value: {}", minSupport);
float minLLRValue = LLRReducer.DEFAULT_MIN_LLR;
if (getOption("minLLR") != null) {
minLLRValue = Float.parseFloat(getOption("minLLR"));
}
log.info("Minimum LLR value: {}", minLLRValue);
int reduceTasks = DEFAULT_PASS1_NUM_REDUCE_TASKS;
if (getOption("maxRed") != null) {
reduceTasks = Integer.parseInt(getOption("maxRed"));
}
log.info("Number of pass1 reduce tasks: {}", reduceTasks);
boolean emitUnigrams = argMap.containsKey("emitUnigrams");
if (argMap.containsKey("preprocess")) {
log.info("Input will be preprocessed");
Class analyzerClass = StandardAnalyzer.class;
if (getOption("analyzerName") != null) {
String className = getOption("analyzerName");
analyzerClass = Class.forName(className).asSubclass(Analyzer.class);
// try instantiating it, b/c there isn't any point in setting it if
// you can't instantiate it
AnalyzerUtils.createAnalyzer(analyzerClass);
}
Path tokenizedPath = new Path(output, DocumentProcessor.TOKENIZED_DOCUMENT_OUTPUT_FOLDER);
DocumentProcessor.tokenizeDocuments(input, analyzerClass, tokenizedPath, getConf());
input = tokenizedPath;
} else {
log.info("Input will NOT be preprocessed");
}
// parse input and extract collocations
long ngramCount =
generateCollocations(input, output, getConf(), emitUnigrams, maxNGramSize, reduceTasks, minSupport);
// tally collocations and perform LLR calculation
computeNGramsPruneByLLR(output, getConf(), ngramCount, emitUnigrams, minLLRValue, reduceTasks);
return 0;
}
/**
* Generate all ngrams for the {@link org.apache.mahout.vectorizer.DictionaryVectorizer} job
*
* @param input
* input path containing tokenized documents
* @param output
* output path where ngrams are generated including unigrams
* @param baseConf
* job configuration
* @param maxNGramSize
* minValue = 2.
* @param minSupport
* minimum support to prune ngrams including unigrams
* @param minLLRValue
* minimum threshold to prune ngrams
* @param reduceTasks
* number of reducers used
*/
public static void generateAllGrams(Path input,
Path output,
Configuration baseConf,
int maxNGramSize,
int minSupport,
float minLLRValue,
int reduceTasks)
throws IOException, InterruptedException, ClassNotFoundException {
// parse input and extract collocations
long ngramCount = generateCollocations(input, output, baseConf, true, maxNGramSize, reduceTasks, minSupport);
// tally collocations and perform LLR calculation
computeNGramsPruneByLLR(output, baseConf, ngramCount, true, minLLRValue, reduceTasks);
}
/**
* pass1: generate collocations, ngrams
*/
private static long generateCollocations(Path input,
Path output,
Configuration baseConf,
boolean emitUnigrams,
int maxNGramSize,
int reduceTasks,
int minSupport)
throws IOException, ClassNotFoundException, InterruptedException {
Configuration con = new Configuration(baseConf);
con.setBoolean(EMIT_UNIGRAMS, emitUnigrams);
con.setInt(CollocMapper.MAX_SHINGLE_SIZE, maxNGramSize);
con.setInt(CollocReducer.MIN_SUPPORT, minSupport);
Job job = new Job(con);
job.setJobName(CollocDriver.class.getSimpleName() + ".generateCollocations:" + input);
job.setJarByClass(CollocDriver.class);
job.setMapOutputKeyClass(GramKey.class);
job.setMapOutputValueClass(Gram.class);
job.setPartitionerClass(GramKeyPartitioner.class);
job.setGroupingComparatorClass(GramKeyGroupComparator.class);
job.setOutputKeyClass(Gram.class);
job.setOutputValueClass(Gram.class);
job.setCombinerClass(CollocCombiner.class);
FileInputFormat.setInputPaths(job, input);
Path outputPath = new Path(output, SUBGRAM_OUTPUT_DIRECTORY);
FileOutputFormat.setOutputPath(job, outputPath);
job.setInputFormatClass(SequenceFileInputFormat.class);
job.setMapperClass(CollocMapper.class);
job.setOutputFormatClass(SequenceFileOutputFormat.class);
job.setReducerClass(CollocReducer.class);
job.setNumReduceTasks(reduceTasks);
boolean succeeded = job.waitForCompletion(true);
if (!succeeded) {
throw new IllegalStateException("Job failed!");
}
return job.getCounters().findCounter(CollocMapper.Count.NGRAM_TOTAL).getValue();
}
/**
* pass2: perform the LLR calculation
*/
private static void computeNGramsPruneByLLR(Path output,
Configuration baseConf,
long nGramTotal,
boolean emitUnigrams,
float minLLRValue,
int reduceTasks)
throws IOException, InterruptedException, ClassNotFoundException {
Configuration conf = new Configuration(baseConf);
conf.setLong(LLRReducer.NGRAM_TOTAL, nGramTotal);
conf.setBoolean(EMIT_UNIGRAMS, emitUnigrams);
conf.setFloat(LLRReducer.MIN_LLR, minLLRValue);
Job job = new Job(conf);
job.setJobName(CollocDriver.class.getSimpleName() + ".computeNGrams: " + output);
job.setJarByClass(CollocDriver.class);
job.setMapOutputKeyClass(Gram.class);
job.setMapOutputValueClass(Gram.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(DoubleWritable.class);
FileInputFormat.setInputPaths(job, new Path(output, SUBGRAM_OUTPUT_DIRECTORY));
Path outPath = new Path(output, NGRAM_OUTPUT_DIRECTORY);
FileOutputFormat.setOutputPath(job, outPath);
job.setMapperClass(Mapper.class);
job.setInputFormatClass(SequenceFileInputFormat.class);
job.setOutputFormatClass(SequenceFileOutputFormat.class);
job.setReducerClass(LLRReducer.class);
job.setNumReduceTasks(reduceTasks);
boolean succeeded = job.waitForCompletion(true);
if (!succeeded) {
throw new IllegalStateException("Job failed!");
}
}
}
