[TESTS] randomize metric type, better naming, fix gap handling
- Randomizes the metric type between min/max/avg. Should have identical behavior, but good to test - Fixes improper handling of gaps due to a bug in the production of the "expected" dataset. Due to this fix, randomization of gap policy was re-enabled - Bunch of renaming to be more descriptive and less verbose
This commit is contained in:
Zachary Tong
parent
a03cefcece
commit
2a74f2ce0f
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@ -21,7 +21,6 @@ package org.elasticsearch.search.aggregations.reducers.moving.avg;
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import com.google.common.collect.EvictingQueue;
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import org.elasticsearch.action.index.IndexRequestBuilder;
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import org.elasticsearch.action.search.SearchPhaseExecutionException;
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import org.elasticsearch.action.search.SearchResponse;
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@ -30,22 +29,21 @@ import org.elasticsearch.search.aggregations.bucket.filter.InternalFilter;
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import org.elasticsearch.search.aggregations.bucket.histogram.Histogram;
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import org.elasticsearch.search.aggregations.bucket.histogram.InternalHistogram;
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import org.elasticsearch.search.aggregations.bucket.histogram.InternalHistogram.Bucket;
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import org.elasticsearch.search.aggregations.metrics.ValuesSourceMetricsAggregationBuilder;
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import org.elasticsearch.search.aggregations.reducers.BucketHelpers;
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import org.elasticsearch.search.aggregations.reducers.SimpleValue;
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import org.elasticsearch.search.aggregations.reducers.movavg.models.*;
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import org.elasticsearch.test.ElasticsearchIntegrationTest;
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import org.hamcrest.Matchers;
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import org.junit.Test;
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import java.util.ArrayList;
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import java.util.List;
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import static org.elasticsearch.common.xcontent.XContentFactory.jsonBuilder;
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import static org.elasticsearch.search.aggregations.AggregationBuilders.histogram;
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import static org.elasticsearch.search.aggregations.AggregationBuilders.sum;
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import static org.elasticsearch.search.aggregations.reducers.ReducerBuilders.smooth;
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import static org.elasticsearch.search.aggregations.AggregationBuilders.*;
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import static org.elasticsearch.search.aggregations.reducers.ReducerBuilders.movingAvg;
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import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertSearchResponse;
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import static org.hamcrest.Matchers.equalTo;
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import static org.hamcrest.Matchers.*;
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import static org.hamcrest.core.IsNull.notNullValue;
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@ElasticsearchIntegrationTest.SuiteScopeTest
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@ -62,16 +60,16 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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static BucketHelpers.GapPolicy gapPolicy;
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static long[] docCounts;
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static long[] valueCounts;
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static Double[] simpleMovAvgCounts;
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static Double[] linearMovAvgCounts;
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static Double[] singleExpMovAvgCounts;
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static Double[] doubleExpMovAvgCounts;
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static long[] docValues;
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static Double[] simpleDocCounts;
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static Double[] linearDocCounts;
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static Double[] singleDocCounts;
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static Double[] doubleDocCounts;
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static Double[] simpleMovAvgValueCounts;
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static Double[] linearMovAvgValueCounts;
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static Double[] singleExpMovAvgValueCounts;
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static Double[] doubleExpMovAvgValueCounts;
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static Double[] simpleDocValues;
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static Double[] linearDocValues;
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static Double[] singleDocValues;
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static Double[] doubleDocValues;
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@Override
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public void setupSuiteScopeCluster() throws Exception {
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@ -83,13 +81,14 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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numValueBuckets = randomIntBetween(6, 80);
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numFilledValueBuckets = numValueBuckets;
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windowSize = randomIntBetween(3,10);
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gapPolicy = BucketHelpers.GapPolicy.INSERT_ZEROS; // TODO randomBoolean() ? BucketHelpers.GapPolicy.IGNORE : BucketHelpers.GapPolicy.INSERT_ZEROS;
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gapPolicy = randomBoolean() ? BucketHelpers.GapPolicy.IGNORE : BucketHelpers.GapPolicy.INSERT_ZEROS;
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docCounts = new long[numValueBuckets];
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valueCounts = new long[numValueBuckets];
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docValues = new long[numValueBuckets];
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for (int i = 0; i < numValueBuckets; i++) {
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docCounts[i] = randomIntBetween(0, 20);
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valueCounts[i] = randomIntBetween(1,20); //this will be used as a constant for all values within a bucket
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docValues[i] = randomIntBetween(1,20); //this will be used as a constant for all values within a bucket
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}
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// Used for the gap tests
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@ -104,14 +103,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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this.setupLinear();
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this.setupSingle();
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this.setupDouble();
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for (int i = 0; i < numValueBuckets; i++) {
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for (int docs = 0; docs < docCounts[i]; docs++) {
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builders.add(client().prepareIndex("idx", "type").setSource(jsonBuilder().startObject()
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.field(SINGLE_VALUED_FIELD_NAME, i * interval)
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.field(SINGLE_VALUED_VALUE_FIELD_NAME, 1).endObject()));
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.field(SINGLE_VALUED_VALUE_FIELD_NAME, docValues[i]).endObject()));
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}
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}
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@ -120,24 +117,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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}
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private void setupSimple() {
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simpleMovAvgCounts = new Double[numValueBuckets];
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simpleDocCounts = new Double[numValueBuckets];
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EvictingQueue<Double> window = EvictingQueue.create(windowSize);
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for (int i = 0; i < numValueBuckets; i++) {
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double thisValue = docCounts[i];
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window.offer(thisValue);
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double movAvg = 0;
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for (double value : window) {
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movAvg += value;
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if (docCounts[i] == 0 && gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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}
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movAvg /= window.size();
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simpleMovAvgCounts[i] = movAvg;
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}
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window.clear();
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simpleMovAvgValueCounts = new Double[numValueBuckets];
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for (int i = 0; i < numValueBuckets; i++) {
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window.offer((double)docCounts[i]);
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double movAvg = 0;
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@ -146,7 +131,34 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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}
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movAvg /= window.size();
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simpleMovAvgValueCounts[i] = movAvg;
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simpleDocCounts[i] = movAvg;
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}
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window.clear();
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simpleDocValues = new Double[numValueBuckets];
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for (int i = 0; i < numValueBuckets; i++) {
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if (docCounts[i] == 0) {
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// If there was a gap in doc counts and we are ignoring, just skip this bucket
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if (gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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} else if (gapPolicy.equals(BucketHelpers.GapPolicy.INSERT_ZEROS)) {
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// otherwise insert a zero instead of the true value
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window.offer(0.0);
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} else {
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window.offer((double) docValues[i]);
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}
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} else {
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//if there are docs in this bucket, insert the regular value
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window.offer((double) docValues[i]);
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}
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double movAvg = 0;
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for (double value : window) {
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movAvg += value;
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}
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movAvg /= window.size();
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simpleDocValues[i] = movAvg;
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}
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@ -154,14 +166,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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private void setupLinear() {
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EvictingQueue<Double> window = EvictingQueue.create(windowSize);
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linearMovAvgCounts = new Double[numValueBuckets];
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linearDocCounts = new Double[numValueBuckets];
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window.clear();
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for (int i = 0; i < numValueBuckets; i++) {
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double thisValue = docCounts[i];
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if (thisValue == -1) {
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thisValue = 0;
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if (docCounts[i] == 0 && gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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}
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window.offer(thisValue);
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window.offer((double)docCounts[i]);
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double avg = 0;
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long totalWeight = 1;
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@ -172,15 +183,27 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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totalWeight += current;
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current += 1;
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}
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linearMovAvgCounts[i] = avg / totalWeight;
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linearDocCounts[i] = avg / totalWeight;
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}
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window.clear();
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linearMovAvgValueCounts = new Double[numValueBuckets];
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linearDocValues = new Double[numValueBuckets];
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for (int i = 0; i < numValueBuckets; i++) {
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double thisValue = docCounts[i];
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window.offer(thisValue);
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if (docCounts[i] == 0) {
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// If there was a gap in doc counts and we are ignoring, just skip this bucket
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if (gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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} else if (gapPolicy.equals(BucketHelpers.GapPolicy.INSERT_ZEROS)) {
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// otherwise insert a zero instead of the true value
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window.offer(0.0);
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} else {
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window.offer((double) docValues[i]);
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}
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} else {
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//if there are docs in this bucket, insert the regular value
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window.offer((double) docValues[i]);
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}
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double avg = 0;
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long totalWeight = 1;
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@ -191,39 +214,17 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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totalWeight += current;
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current += 1;
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}
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linearMovAvgValueCounts[i] = avg / totalWeight;
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linearDocValues[i] = avg / totalWeight;
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}
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}
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private void setupSingle() {
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EvictingQueue<Double> window = EvictingQueue.create(windowSize);
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singleExpMovAvgCounts = new Double[numValueBuckets];
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singleDocCounts = new Double[numValueBuckets];
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for (int i = 0; i < numValueBuckets; i++) {
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double thisValue = docCounts[i];
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if (thisValue == -1) {
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thisValue = 0;
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if (docCounts[i] == 0 && gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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}
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window.offer(thisValue);
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double avg = 0;
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double alpha = 0.5;
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boolean first = true;
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for (double value : window) {
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if (first) {
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avg = value;
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first = false;
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} else {
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avg = (value * alpha) + (avg * (1 - alpha));
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}
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}
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singleExpMovAvgCounts[i] = avg ;
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}
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singleExpMovAvgValueCounts = new Double[numValueBuckets];
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window.clear();
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for (int i = 0; i < numValueBuckets; i++) {
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window.offer((double)docCounts[i]);
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double avg = 0;
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@ -238,56 +239,53 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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avg = (value * alpha) + (avg * (1 - alpha));
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}
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}
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singleExpMovAvgCounts[i] = avg ;
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singleDocCounts[i] = avg ;
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}
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singleDocValues = new Double[numValueBuckets];
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window.clear();
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for (int i = 0; i < numValueBuckets; i++) {
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if (docCounts[i] == 0) {
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// If there was a gap in doc counts and we are ignoring, just skip this bucket
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if (gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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} else if (gapPolicy.equals(BucketHelpers.GapPolicy.INSERT_ZEROS)) {
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// otherwise insert a zero instead of the true value
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window.offer(0.0);
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} else {
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window.offer((double) docValues[i]);
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}
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} else {
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//if there are docs in this bucket, insert the regular value
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window.offer((double) docValues[i]);
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}
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double avg = 0;
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double alpha = 0.5;
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boolean first = true;
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for (double value : window) {
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if (first) {
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avg = value;
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first = false;
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} else {
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avg = (value * alpha) + (avg * (1 - alpha));
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}
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}
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singleDocValues[i] = avg ;
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}
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}
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private void setupDouble() {
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EvictingQueue<Double> window = EvictingQueue.create(windowSize);
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doubleExpMovAvgCounts = new Double[numValueBuckets];
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doubleDocCounts = new Double[numValueBuckets];
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for (int i = 0; i < numValueBuckets; i++) {
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double thisValue = docCounts[i];
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if (thisValue == -1) {
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thisValue = 0;
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if (docCounts[i] == 0 && gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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}
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window.offer(thisValue);
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double s = 0;
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double last_s = 0;
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// Trend value
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double b = 0;
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double last_b = 0;
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double alpha = 0.5;
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double beta = 0.5;
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int counter = 0;
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double last;
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for (double value : window) {
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last = value;
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if (counter == 1) {
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s = value;
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b = value - last;
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} else {
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s = alpha * value + (1.0d - alpha) * (last_s + last_b);
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b = beta * (s - last_s) + (1 - beta) * last_b;
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}
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counter += 1;
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last_s = s;
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last_b = b;
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}
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doubleExpMovAvgCounts[i] = s + (0 * b) ;
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}
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doubleExpMovAvgValueCounts = new Double[numValueBuckets];
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window.clear();
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for (int i = 0; i < numValueBuckets; i++) {
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window.offer((double)docCounts[i]);
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double s = 0;
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@ -317,7 +315,56 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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last_b = b;
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}
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doubleExpMovAvgValueCounts[i] = s + (0 * b) ;
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doubleDocCounts[i] = s + (0 * b) ;
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}
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doubleDocValues = new Double[numValueBuckets];
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window.clear();
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for (int i = 0; i < numValueBuckets; i++) {
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if (docCounts[i] == 0) {
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// If there was a gap in doc counts and we are ignoring, just skip this bucket
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if (gapPolicy.equals(BucketHelpers.GapPolicy.IGNORE)) {
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continue;
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} else if (gapPolicy.equals(BucketHelpers.GapPolicy.INSERT_ZEROS)) {
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// otherwise insert a zero instead of the true value
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window.offer(0.0);
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} else {
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window.offer((double) docValues[i]);
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}
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} else {
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//if there are docs in this bucket, insert the regular value
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window.offer((double) docValues[i]);
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}
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double s = 0;
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double last_s = 0;
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// Trend value
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double b = 0;
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double last_b = 0;
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double alpha = 0.5;
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double beta = 0.5;
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int counter = 0;
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double last;
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for (double value : window) {
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last = value;
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if (counter == 1) {
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s = value;
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b = value - last;
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} else {
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s = alpha * value + (1.0d - alpha) * (last_s + last_b);
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b = beta * (s - last_s) + (1 - beta) * last_b;
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}
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counter += 1;
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last_s = s;
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last_b = b;
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}
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doubleDocValues[i] = s + (0 * b) ;
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}
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}
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@ -332,8 +379,8 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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.addAggregation(
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histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
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.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
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.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
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.subAggregation(movingAvg("movingAvg")
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.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
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.subAggregation(movingAvg("movavg_counts")
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.window(windowSize)
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.modelBuilder(new SimpleModel.SimpleModelBuilder())
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.gapPolicy(gapPolicy)
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@ -342,7 +389,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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.window(windowSize)
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.modelBuilder(new SimpleModel.SimpleModelBuilder())
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.gapPolicy(gapPolicy)
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.setBucketsPaths("the_sum"))
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.setBucketsPaths("the_metric"))
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).execute().actionGet();
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assertSearchResponse(response);
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@ -356,13 +403,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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for (int i = 0; i < numValueBuckets; ++i) {
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Histogram.Bucket bucket = buckets.get(i);
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checkBucketKeyAndDocCount("Bucket " + i, bucket, i * interval, docCounts[i]);
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SimpleValue docCountMovAvg = bucket.getAggregations().get("movingAvg");
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SimpleValue docCountMovAvg = bucket.getAggregations().get("movavg_counts");
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assertThat(docCountMovAvg, notNullValue());
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assertThat(docCountMovAvg.value(), equalTo(simpleMovAvgCounts[i]));
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assertThat(docCountMovAvg.value(), equalTo(simpleDocCounts[i]));
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SimpleValue valuesMovAvg = bucket.getAggregations().get("movavg_values");
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assertThat(valuesMovAvg, notNullValue());
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assertThat(valuesMovAvg.value(), equalTo(simpleMovAvgCounts[i]));
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assertThat(valuesMovAvg.value(), equalTo(simpleDocValues[i]));
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}
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}
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@ -377,8 +424,8 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
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.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(new LinearModel.LinearModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
|
|
@ -387,7 +434,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.window(windowSize)
|
||||
.modelBuilder(new LinearModel.LinearModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
|
||||
assertSearchResponse(response);
|
||||
|
|
@ -401,13 +448,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
for (int i = 0; i < numValueBuckets; ++i) {
|
||||
Histogram.Bucket bucket = buckets.get(i);
|
||||
checkBucketKeyAndDocCount("Bucket " + i, bucket, i * interval, docCounts[i]);
|
||||
SimpleValue docCountMovAvg = bucket.getAggregations().get("movingAvg");
|
||||
SimpleValue docCountMovAvg = bucket.getAggregations().get("movavg_counts");
|
||||
assertThat(docCountMovAvg, notNullValue());
|
||||
assertThat(docCountMovAvg.value(), equalTo(linearMovAvgCounts[i]));
|
||||
assertThat(docCountMovAvg.value(), equalTo(linearDocCounts[i]));
|
||||
|
||||
SimpleValue valuesMovAvg = bucket.getAggregations().get("movavg_values");
|
||||
assertThat(valuesMovAvg, notNullValue());
|
||||
assertThat(valuesMovAvg.value(), equalTo(linearMovAvgCounts[i]));
|
||||
assertThat(valuesMovAvg.value(), equalTo(linearDocValues[i]));
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -422,8 +469,8 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(new SingleExpModel.SingleExpModelBuilder().alpha(0.5))
|
||||
.gapPolicy(gapPolicy)
|
||||
|
|
@ -432,7 +479,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.window(windowSize)
|
||||
.modelBuilder(new SingleExpModel.SingleExpModelBuilder().alpha(0.5))
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
|
||||
assertSearchResponse(response);
|
||||
|
|
@ -446,13 +493,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
for (int i = 0; i < numValueBuckets; ++i) {
|
||||
Histogram.Bucket bucket = buckets.get(i);
|
||||
checkBucketKeyAndDocCount("Bucket " + i, bucket, i * interval, docCounts[i]);
|
||||
SimpleValue docCountMovAvg = bucket.getAggregations().get("movingAvg");
|
||||
SimpleValue docCountMovAvg = bucket.getAggregations().get("movavg_counts");
|
||||
assertThat(docCountMovAvg, notNullValue());
|
||||
assertThat(docCountMovAvg.value(), equalTo(singleExpMovAvgCounts[i]));
|
||||
assertThat(docCountMovAvg.value(), equalTo(singleDocCounts[i]));
|
||||
|
||||
SimpleValue valuesMovAvg = bucket.getAggregations().get("movavg_values");
|
||||
assertThat(valuesMovAvg, notNullValue());
|
||||
assertThat(valuesMovAvg.value(), equalTo(singleExpMovAvgCounts[i]));
|
||||
assertThat(valuesMovAvg.value(), equalTo(singleDocValues[i]));
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -467,8 +514,8 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(new DoubleExpModel.DoubleExpModelBuilder().alpha(0.5).beta(0.5))
|
||||
.gapPolicy(gapPolicy)
|
||||
|
|
@ -477,7 +524,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.window(windowSize)
|
||||
.modelBuilder(new DoubleExpModel.DoubleExpModelBuilder().alpha(0.5).beta(0.5))
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
|
||||
assertSearchResponse(response);
|
||||
|
|
@ -491,13 +538,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
for (int i = 0; i < numValueBuckets; ++i) {
|
||||
Histogram.Bucket bucket = buckets.get(i);
|
||||
checkBucketKeyAndDocCount("Bucket " + i, bucket, i * interval, docCounts[i]);
|
||||
SimpleValue docCountMovAvg = bucket.getAggregations().get("movingAvg");
|
||||
SimpleValue docCountMovAvg = bucket.getAggregations().get("movavg_counts");
|
||||
assertThat(docCountMovAvg, notNullValue());
|
||||
assertThat(docCountMovAvg.value(), equalTo(doubleExpMovAvgCounts[i]));
|
||||
assertThat(docCountMovAvg.value(), equalTo(doubleDocCounts[i]));
|
||||
|
||||
SimpleValue valuesMovAvg = bucket.getAggregations().get("movavg_values");
|
||||
assertThat(valuesMovAvg, notNullValue());
|
||||
assertThat(valuesMovAvg.value(), equalTo(doubleExpMovAvgCounts[i]));
|
||||
assertThat(valuesMovAvg.value(), equalTo(doubleDocValues[i]));
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -509,12 +556,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(0)
|
||||
.modelBuilder(new SimpleModel.SimpleModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
fail("MovingAvg should not accept a window that is zero");
|
||||
|
||||
|
|
@ -531,13 +578,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
client()
|
||||
.prepareSearch("idx")
|
||||
.addAggregation(
|
||||
range("histo").field(SINGLE_VALUED_FIELD_NAME).addRange(0,10)
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
range("histo").field(SINGLE_VALUED_FIELD_NAME).addRange(0, 10)
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(0)
|
||||
.modelBuilder(new SimpleModel.SimpleModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
fail("MovingAvg should not accept non-histogram as parent");
|
||||
|
||||
|
|
@ -554,8 +601,8 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(-10)
|
||||
.modelBuilder(new SimpleModel.SimpleModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
|
|
@ -578,12 +625,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field("test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(new SimpleModel.SimpleModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
|
||||
assertSearchResponse(response);
|
||||
|
|
@ -603,13 +650,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.predict(0)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
fail("MovingAvg should not accept a prediction size that is zero");
|
||||
|
||||
|
|
@ -626,13 +673,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field(SINGLE_VALUED_FIELD_NAME).interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", SINGLE_VALUED_VALUE_FIELD_NAME))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.predict(-10)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
fail("MovingAvg should not accept a prediction size that is negative");
|
||||
|
||||
|
|
@ -655,12 +702,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
.addAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
|
||||
assertSearchResponse(response);
|
||||
|
|
@ -671,12 +718,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
List<? extends Bucket> buckets = histo.getBuckets();
|
||||
assertThat(buckets.size(), equalTo(numValueBuckets));
|
||||
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movingAvg"))).value();
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movavg_counts"))).value();
|
||||
assertThat(Double.compare(lastValue, 0.0d), greaterThanOrEqualTo(0));
|
||||
|
||||
double currentValue;
|
||||
for (int i = 1; i < numValueBuckets - 2; i++) {
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movavg_counts"))).value();
|
||||
|
||||
// Since there are only two values in this test, at the beginning and end, the moving average should
|
||||
// decrease every step (until it reaches zero). Crude way to check that it's doing the right thing
|
||||
|
|
@ -687,7 +734,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
}
|
||||
|
||||
// The last bucket has a real value, so this should always increase the moving avg
|
||||
currentValue = ((SimpleValue)(buckets.get(numValueBuckets - 1).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(numValueBuckets - 1).getAggregations().get("movavg_counts"))).value();
|
||||
assertThat(Double.compare(lastValue, currentValue), equalTo(-1));
|
||||
}
|
||||
|
||||
|
|
@ -698,19 +745,19 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
public void testGiantGapWithPredict() {
|
||||
|
||||
MovAvgModelBuilder model = randomModelBuilder();
|
||||
int numPredictions = randomIntBetween(0, 10);
|
||||
int numPredictions = randomIntBetween(1, 10);
|
||||
SearchResponse response = client()
|
||||
.prepareSearch("idx")
|
||||
.addAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(model)
|
||||
.gapPolicy(gapPolicy)
|
||||
.predict(numPredictions)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
).execute().actionGet();
|
||||
|
||||
assertSearchResponse(response);
|
||||
|
|
@ -721,12 +768,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
List<? extends Bucket> buckets = histo.getBuckets();
|
||||
assertThat(buckets.size(), equalTo(numValueBuckets + numPredictions));
|
||||
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movingAvg"))).value();
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movavg_counts"))).value();
|
||||
assertThat(Double.compare(lastValue, 0.0d), greaterThanOrEqualTo(0));
|
||||
|
||||
double currentValue;
|
||||
for (int i = 1; i < numValueBuckets - 2; i++) {
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movavg_counts"))).value();
|
||||
|
||||
// Since there are only two values in this test, at the beginning and end, the moving average should
|
||||
// decrease every step (until it reaches zero). Crude way to check that it's doing the right thing
|
||||
|
|
@ -737,15 +784,15 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
}
|
||||
|
||||
// The last bucket has a real value, so this should always increase the moving avg
|
||||
currentValue = ((SimpleValue)(buckets.get(numValueBuckets - 1).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(numValueBuckets - 1).getAggregations().get("movavg_counts"))).value();
|
||||
assertThat(Double.compare(lastValue, currentValue), equalTo(-1));
|
||||
|
||||
// Now check predictions
|
||||
for (int i = numValueBuckets; i < numValueBuckets + numPredictions; i++) {
|
||||
// Unclear at this point which direction the predictions will go, just verify they are
|
||||
// not null, and that we don't have the_sum anymore
|
||||
assertThat((buckets.get(i).getAggregations().get("movingAvg")), notNullValue());
|
||||
assertThat((buckets.get(i).getAggregations().get("the_sum")), nullValue());
|
||||
// not null, and that we don't have the_metric anymore
|
||||
assertThat((buckets.get(i).getAggregations().get("movavg_counts")), notNullValue());
|
||||
assertThat((buckets.get(i).getAggregations().get("the_metric")), nullValue());
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -763,12 +810,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
filter("filtered").filter(new RangeFilterBuilder("gap_test").from(1)).subAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
)
|
||||
|
||||
).execute().actionGet();
|
||||
|
|
@ -789,7 +836,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
double currentValue;
|
||||
double lastValue = 0.0;
|
||||
for (int i = 0; i < numValueBuckets - 1; i++) {
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movavg_counts"))).value();
|
||||
|
||||
assertThat(Double.compare(lastValue, currentValue), lessThanOrEqualTo(0));
|
||||
lastValue = currentValue;
|
||||
|
|
@ -808,13 +855,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
filter("filtered").filter(new RangeFilterBuilder("gap_test").from(1)).subAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.predict(numPredictions)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
)
|
||||
|
||||
).execute().actionGet();
|
||||
|
|
@ -835,7 +882,7 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
double currentValue;
|
||||
double lastValue = 0.0;
|
||||
for (int i = 0; i < numValueBuckets - 1; i++) {
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movavg_counts"))).value();
|
||||
|
||||
assertThat(Double.compare(lastValue, currentValue), lessThanOrEqualTo(0));
|
||||
lastValue = currentValue;
|
||||
|
|
@ -844,9 +891,9 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
// Now check predictions
|
||||
for (int i = numValueBuckets; i < numValueBuckets + numPredictions; i++) {
|
||||
// Unclear at this point which direction the predictions will go, just verify they are
|
||||
// not null, and that we don't have the_sum anymore
|
||||
assertThat((buckets.get(i).getAggregations().get("movingAvg")), notNullValue());
|
||||
assertThat((buckets.get(i).getAggregations().get("the_sum")), nullValue());
|
||||
// not null, and that we don't have the_metric anymore
|
||||
assertThat((buckets.get(i).getAggregations().get("movavg_counts")), notNullValue());
|
||||
assertThat((buckets.get(i).getAggregations().get("the_metric")), nullValue());
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -864,12 +911,12 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
filter("filtered").filter(new RangeFilterBuilder("gap_test").to((interval * (numValueBuckets - 1) - interval))).subAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
)
|
||||
|
||||
).execute().actionGet();
|
||||
|
|
@ -888,9 +935,9 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
assertThat(buckets.size(), equalTo(numValueBuckets));
|
||||
|
||||
double currentValue;
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movingAvg"))).value();
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movavg_counts"))).value();
|
||||
for (int i = 1; i < numValueBuckets - 1; i++) {
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movavg_counts"))).value();
|
||||
|
||||
assertThat(Double.compare(lastValue, currentValue), greaterThanOrEqualTo(0));
|
||||
lastValue = currentValue;
|
||||
|
|
@ -909,13 +956,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
filter("filtered").filter(new RangeFilterBuilder("gap_test").to((interval * (numValueBuckets - 1) - interval))).subAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.extendedBounds(0L, (long) (interval * (numValueBuckets - 1)))
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.predict(numPredictions)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
)
|
||||
|
||||
).execute().actionGet();
|
||||
|
|
@ -934,9 +981,9 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
assertThat(buckets.size(), equalTo(numValueBuckets + numPredictions));
|
||||
|
||||
double currentValue;
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movingAvg"))).value();
|
||||
double lastValue = ((SimpleValue)(buckets.get(0).getAggregations().get("movavg_counts"))).value();
|
||||
for (int i = 1; i < numValueBuckets - 1; i++) {
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movingAvg"))).value();
|
||||
currentValue = ((SimpleValue)(buckets.get(i).getAggregations().get("movavg_counts"))).value();
|
||||
|
||||
assertThat(Double.compare(lastValue, currentValue), greaterThanOrEqualTo(0));
|
||||
lastValue = currentValue;
|
||||
|
|
@ -945,9 +992,9 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
// Now check predictions
|
||||
for (int i = numValueBuckets; i < numValueBuckets + numPredictions; i++) {
|
||||
// Unclear at this point which direction the predictions will go, just verify they are
|
||||
// not null, and that we don't have the_sum anymore
|
||||
assertThat((buckets.get(i).getAggregations().get("movingAvg")), notNullValue());
|
||||
assertThat((buckets.get(i).getAggregations().get("the_sum")), nullValue());
|
||||
// not null, and that we don't have the_metric anymore
|
||||
assertThat((buckets.get(i).getAggregations().get("movavg_counts")), notNullValue());
|
||||
assertThat((buckets.get(i).getAggregations().get("the_metric")), nullValue());
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -962,13 +1009,13 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
// Filter so we are above all values
|
||||
filter("filtered").filter(new RangeFilterBuilder("gap_test").from((interval * (numValueBuckets - 1) + interval))).subAggregation(
|
||||
histogram("histo").field("gap_test").interval(interval).minDocCount(0)
|
||||
.subAggregation(sum("the_sum").field(GAP_FIELD))
|
||||
.subAggregation(movingAvg("movingAvg")
|
||||
.subAggregation(randomMetric("the_metric", GAP_FIELD))
|
||||
.subAggregation(movingAvg("movavg_counts")
|
||||
.window(windowSize)
|
||||
.modelBuilder(randomModelBuilder())
|
||||
.gapPolicy(gapPolicy)
|
||||
.predict(numPredictions)
|
||||
.setBucketsPaths("the_sum"))
|
||||
.setBucketsPaths("the_metric"))
|
||||
)
|
||||
|
||||
).execute().actionGet();
|
||||
|
|
@ -1014,5 +1061,20 @@ public class MovAvgTests extends ElasticsearchIntegrationTest {
|
|||
return new SimpleModel.SimpleModelBuilder();
|
||||
}
|
||||
}
|
||||
|
||||
private ValuesSourceMetricsAggregationBuilder randomMetric(String name, String field) {
|
||||
int rand = randomIntBetween(0,3);
|
||||
|
||||
switch (rand) {
|
||||
case 0:
|
||||
return min(name).field(field);
|
||||
case 2:
|
||||
return max(name).field(field);
|
||||
case 3:
|
||||
return avg(name).field(field);
|
||||
default:
|
||||
return avg(name).field(field);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue