@Override
public int run(String[] args) throws Exception {
addOption(
SEQ_FILE_DIR_OPTION, "s", "The directory containing Sequence Files for the Clusters", true);
addOption(
OUTPUT_OPTION, "o", "Optional output directory. Default is to output to the console.");
addOption(SUBSTRING_OPTION, "b", "The number of chars of the asFormatString() to print");
addOption(NUM_WORDS_OPTION, "n", "The number of top terms to print");
addOption(
JSON_OPTION,
"j",
"Output the centroid as JSON. Otherwise it substitues in the terms for vector cell entries");
addOption(
POINTS_DIR_OPTION,
"p",
"The directory containing points sequence files mapping input vectors to their cluster. "
+ "If specified, then the program will output the points associated with a cluster");
addOption(DICTIONARY_OPTION, "d", "The dictionary file");
addOption(DICTIONARY_TYPE_OPTION, "dt", "The dictionary file type (text|sequencefile)", "text");
if (parseArguments(args) == null) {
return -1;
}
seqFileDir = new Path(getOption(SEQ_FILE_DIR_OPTION));
if (hasOption(POINTS_DIR_OPTION)) {
pointsDir = new Path(getOption(POINTS_DIR_OPTION));
}
outputFile = getOption(OUTPUT_OPTION);
if (hasOption(SUBSTRING_OPTION)) {
int sub = Integer.parseInt(getOption(SUBSTRING_OPTION));
if (sub >= 0) {
subString = sub;
}
}
if (hasOption(JSON_OPTION)) {
useJSON = true;
}
termDictionary = getOption(DICTIONARY_OPTION);
dictionaryFormat = getOption(DICTIONARY_TYPE_OPTION);
if (hasOption(NUM_WORDS_OPTION)) {
numTopFeatures = Integer.parseInt(getOption(NUM_WORDS_OPTION));
}
init();
printClusters(null);
return 0;
}
/**
* Run the canopy clustering job on an input dataset using the given distance measure, t1 and t2
* parameters. All output data will be written to the output directory, which will be initially
* deleted if it exists. The clustered points will reside in the path <output>/clustered-points.
* By default, the job expects the a file containing synthetic_control.data as obtained from
* http://archive.ics.uci.edu/ml/datasets/Synthetic+Control+Chart+Time+Series resides in a
* directory named "testdata", and writes output to a directory named "output".
*
* @param input the String denoting the input directory path
* @param output the String denoting the output directory path
* @param measure the DistanceMeasure to use
* @param t1 the canopy T1 threshold
* @param t2 the canopy T2 threshold
*/
private static void run(Path input, Path output, DistanceMeasure measure, double t1, double t2)
throws Exception {
Path directoryContainingConvertedInput = new Path(output, DIRECTORY_CONTAINING_CONVERTED_INPUT);
InputDriver.runJob(
input,
directoryContainingConvertedInput,
"org.apache.mahout.math.RandomAccessSparseVector");
CanopyDriver.run(
new Configuration(),
directoryContainingConvertedInput,
output,
measure,
t1,
t2,
true,
0.0,
false);
// run ClusterDumper
ClusterDumper clusterDumper =
new ClusterDumper(
new Path(output, "clusters-0-final"), new Path(output, "clusteredPoints"));
clusterDumper.printClusters(null);
}
