@Override
public int execute(Configuration conf) throws IOException {
Pipeline p = pipelineParams.create(KMeansSketchCommand.class, conf);
List<Vector> initial = null;
if (initVectorsPath != null) {
initial = getInitialVectors(p);
}
PCollection<Vector> input = inputParams.getVectors(p);
if (initial == null || initial.isEmpty()) {
initial = Lists.newArrayList();
initial.add(input.materialize().iterator().next());
}
KMeansParallel kmp = new KMeansParallel(randomParams.getRandom(), indexBits, indexSamples);
Crossfold cf = new Crossfold(crossFolds);
List<List<Weighted<Vector>>> wv =
kmp.initialization(input, numIterations, samplesPerIteration, initial, cf);
AvroIO.write(toWeightedCenters(wv), new File(outputFile));
p.done();
return 0;
}
@Override
public int execute(Configuration conf) throws Exception {
Pipeline p = pipelineParams.create(SampleCommand.class, conf);
PCollection<Record> elements = inputParams.getRecords(p);
if (sampleSize > 0 && samplingProbability > 0.0) {
throw new IllegalArgumentException("--size and --prob are mutually exclusive options.");
}
PCollection<Record> sample;
if (sampleSize > 0) {
sample = ReservoirSampling.sample(elements, sampleSize);
} else if (samplingProbability > 0.0 && samplingProbability < 1.0) {
sample = Sample.sample(elements, samplingProbability);
} else {
throw new IllegalArgumentException(
String.format(
"Invalid input args: sample size = %d, sample prob = %.4f",
sampleSize, samplingProbability));
}
outputParams.write(sample, sampleFile);
PipelineResult pr = p.done();
return pr.succeeded() ? 0 : 1;
}
@Override
public int execute(Configuration conf) throws Exception {
Pipeline p = pipelineParams.create(SummaryCommand.class, conf);
PCollection<Record> records = inputParams.getRecords(p);
Spec spec = null;
List<Integer> symbolicColumns = Lists.newArrayList();
List<Integer> ignoredColumns = Lists.newArrayList();
if (headerFile != null) {
spec = Specs.readFromHeaderFile(headerFile, ignoredColumns, symbolicColumns);
}
Summarizer summarizer =
new Summarizer()
.spec(spec)
.defaultToSymbolic(false)
.exceptionColumns(symbolicColumns)
.ignoreColumns(ignoredColumns);
Summary summary = summarizer.build(records).getValue();
summaryParams.save(summary, summaryFile);
p.done();
return 0;
}