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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;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.util.ToolRunner;
import org.apache.lucene.analysis.Analyzer;
import org.apache.mahout.common.AbstractJob;
import org.apache.mahout.common.ClassUtils;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.commandline.DefaultOptionCreator;
import org.apache.mahout.vectorizer.encoders.FeatureVectorEncoder;
import org.apache.mahout.vectorizer.encoders.LuceneTextValueEncoder;
/**
* Converts a given set of sequence files into SparseVectors
*/
public final class EncodedVectorsFromSequenceFiles extends AbstractJob {
public static void main(String[] args) throws Exception {
ToolRunner.run(new Configuration(), new EncodedVectorsFromSequenceFiles(), args);
}
@Override
public int run(String[] args) throws Exception {
addInputOption();
addOutputOption();
addOption(DefaultOptionCreator.analyzerOption().create());
addOption(buildOption("sequentialAccessVector", "seq",
"(Optional) Whether output vectors should be SequentialAccessVectors. "
+ "If set true else false",
false, false, null));
addOption(buildOption("namedVector", "nv",
"Create named vectors using the key. False by default", false, false, null));
addOption("cardinality", "c",
"The cardinality to use for creating the vectors. Default is 5000", "5000");
addOption("encoderFieldName", "en",
"The name of the encoder to be passed to the FeatureVectorEncoder constructor. Default is text. "
+ "Note this is not the class name of a FeatureValueEncoder, but is instead the construction "
+ "argument.",
"text");
addOption("encoderClass", "ec",
"The class name of the encoder to be used. Default is " + LuceneTextValueEncoder.class.getName(),
LuceneTextValueEncoder.class.getName());
addOption(DefaultOptionCreator.overwriteOption().create());
if (parseArguments(args) == null) {
return -1;
}
Path input = getInputPath();
Path output = getOutputPath();
if (hasOption(DefaultOptionCreator.OVERWRITE_OPTION)) {
HadoopUtil.delete(getConf(), output);
}
Class extends Analyzer> analyzerClass = getAnalyzerClassFromOption();
Configuration conf = getConf();
boolean sequentialAccessOutput = hasOption("sequentialAccessVector");
boolean namedVectors = hasOption("namedVector");
int cardinality = 5000;
if (hasOption("cardinality")) {
cardinality = Integer.parseInt(getOption("cardinality"));
}
String encoderName = "text";
if (hasOption("encoderFieldName")) {
encoderName = getOption("encoderFieldName");
}
String encoderClass = LuceneTextValueEncoder.class.getName();
if (hasOption("encoderClass")) {
encoderClass = getOption("encoderClass");
ClassUtils.instantiateAs(encoderClass, FeatureVectorEncoder.class, new Class[] { String.class },
new Object[] { encoderName }); //try instantiating it
}
SimpleTextEncodingVectorizer vectorizer = new SimpleTextEncodingVectorizer();
VectorizerConfig config = new VectorizerConfig(conf, analyzerClass.getName(), encoderClass, encoderName,
sequentialAccessOutput, namedVectors, cardinality);
vectorizer.createVectors(input, output, config);
return 0;
}
}
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