org.elasticsearch.search.aggregations.pipeline.EwmaModel Maven / Gradle / Ivy
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* ownership. Elasticsearch 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.elasticsearch.search.aggregations.pipeline;
import org.elasticsearch.common.Nullable;
import org.elasticsearch.common.io.stream.StreamInput;
import org.elasticsearch.common.io.stream.StreamOutput;
import org.elasticsearch.common.xcontent.XContentBuilder;
import java.io.IOException;
import java.text.ParseException;
import java.util.Arrays;
import java.util.Collection;
import java.util.Map;
import java.util.Objects;
/**
* Calculate a exponentially weighted moving average
*/
public class EwmaModel extends MovAvgModel {
public static final String NAME = "ewma";
private static final double DEFAULT_ALPHA = 0.3;
/**
* Controls smoothing of data. Also known as "level" value.
* Alpha = 1 retains no memory of past values
* (e.g. random walk), while alpha = 0 retains infinite memory of past values (e.g.
* mean of the series).
*/
private final double alpha;
public EwmaModel() {
this(DEFAULT_ALPHA);
}
public EwmaModel(double alpha) {
this.alpha = alpha;
}
/**
* Read from a stream.
*/
public EwmaModel(StreamInput in) throws IOException {
alpha = in.readDouble();
}
@Override
public void writeTo(StreamOutput out) throws IOException {
out.writeDouble(alpha);
}
@Override
public String getWriteableName() {
return NAME;
}
@Override
public boolean canBeMinimized() {
return true;
}
@Override
public MovAvgModel neighboringModel() {
double alpha = Math.random();
return new EwmaModel(alpha);
}
@Override
public MovAvgModel clone() {
return new EwmaModel(this.alpha);
}
@Override
protected double[] doPredict(Collection values, int numPredictions) {
double[] predictions = new double[numPredictions];
// EWMA just emits the same final prediction repeatedly.
Arrays.fill(predictions, next(values));
return predictions;
}
@Override
public double next(Collection values) {
return MovingFunctions.ewma(values.stream().mapToDouble(Double::doubleValue).toArray(), alpha);
}
@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.field(MovAvgPipelineAggregationBuilder.MODEL.getPreferredName(), NAME);
builder.startObject(MovAvgPipelineAggregationBuilder.SETTINGS.getPreferredName());
builder.field("alpha", alpha);
builder.endObject();
return builder;
}
public static final AbstractModelParser PARSER = new AbstractModelParser() {
@Override
public MovAvgModel parse(@Nullable Map settings, String pipelineName, int windowSize) throws ParseException {
double alpha = parseDoubleParam(settings, "alpha", DEFAULT_ALPHA);
checkUnrecognizedParams(settings);
return new EwmaModel(alpha);
}
};
@Override
public int hashCode() {
return Objects.hash(alpha);
}
@Override
public boolean equals(Object obj) {
if (obj == null) {
return false;
}
if (getClass() != obj.getClass()) {
return false;
}
EwmaModel other = (EwmaModel) obj;
return Objects.equals(alpha, other.alpha);
}
public static class EWMAModelBuilder implements MovAvgModelBuilder {
private double alpha = DEFAULT_ALPHA;
/**
* Alpha controls the smoothing of the data. Alpha = 1 retains no memory of past values
* (e.g. a random walk), while alpha = 0 retains infinite memory of past values (e.g.
* the series mean). Useful values are somewhere in between. Defaults to 0.5.
*
* @param alpha A double between 0-1 inclusive, controls data smoothing
*
* @return The builder to continue chaining
*/
public EWMAModelBuilder alpha(double alpha) {
this.alpha = alpha;
return this;
}
@Override
public XContentBuilder toXContent(XContentBuilder builder, Params params) throws IOException {
builder.field(MovAvgPipelineAggregationBuilder.MODEL.getPreferredName(), NAME);
builder.startObject(MovAvgPipelineAggregationBuilder.SETTINGS.getPreferredName());
builder.field("alpha", alpha);
builder.endObject();
return builder;
}
@Override
public MovAvgModel build() {
return new EwmaModel(alpha);
}
}
}