public Values(String... strs) { super(strs.length); for (String s : strs) { add(s); } type = STRING; }
public Values(Integer... ints) { super(ints.length); for (Integer i : ints) { add(i); } type = INTEGER; }
public Values(Object... vals) { super(vals.length); for (Object o : vals) { add(o); } type = OBJECT; }
public Values(Object... vals) { super(vals.length); for(Object o: vals) { add(o); } } }
public Values(Integer... ints) { super(ints.length); for (Integer i : ints) { add(i); } type = INTEGER; }
public Values(Object... vals) { super(vals.length); for(Object o: vals) { add(o); } } }
public Values(Object... vals) { super(vals.length); for (Object o : vals) { add(o); } type = OBJECT; }
public Values(String... strs) { super(strs.length); for (String s : strs) { add(s); } type = STRING; }
public Values(Object... vals) { super(vals.length); for (Object o : vals) { add(o); } } }
@Override public void emitBatch(long batchId, TridentCollector collector) { for (int i = 0; i < this.maxBatchSize; i++) { Values values = new Values(); double[] features = new double[this.featureSize]; for (int j = 0; j < this.featureSize; j++) { features[j] = j + this.random.nextGaussian() * this.variance; } if (this.withLabel) { values.add(FEATURES_TO_LABEL.apply(features)); } for (double feature : features) { values.add(feature); } collector.emit(values); } }
@Override public void emitBatch(long batchId, TridentCollector collector) { List<Instance<Integer>> instances = Datasets.generateDataForMultiLabelClassification(this.maxBatchSize, this.featureSize, this.nbClasses); Values values; for (Instance<Integer> instance : instances) { values = new Values(); if (this.withLabel) { values.add(instance.label); } for (int i = 0; i < instance.features.length; i++) { values.add(instance.features[i]); } collector.emit(values); } }
private Values generate() { final Values ret = new Values(); for (final Uniform r : this.randomGenerators) { ret.add(r.nextIntFromTo(min, max)); } return ret; }
private Values generate() { final Values ret = new Values(); for (final Uniform r : this.randomGenerators) { ret.add(r.nextIntFromTo(min, max)); } return ret; }
values.add(new MetaMsg().topic(RaceConfig.PAY).body(msg.getBody())); }else if(msg.getTopic().equals(RaceConfig.MqTaobaoTradeTopic)){ values.add(new MetaMsg().topic(RaceConfig.TBORDER).body(msg.getBody())); }else if(msg.getTopic().equals(RaceConfig.MqTmallTradeTopic)){ values.add(new MetaMsg().topic(RaceConfig.TMORDER).body(msg.getBody())); }else { LOG.info("unknown topic:{}",msg.getTopic());
output.getMessage().add(0);