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+/*
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+ * Licensed to Elasticsearch under one or more contributor
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+ * license agreements. See the NOTICE file distributed with
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+ * this work for additional information regarding copyright
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+ * ownership. Elasticsearch licenses this file to you under
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+ * the Apache License, Version 2.0 (the "License"); you may
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+ * not use this file except in compliance with the License.
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+ * You may obtain a copy of the License at
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+ *
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+ * http://www.apache.org/licenses/LICENSE-2.0
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+ *
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+ * Unless required by applicable law or agreed to in writing,
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+ * software distributed under the License is distributed on an
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+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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+ * KIND, either express or implied. See the License for the
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+ * specific language governing permissions and limitations
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+ * under the License.
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+ */
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+
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+package org.elasticsearch.search.aggregations.metrics;
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+
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+import java.util.HashMap;
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+import java.util.List;
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+import java.util.Map;
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+import org.elasticsearch.common.io.stream.Writeable.Reader;
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+import org.elasticsearch.search.DocValueFormat;
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+import org.elasticsearch.search.aggregations.ParsedAggregation;
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+import org.elasticsearch.search.aggregations.pipeline.PipelineAggregator;
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+import org.elasticsearch.test.InternalAggregationTestCase;
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+
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+public class InternalWeightedAvgTests extends InternalAggregationTestCase<InternalWeightedAvg> {
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+
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+ @Override
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+ protected InternalWeightedAvg createTestInstance(
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+ String name,
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+ List<PipelineAggregator> pipelineAggregators,
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+ Map<String, Object> metaData
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+ ) {
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+ DocValueFormat formatter = randomNumericDocValueFormat();
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+ return new InternalWeightedAvg(
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+ name,
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+ randomDoubleBetween(0, 100000, true),
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+ randomDoubleBetween(0, 100000, true),
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+ formatter, pipelineAggregators, metaData);
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+ }
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+
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+ @Override
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+ protected Reader<InternalWeightedAvg> instanceReader() {
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+ return InternalWeightedAvg::new;
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+ }
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+
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+ @Override
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+ protected void assertReduced(InternalWeightedAvg reduced, List<InternalWeightedAvg> inputs) {
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+ double sum = 0;
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+ double weight = 0;
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+ for (InternalWeightedAvg in : inputs) {
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+ sum += in.getSum();
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+ weight += in.getWeight();
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+ }
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+ assertEquals(sum, reduced.getSum(), 0.0000001);
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+ assertEquals(weight, reduced.getWeight(), 0.0000001);
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+ assertEquals(sum / weight, reduced.getValue(), 0.0000001);
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+ }
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+
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+ @Override
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+ protected void assertFromXContent(InternalWeightedAvg avg, ParsedAggregation parsedAggregation) {
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+ ParsedWeightedAvg parsed = ((ParsedWeightedAvg) parsedAggregation);
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+ assertEquals(avg.getValue(), parsed.getValue(), Double.MIN_VALUE);
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+ // we don't print out VALUE_AS_STRING for avg.getCount() == 0, so we cannot get the exact same value back
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+ if (avg.getWeight() != 0) {
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+ assertEquals(avg.getValueAsString(), parsed.getValueAsString());
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+ }
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+ }
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+
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+ @Override
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+ protected InternalWeightedAvg mutateInstance(InternalWeightedAvg instance) {
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+ String name = instance.getName();
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+ double sum = instance.getSum();
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+ double weight = instance.getWeight();
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+ DocValueFormat formatter = instance.getFormatter();
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+ List<PipelineAggregator> pipelineAggregators = instance.pipelineAggregators();
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+ Map<String, Object> metaData = instance.getMetaData();
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+ switch (between(0, 2)) {
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+ case 0:
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+ name += randomAlphaOfLength(5);
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+ break;
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+ case 1:
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+ if (Double.isFinite(sum)) {
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+ sum += between(1, 100);
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+ } else {
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+ sum = between(1, 100);
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+ }
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+ break;
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+ case 2:
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+ if (Double.isFinite(weight)) {
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+ weight += between(1, 100);
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+ } else {
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+ weight = between(1, 100);
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+ }
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+ break;
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+ case 3:
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+ if (metaData == null) {
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+ metaData = new HashMap<>(1);
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+ } else {
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+ metaData = new HashMap<>(instance.getMetaData());
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+ }
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+ metaData.put(randomAlphaOfLength(15), randomInt());
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+ break;
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+ default:
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+ throw new AssertionError("Illegal randomisation branch");
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+ }
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+ return new InternalWeightedAvg(name, sum, weight, formatter, pipelineAggregators, metaData);
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+ }
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+}
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David Findley