1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
|
/*
* Licensed to Elasticsearch under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* 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.metrics.percentiles.tdigest;
import org.elasticsearch.common.io.stream.Writeable.Reader;
import org.elasticsearch.search.DocValueFormat;
import org.elasticsearch.search.aggregations.metrics.percentiles.InternalPercentilesRanksTestCase;
import org.elasticsearch.search.aggregations.metrics.percentiles.ParsedPercentileRanks;
import org.elasticsearch.search.aggregations.pipeline.PipelineAggregator;
import java.util.List;
import java.util.Map;
public class InternalTDigestPercentilesRanksTests extends InternalPercentilesRanksTestCase<InternalTDigestPercentileRanks> {
@Override
protected InternalTDigestPercentileRanks createTestInstance(String name, List<PipelineAggregator> aggregators,
Map<String, Object> metadata,
double[] cdfValues, boolean keyed, DocValueFormat format) {
TDigestState state = new TDigestState(100);
int numValues = randomInt(100);
for (int i = 0; i < numValues; ++i) {
state.add(randomDouble());
}
return new InternalTDigestPercentileRanks(name, cdfValues, state, keyed, format, aggregators, metadata);
}
@Override
protected void assertReduced(InternalTDigestPercentileRanks reduced, List<InternalTDigestPercentileRanks> inputs) {
// it is hard to check the values due to the inaccuracy of the algorithm
// the min/max values should be accurate due to the way the algo works so we can at least test those
double min = Double.POSITIVE_INFINITY;
double max = Double.NEGATIVE_INFINITY;
long totalCount = 0;
for (InternalTDigestPercentileRanks ranks : inputs) {
if (ranks.state.centroidCount() == 0) {
// quantiles would return NaN
continue;
}
totalCount += ranks.state.size();
min = Math.min(ranks.state.quantile(0), min);
max = Math.max(ranks.state.quantile(1), max);
}
assertEquals(totalCount, reduced.state.size());
if (totalCount > 0) {
assertEquals(reduced.state.quantile(0), min, 0d);
assertEquals(reduced.state.quantile(1), max, 0d);
}
}
@Override
protected Reader<InternalTDigestPercentileRanks> instanceReader() {
return InternalTDigestPercentileRanks::new;
}
@Override
protected Class<? extends ParsedPercentileRanks> parsedParsedPercentileRanksClass() {
return ParsedTDigestPercentileRanks.class;
}
}
|
