Java tutorial
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See the License for the * specific language governing permissions and limitations * under the License. */ package org.elasticsearch.search.aggregations.reducers.movavg; import com.google.common.base.Function; import com.google.common.collect.EvictingQueue; import com.google.common.collect.Lists; import org.elasticsearch.common.Nullable; import org.elasticsearch.common.io.stream.StreamInput; import org.elasticsearch.common.io.stream.StreamOutput; import org.elasticsearch.search.aggregations.Aggregation; import org.elasticsearch.search.aggregations.AggregationExecutionException; import org.elasticsearch.search.aggregations.AggregatorFactory; import org.elasticsearch.search.aggregations.InternalAggregation; import org.elasticsearch.search.aggregations.InternalAggregation.ReduceContext; import org.elasticsearch.search.aggregations.InternalAggregation.Type; import org.elasticsearch.search.aggregations.InternalAggregations; import org.elasticsearch.search.aggregations.bucket.histogram.HistogramAggregator; import org.elasticsearch.search.aggregations.bucket.histogram.InternalHistogram; import org.elasticsearch.search.aggregations.reducers.BucketHelpers.GapPolicy; import org.elasticsearch.search.aggregations.reducers.InternalSimpleValue; import org.elasticsearch.search.aggregations.reducers.Reducer; import org.elasticsearch.search.aggregations.reducers.ReducerFactory; import org.elasticsearch.search.aggregations.reducers.ReducerStreams; import org.elasticsearch.search.aggregations.reducers.movavg.models.MovAvgModel; import org.elasticsearch.search.aggregations.reducers.movavg.models.MovAvgModelStreams; import org.elasticsearch.search.aggregations.support.format.ValueFormatter; import org.elasticsearch.search.aggregations.support.format.ValueFormatterStreams; import org.joda.time.DateTime; import java.io.IOException; import java.util.ArrayList; import java.util.List; import java.util.Map; import static org.elasticsearch.search.aggregations.reducers.BucketHelpers.resolveBucketValue; public class MovAvgReducer extends Reducer { public final static Type TYPE = new Type("moving_avg"); public final static ReducerStreams.Stream STREAM = new ReducerStreams.Stream() { @Override public MovAvgReducer readResult(StreamInput in) throws IOException { MovAvgReducer result = new MovAvgReducer(); result.readFrom(in); return result; } }; public static void registerStreams() { ReducerStreams.registerStream(STREAM, TYPE.stream()); } private static final Function<Aggregation, InternalAggregation> FUNCTION = new Function<Aggregation, InternalAggregation>() { @Override public InternalAggregation apply(Aggregation input) { return (InternalAggregation) input; } }; private ValueFormatter formatter; private GapPolicy gapPolicy; private int window; private MovAvgModel model; private int predict; public MovAvgReducer() { } public MovAvgReducer(String name, String[] bucketsPaths, @Nullable ValueFormatter formatter, GapPolicy gapPolicy, int window, int predict, MovAvgModel model, Map<String, Object> metadata) { super(name, bucketsPaths, metadata); this.formatter = formatter; this.gapPolicy = gapPolicy; this.window = window; this.model = model; this.predict = predict; } @Override public Type type() { return TYPE; } @Override public InternalAggregation reduce(InternalAggregation aggregation, ReduceContext reduceContext) { InternalHistogram histo = (InternalHistogram) aggregation; List<? extends InternalHistogram.Bucket> buckets = histo.getBuckets(); InternalHistogram.Factory<? extends InternalHistogram.Bucket> factory = histo.getFactory(); List newBuckets = new ArrayList<>(); EvictingQueue<Double> values = EvictingQueue.create(this.window); long lastKey = 0; long interval = Long.MAX_VALUE; Object currentKey; for (InternalHistogram.Bucket bucket : buckets) { Double thisBucketValue = resolveBucketValue(histo, bucket, bucketsPaths()[0], gapPolicy); currentKey = bucket.getKey(); if (!(thisBucketValue == null || thisBucketValue.equals(Double.NaN))) { values.offer(thisBucketValue); double movavg = model.next(values); List<InternalAggregation> aggs = new ArrayList<>( Lists.transform(bucket.getAggregations().asList(), FUNCTION)); aggs.add(new InternalSimpleValue(name(), movavg, formatter, new ArrayList<Reducer>(), metaData())); InternalHistogram.Bucket newBucket = factory.createBucket(currentKey, bucket.getDocCount(), new InternalAggregations(aggs), bucket.getKeyed(), bucket.getFormatter()); newBuckets.add(newBucket); } else { newBuckets.add(bucket); } if (predict > 0) { if (currentKey instanceof Number) { interval = Math.min(interval, ((Number) bucket.getKey()).longValue() - lastKey); lastKey = ((Number) bucket.getKey()).longValue(); } else if (currentKey instanceof DateTime) { interval = Math.min(interval, ((DateTime) bucket.getKey()).getMillis() - lastKey); lastKey = ((DateTime) bucket.getKey()).getMillis(); } else { throw new AggregationExecutionException( "Expected key of type Number or DateTime but got [" + currentKey + "]"); } } } if (buckets.size() > 0 && predict > 0) { boolean keyed; ValueFormatter formatter; keyed = buckets.get(0).getKeyed(); formatter = buckets.get(0).getFormatter(); double[] predictions = model.predict(values, predict); for (int i = 0; i < predictions.length; i++) { List<InternalAggregation> aggs = new ArrayList<>(); aggs.add(new InternalSimpleValue(name(), predictions[i], formatter, new ArrayList<Reducer>(), metaData())); InternalHistogram.Bucket newBucket = factory.createBucket(lastKey + (interval * (i + 1)), 0, new InternalAggregations(aggs), keyed, formatter); newBuckets.add(newBucket); } } return factory.create(newBuckets, histo); } @Override public void doReadFrom(StreamInput in) throws IOException { formatter = ValueFormatterStreams.readOptional(in); gapPolicy = GapPolicy.readFrom(in); window = in.readVInt(); predict = in.readVInt(); model = MovAvgModelStreams.read(in); } @Override public void doWriteTo(StreamOutput out) throws IOException { ValueFormatterStreams.writeOptional(formatter, out); gapPolicy.writeTo(out); out.writeVInt(window); out.writeVInt(predict); model.writeTo(out); } public static class Factory extends ReducerFactory { private final ValueFormatter formatter; private GapPolicy gapPolicy; private int window; private MovAvgModel model; private int predict; public Factory(String name, String[] bucketsPaths, @Nullable ValueFormatter formatter, GapPolicy gapPolicy, int window, int predict, MovAvgModel model) { super(name, TYPE.name(), bucketsPaths); this.formatter = formatter; this.gapPolicy = gapPolicy; this.window = window; this.model = model; this.predict = predict; } @Override protected Reducer createInternal(Map<String, Object> metaData) throws IOException { return new MovAvgReducer(name, bucketsPaths, formatter, gapPolicy, window, predict, model, metaData); } @Override public void doValidate(AggregatorFactory parent, AggregatorFactory[] aggFactories, List<ReducerFactory> reducerFactories) { if (bucketsPaths.length != 1) { throw new IllegalStateException(Reducer.Parser.BUCKETS_PATH.getPreferredName() + " must contain a single entry for reducer [" + name + "]"); } if (!(parent instanceof HistogramAggregator.Factory)) { throw new IllegalStateException( "derivative reducer [" + name + "] must have a histogram or date_histogram as parent"); } else { HistogramAggregator.Factory histoParent = (HistogramAggregator.Factory) parent; if (histoParent.minDocCount() != 0) { throw new IllegalStateException( "parent histogram of derivative reducer [" + name + "] must have min_doc_count of 0"); } } } } }